1 Introduction
 The notorious Sphere Packing Problem asks a simple question: What is the best way of stacking higher-dimensional oranges
Footnote 
1
 in a higher-dimensional supermarket? It is not too surprising that in dimension 
 $3$
, an optimal configuration arises when oranges (or cannonballs, which are not so juicy) are arranged in a hexagonal close packing, where laminated layers of spheres are assembled according to a suitable translation of the hexagonal lattice (fitting new spheres in the deep holes of the previous layer). What is remarkable is that this problem was proposed by Kepler around 1611 and was only solved in 1998 by Hales, in his famous large computer-assisted proof [Reference Hales18]. Recently, in 2016, the problem in dimensions
$3$
, an optimal configuration arises when oranges (or cannonballs, which are not so juicy) are arranged in a hexagonal close packing, where laminated layers of spheres are assembled according to a suitable translation of the hexagonal lattice (fitting new spheres in the deep holes of the previous layer). What is remarkable is that this problem was proposed by Kepler around 1611 and was only solved in 1998 by Hales, in his famous large computer-assisted proof [Reference Hales18]. Recently, in 2016, the problem in dimensions 
 $8$
 and
$8$
 and 
 $24$
 was solved by Viazovska et al. [Reference Cohn, Kumar, Miller, Radchenko and Viazovska10, Reference Viazovska27], introducing a remarkable new construction using quasi-modular forms to define certain smooth auxiliary functions
$24$
 was solved by Viazovska et al. [Reference Cohn, Kumar, Miller, Radchenko and Viazovska10, Reference Viazovska27], introducing a remarkable new construction using quasi-modular forms to define certain smooth auxiliary functions 
 $f_8$
 and
$f_8$
 and 
 $f_{24}$
 satisfying certain sign constraints in physical and frequency space to solve the problem.Footnote 
2
 To the best of our knowledge, there are only two other instances where Viazovska’s technique was used to construct auxiliary functions that were indeed used in the solution of some kind of optimization problem: (1) in the solution of a
$f_{24}$
 satisfying certain sign constraints in physical and frequency space to solve the problem.Footnote 
2
 To the best of our knowledge, there are only two other instances where Viazovska’s technique was used to construct auxiliary functions that were indeed used in the solution of some kind of optimization problem: (1) in the solution of a 
 $12$
-dimensional uncertainty principle by the Cohn and Gonçalves [Reference Cohn and Gonçalves9] (best constant and function); (2) in the proof of the universality of the
$12$
-dimensional uncertainty principle by the Cohn and Gonçalves [Reference Cohn and Gonçalves9] (best constant and function); (2) in the proof of the universality of the 
 $E_8$
 and Leech lattices by Cohn, Kumar, Miller, Radchenko and Viazovska [Reference Cohn, Kumar, Miller, Radchenko and Viazovska11].
$E_8$
 and Leech lattices by Cohn, Kumar, Miller, Radchenko and Viazovska [Reference Cohn, Kumar, Miller, Radchenko and Viazovska11].
1.1 Motivation
In this paper, we systematically study a new type of constrained sphere packing problem, where we forbid certain short distances between centers of spheres. We are then able to solve exactly this problem when the forbidden set is the complement of a finite collection of square roots of even integers. The main questions driving/inspiring the problems we study and solve in this manuscript are the following:
- 
• What other ‘natural’ discrete geometry problems can be solved using Viazovska’s modular forms construction technique? 
- 
• Can we embed the functions  $f_8$
 and $f_8$
 and $f_{24}$
 found by Viazovska in a larger family of functions $f_{24}$
 found by Viazovska in a larger family of functions $\{f_{d}\}_{8|d}$
 in such a way that these work as auxiliary functions that solve some kind of dual optimization problem of the question above? $\{f_{d}\}_{8|d}$
 in such a way that these work as auxiliary functions that solve some kind of dual optimization problem of the question above?
Our answer: Packings with forbidden distances and Theorems 3 and 4.
 We now comment about our answer. First of all, the idea of creating a larger family of functions 
 $\{f_{d}\}_{8|d}$
 that contains Viazovska’s functions was already explored in the interesting papers [Reference Rolen and Wagner25, Reference Feigenbaum, Grabner and Hardin15]. However, in these two papers, no geometrical optimization problem was solved, and the functions they generate are not related to ours. Also, it is worth pointing out that, as we shall see in the proof of Theorem 4, there are several constraints our functions
$\{f_{d}\}_{8|d}$
 that contains Viazovska’s functions was already explored in the interesting papers [Reference Rolen and Wagner25, Reference Feigenbaum, Grabner and Hardin15]. However, in these two papers, no geometrical optimization problem was solved, and the functions they generate are not related to ours. Also, it is worth pointing out that, as we shall see in the proof of Theorem 4, there are several constraints our functions 
 $\{H_d\}_{8|d}$
 satisfy. The troublesome part is to show that certain sign conditions are met, and these do not follow from positivity of Fourier coefficients (as in [Reference Feigenbaum, Grabner and Hardin15], conjecturally), since they indeed change sign in our case. To overcome this, we came up with a numerical procedure, inspired by the one in [Reference Cohn, Kumar, Miller, Radchenko and Viazovska10], and so our proof is unavoidably computer-assisted. Secondly, at first glance, one might say that imposing additional constraints in a sphere packing, such as forbidding certain distances, is esoteric or unnatural. However, from the coding theory perceptive (sphere packings in
$\{H_d\}_{8|d}$
 satisfy. The troublesome part is to show that certain sign conditions are met, and these do not follow from positivity of Fourier coefficients (as in [Reference Feigenbaum, Grabner and Hardin15], conjecturally), since they indeed change sign in our case. To overcome this, we came up with a numerical procedure, inspired by the one in [Reference Cohn, Kumar, Miller, Radchenko and Viazovska10], and so our proof is unavoidably computer-assisted. Secondly, at first glance, one might say that imposing additional constraints in a sphere packing, such as forbidding certain distances, is esoteric or unnatural. However, from the coding theory perceptive (sphere packings in 
 $\mathbb {F}_q^m$
), this question has been asked already, studied to some extent and has applications. To the best of our knowledge, we believe we were the first to consider this question in Euclidean space; nevertheless, in coding theory, codes with forbidden distances have been the object of study in many occasions. See, for instance, [Reference Bassalygo, Cohen and Zémor1, Reference Bassalygo, Zinoviev, Zyablov, Pinsker and Poltyrev2, Reference Enomoto, Frankl, Ito and Nomura14, Reference Frankl16]. In Euclidean space, a cousin problem of the sphere packing problem is the chromatic number of
$\mathbb {F}_q^m$
), this question has been asked already, studied to some extent and has applications. To the best of our knowledge, we believe we were the first to consider this question in Euclidean space; nevertheless, in coding theory, codes with forbidden distances have been the object of study in many occasions. See, for instance, [Reference Bassalygo, Cohen and Zémor1, Reference Bassalygo, Zinoviev, Zyablov, Pinsker and Poltyrev2, Reference Enomoto, Frankl, Ito and Nomura14, Reference Frankl16]. In Euclidean space, a cousin problem of the sphere packing problem is the chromatic number of 
 $\mathbb {R}^d$
, and in this venue, mathematicians have considered already the version with forbidden distances; see, for instance, [Reference Berdnikov4, Reference Raigorodskii24, Reference Naslund21]. Thirdly, there are a bunch of unexpected features coming from our study that might drive further research, such as the following:
$\mathbb {R}^d$
, and in this venue, mathematicians have considered already the version with forbidden distances; see, for instance, [Reference Berdnikov4, Reference Raigorodskii24, Reference Naslund21]. Thirdly, there are a bunch of unexpected features coming from our study that might drive further research, such as the following:
 
 $\heartsuit $
 The functions
$\heartsuit $
 The functions 
 $\{H_d\}_{8|d}$
 we create in the proof of Theorem 4 have several curious properties that we have verified with a computer up to
$\{H_d\}_{8|d}$
 we create in the proof of Theorem 4 have several curious properties that we have verified with a computer up to 
 $d=1200$
, but they lack proper mathematical explanation. Proving these properties propagate in every dimension
$d=1200$
, but they lack proper mathematical explanation. Proving these properties propagate in every dimension 
 $8|d$
 would allow us to extend Theorem 4 to every dimension;
$8|d$
 would allow us to extend Theorem 4 to every dimension;
 
 $\heartsuit $
 The one-dimensional case we study in Section 2.1 is a very intriguing combinatorial/geometric problem that seems hard to analyze. The natural question here is to know when the best packing can be taken to be periodic, and we do provide a partial answer when the complement of the forbidden set is finite or has finitely many accumulation points (so to speak);
$\heartsuit $
 The one-dimensional case we study in Section 2.1 is a very intriguing combinatorial/geometric problem that seems hard to analyze. The natural question here is to know when the best packing can be taken to be periodic, and we do provide a partial answer when the complement of the forbidden set is finite or has finitely many accumulation points (so to speak);
 
 $\heartsuit $
 Perhaps the most interesting contribution of our manuscript is Theorem 1, which we single out. It turns out that in dimension
$\heartsuit $
 Perhaps the most interesting contribution of our manuscript is Theorem 1, which we single out. It turns out that in dimension 
 $48$
, the constraints we need to impose are rather simple and nice, and we show that extremal lattices are optimal. Moreover, it is conjectured that extremal lattices are optimal unconstrained sphere packings in dimension
$48$
, the constraints we need to impose are rather simple and nice, and we show that extremal lattices are optimal. Moreover, it is conjectured that extremal lattices are optimal unconstrained sphere packings in dimension 
 $48$
, so one can also see Theorem 1 as further evidence to Conjecture 1.
$48$
, so one can also see Theorem 1 as further evidence to Conjecture 1.
 
 $\heartsuit $
 Since the submission of this paper, there have been further results on this topic that we would like to highlight. In [Reference Boyvalenkov and Cherkashin5], Boyvalenkov and Cherkashin find the largest kissing number with forbidden distances in dimension 48 – a configuration avoiding the set
$\heartsuit $
 Since the submission of this paper, there have been further results on this topic that we would like to highlight. In [Reference Boyvalenkov and Cherkashin5], Boyvalenkov and Cherkashin find the largest kissing number with forbidden distances in dimension 48 – a configuration avoiding the set 
 $(-1/3,-1/6)\cup (1/6,1/3)$
. The related energy problem is investigated in [Reference Boyvalenkov and Dragnev7]. Moreover, and most surprisingly, in [Reference Boyvalenkov, Cherkashin and Dragnev6], Boyvalenkov, Cherkashin and Dragnev find several types of distance avoiding optimal spherical codes in
$(-1/3,-1/6)\cup (1/6,1/3)$
. The related energy problem is investigated in [Reference Boyvalenkov and Dragnev7]. Moreover, and most surprisingly, in [Reference Boyvalenkov, Cherkashin and Dragnev6], Boyvalenkov, Cherkashin and Dragnev find several types of distance avoiding optimal spherical codes in 
 $\mathbb {S}^{15}, \mathbb {S}^{21}, \mathbb {S}^{22}$
 and
$\mathbb {S}^{15}, \mathbb {S}^{21}, \mathbb {S}^{22}$
 and 
 $\mathbb {S}^{23}$
, via the linear programming method.
$\mathbb {S}^{23}$
, via the linear programming method.
1.2 Main results
 As a prototype example of the kind of problem we will be concerned with, imagine that we are trying to place solid disks of diameter 
 $1$
 in
$1$
 in 
 $\mathbb {R}^2$
, so to obtain the largest possible density. However, we require that either two disks kiss each other or their centers are far apart, say, with a distance not smaller than
$\mathbb {R}^2$
, so to obtain the largest possible density. However, we require that either two disks kiss each other or their centers are far apart, say, with a distance not smaller than 
 $\lambda>1$
. As
$\lambda>1$
. As 
 $\lambda $
 slowly increases, we expect to see a transition between disks being allowed to ‘freely’ move around and disks clumping together. Indeed, we show in Proposition 10 that as
$\lambda $
 slowly increases, we expect to see a transition between disks being allowed to ‘freely’ move around and disks clumping together. Indeed, we show in Proposition 10 that as 
 $\lambda \to \infty $
, the best arrangement is when three disks are placed on the vertices of an equilateral triangle of side length
$\lambda \to \infty $
, the best arrangement is when three disks are placed on the vertices of an equilateral triangle of side length 
 $1$
 (kissing each other) and the circuncenters of these triangles are placed in a hexagonal lattice of side length approximately
$1$
 (kissing each other) and the circuncenters of these triangles are placed in a hexagonal lattice of side length approximately 
 $\lambda $
. In this paper, we study a generalized version of this problem, where an arbitrary set of distances may be forbidden.
$\lambda $
. In this paper, we study a generalized version of this problem, where an arbitrary set of distances may be forbidden.
 We say that a sphere packing 
 $P=X+r B_d$
 (
$P=X+r B_d$
 (
 $B_d$
 is the unit ball in
$B_d$
 is the unit ball in 
 $\mathbb {R}^d$
 and X the set of centers) avoids a set
$\mathbb {R}^d$
 and X the set of centers) avoids a set 
 $A\subset (1,\infty )$
 if
$A\subset (1,\infty )$
 if 
 $|x_1-x_2|\notin 2 r A$
 for all distinct
$|x_1-x_2|\notin 2 r A$
 for all distinct 
 $x_1,x_2\in X$
 (A is a set of forbidden distances). For instance, for the problem described in the previous paragraph, the set A would be the interval
$x_1,x_2\in X$
 (A is a set of forbidden distances). For instance, for the problem described in the previous paragraph, the set A would be the interval 
 $(1,\lambda )$
. A periodic sphere packing is one where
$(1,\lambda )$
. A periodic sphere packing is one where 
 $X=\Lambda +Y$
,
$X=\Lambda +Y$
, 
 $\Lambda $
 is a lattice of minimal norm at least
$\Lambda $
 is a lattice of minimal norm at least 
 $2r$
 and
$2r$
 and 
 $Y\subset \mathbb {R}^d/\Lambda $
 is a nonempty finite set. A lattice packing is when
$Y\subset \mathbb {R}^d/\Lambda $
 is a nonempty finite set. A lattice packing is when 
 $\#Y=1$
. A lattice is even and unimodular if it has even squared norms and determinant
$\#Y=1$
. A lattice is even and unimodular if it has even squared norms and determinant 
 $1$
. Such lattice is said to be extremal if its minimal norm squared is equal to
$1$
. Such lattice is said to be extremal if its minimal norm squared is equal to 
 $2+2\lfloor d/24 \rfloor $
 (see Section 2 for more information). We now state the first main result of this paper.
$2+2\lfloor d/24 \rfloor $
 (see Section 2 for more information). We now state the first main result of this paper.
Theorem 1. Any even unimodular extremal lattice in 
 $\mathbb {R}^{48}$
 achieves maximal sphere packing density among all sphere packings that avoid the interval
$\mathbb {R}^{48}$
 achieves maximal sphere packing density among all sphere packings that avoid the interval 
 $\left (\sqrt {\tfrac 43},\sqrt {\tfrac 53}\right )$
. Moreover, we have uniqueness among all periodic packings: if
$\left (\sqrt {\tfrac 43},\sqrt {\tfrac 53}\right )$
. Moreover, we have uniqueness among all periodic packings: if 
 $P=\Lambda +Y+rB_d$
 is some periodic sphere packing in
$P=\Lambda +Y+rB_d$
 is some periodic sphere packing in 
 $\mathbb {R}^{48}$
 that avoids this interval and has maximal density, then
$\mathbb {R}^{48}$
 that avoids this interval and has maximal density, then 
 $\frac {\sqrt {6}}{2r}(\Lambda +Y)$
 is an even unimodular extremal lattice.
$\frac {\sqrt {6}}{2r}(\Lambda +Y)$
 is an even unimodular extremal lattice.
 Our result shows that any of the lattices 
 $P_{48p},P_{48q},P_{48m}$
 and
$P_{48p},P_{48q},P_{48m}$
 and 
 $P_{48n}$
 are optimal for this constrained packing problem. The first two lattices have a canonical construction as 2-neighbors of code lattices of extremal ternary codes (see [Reference Conway and Sloane12, p. 195] and [Reference Nebe22] for the other two).
$P_{48n}$
 are optimal for this constrained packing problem. The first two lattices have a canonical construction as 2-neighbors of code lattices of extremal ternary codes (see [Reference Conway and Sloane12, p. 195] and [Reference Nebe22] for the other two).
Conjecture 1. Any extremal lattice in dimension 
 $48$
 has maximal sphere packing density among all possible sphere packings.
$48$
 has maximal sphere packing density among all possible sphere packings.
 This conjecture is backed by the fact that no other better configuration is known. Perhaps an ‘easier’ to prove conjecture is that extremal lattices in 
 $48$
 dimensions are the best lattice packings. We believe Theorem 1 could be used together with a computer-assisted method to reduce the amount of cases needed to be checked and show that
$48$
 dimensions are the best lattice packings. We believe Theorem 1 could be used together with a computer-assisted method to reduce the amount of cases needed to be checked and show that 
 $P_{48p}$
 produces the best lattice packing; however, new ideas are needed here. Below, we state a bold conjecture, which serves more as a research direction, as we have no numerical evidence towards it.
$P_{48p}$
 produces the best lattice packing; however, new ideas are needed here. Below, we state a bold conjecture, which serves more as a research direction, as we have no numerical evidence towards it.
Conjecture 2. Let 
 $L<\mathbb {R}^{48}$
 be a lattice with minimal norm
$L<\mathbb {R}^{48}$
 be a lattice with minimal norm 
 $ \sqrt {6}$
. If there is
$ \sqrt {6}$
. If there is 
 $x \in L$
 with
$x \in L$
 with 
 $\sqrt {8}< |x| < \sqrt {10}$
, then L has covolume
$\sqrt {8}< |x| < \sqrt {10}$
, then L has covolume 
 $> 1$
.
$> 1$
.
 This conjecture in conjunction with Theorem 1 implies that extremal lattices in 
 $\mathbb {R}^{48}$
 are the best lattice sphere packings. To see this, given any lattice L, normalize it so it has minimal norm
$\mathbb {R}^{48}$
 are the best lattice sphere packings. To see this, given any lattice L, normalize it so it has minimal norm 
 $\sqrt {6}$
. If there is no point
$\sqrt {6}$
. If there is no point 
 $x\in L$
 such that
$x\in L$
 such that 
 $\sqrt {8}<|x|<\sqrt {10}$
, we then use Theorem 1; if such a point exists, we use the conjecture.
$\sqrt {8}<|x|<\sqrt {10}$
, we then use Theorem 1; if such a point exists, we use the conjecture.
 Theorem 1 will follow from Theorems 3 and 4, where we develop a new linear programming method, similar to the Cohn and Elkies linear programming bound [Reference Cohn and Elkies8, Theorem 3.1], and a generalization of Viazovska’s modular function technique [Reference Cohn, Kumar, Miller, Radchenko and Viazovska10, Reference Viazovska27] to find the desired ‘magic’ function. It turns out that if we allow ourselves to impose an extra condition on the spectrum of a given periodic configuration, one can prove a result similar to Theorem 1 in every dimension d multiple of 
 $8$
 not congruent to
$8$
 not congruent to 
 $16$
 modulo
$16$
 modulo 
 $24$
 up to
$24$
 up to 
 $d=1200$
.
$d=1200$
.
Define the forbidden set
 $$ \begin{align*}A_d=(1,\sqrt{1+2/a_d})\cup (\sqrt{1+2/a_d},\sqrt{1+4/a_d}) \cup \ldots \cup (\sqrt{(l_d-2)/a_d},\sqrt{l_d/a_d}), \end{align*} $$
$$ \begin{align*}A_d=(1,\sqrt{1+2/a_d})\cup (\sqrt{1+2/a_d},\sqrt{1+4/a_d}) \cup \ldots \cup (\sqrt{(l_d-2)/a_d},\sqrt{l_d/a_d}), \end{align*} $$
where
 $$ \begin{align} a_d=2+2\left\lfloor \frac{d}{24}\right\rfloor \ \ \text{ and } \ \ l_d = a_d + 4\bigg(\bigg\lfloor \frac{d-4}{12} \bigg\rfloor-\bigg\lfloor \frac{d}{24} \bigg\rfloor\bigg). \end{align} $$
$$ \begin{align} a_d=2+2\left\lfloor \frac{d}{24}\right\rfloor \ \ \text{ and } \ \ l_d = a_d + 4\bigg(\bigg\lfloor \frac{d-4}{12} \bigg\rfloor-\bigg\lfloor \frac{d}{24} \bigg\rfloor\bigg). \end{align} $$
Our second main result is the following.
Theorem 2. Let 
 $8\leq d\leq 1200$
, where d is divisible by
$8\leq d\leq 1200$
, where d is divisible by 
 $8$
 but
$8$
 but  . Let
. Let 
 $P=\Lambda +Y+rB_d$
 be some periodic sphere packing that avoids the set
$P=\Lambda +Y+rB_d$
 be some periodic sphere packing that avoids the set 
 $A_d$
 and such that the minimal norm of
$A_d$
 and such that the minimal norm of 
 $\Lambda ^*$
 is larger than
$\Lambda ^*$
 is larger than 
 $2r \sqrt {c_d}$
, where
$2r \sqrt {c_d}$
, where 
 $c_d$
 is given in Table 1. Then
$c_d$
 is given in Table 1. Then 
 $$ \begin{align*}\mathrm{dens}(P)\leq \mathrm{vol} \left( B_d\right) \left( \frac{\sqrt{a_d}}{2}\right)^d.\end{align*} $$
$$ \begin{align*}\mathrm{dens}(P)\leq \mathrm{vol} \left( B_d\right) \left( \frac{\sqrt{a_d}}{2}\right)^d.\end{align*} $$
Moreover, in case 
 $\#Y=1$
, then equality occurs if and only if
$\#Y=1$
, then equality occurs if and only if 
 $\frac {\sqrt {a_d}}{2r}\Lambda $
 is an even unimodular extremal lattice.
$\frac {\sqrt {a_d}}{2r}\Lambda $
 is an even unimodular extremal lattice.
 Indeed, Theorem 1 can be seen as a particular case of Theorem 2 since 
 $c_{48}=0$
 (hence, we no longer need to assume that P is periodic) and
$c_{48}=0$
 (hence, we no longer need to assume that P is periodic) and 
 $A_{48}=(1,\sqrt {4/3})\cup (\sqrt {4/3},\sqrt {5/3})$
, but the first interval can be removed because of a sign condition on the magic function of Theorem 4. Theorem 2 will follow from Theorem 3 (new linear programming bounds), Theorem 4 (magic contructions with modular forms) and Theorem 5 (equivalent to Theorem 2). As in dimension
$A_{48}=(1,\sqrt {4/3})\cup (\sqrt {4/3},\sqrt {5/3})$
, but the first interval can be removed because of a sign condition on the magic function of Theorem 4. Theorem 2 will follow from Theorem 3 (new linear programming bounds), Theorem 4 (magic contructions with modular forms) and Theorem 5 (equivalent to Theorem 2). As in dimension 
 $48$
, one could reduce
$48$
, one could reduce 
 $A_d$
 further for all d by understanding the sign changes of the functions in Theorem 4. However, there seems to be no particular interesting pattern, and the set
$A_d$
 further for all d by understanding the sign changes of the functions in Theorem 4. However, there seems to be no particular interesting pattern, and the set 
 $A_d$
 would be rather complicated and given by a table other than a simple formula. Appealing to simplicity, we decided for the above form. The dimensions
$A_d$
 would be rather complicated and given by a table other than a simple formula. Appealing to simplicity, we decided for the above form. The dimensions 
 $d\equiv 16 \text { mod } 24$
 had to be excluded from our result since (for some unknown reason) the ‘magic’ function we construct in these dimensions fails to satisfy some of the properties in Theorem 4; for instance, their Fourier transform is nonpositive outside a neighborhood of the origin (although having positive mass). However, we believe it is possible to fix these issues if we impose more forbidden distances (see the more general Conjecture 3).
$d\equiv 16 \text { mod } 24$
 had to be excluded from our result since (for some unknown reason) the ‘magic’ function we construct in these dimensions fails to satisfy some of the properties in Theorem 4; for instance, their Fourier transform is nonpositive outside a neighborhood of the origin (although having positive mass). However, we believe it is possible to fix these issues if we impose more forbidden distances (see the more general Conjecture 3).
 A classical result shows that extremal lattices may only exist up to dimension 
 $d\leq 2\times 10^5$
, but extending our results to such high dimensions seems out of reach with the present computational power on Earth, although we do believe they hold in all available dimensions (Conjecture 3). Indeed,
$d\leq 2\times 10^5$
, but extending our results to such high dimensions seems out of reach with the present computational power on Earth, although we do believe they hold in all available dimensions (Conjecture 3). Indeed, 
 $d\leq 1200$
 is an artifact of the computer-assisted part in this paper, but we believe it can be improved a little bit with cleverer/optimized algorithms.
$d\leq 1200$
 is an artifact of the computer-assisted part in this paper, but we believe it can be improved a little bit with cleverer/optimized algorithms.
 Theorem 2 puts forward a general framework and gives some kind of explanation to why one is only able to solve the sphere packing problem via linear programming in dimensions 
 $8$
 and
$8$
 and 
 $24$
. We have now constructed a family of constrained problems, all amenable to linear programming methods and exact solutions via constructions with modular forms, which characterize extremal lattices as having optimal density among sphere packings avoiding certain distances. It is worth pointing out that the
$24$
. We have now constructed a family of constrained problems, all amenable to linear programming methods and exact solutions via constructions with modular forms, which characterize extremal lattices as having optimal density among sphere packings avoiding certain distances. It is worth pointing out that the 
 $E_8$
 and Leech lattices are the only extremal latttices in dimensions
$E_8$
 and Leech lattices are the only extremal latttices in dimensions 
 $8$
 and
$8$
 and 
 $24$
, that
$24$
, that 
 $c_8=c_{24}=0$
 and
$c_8=c_{24}=0$
 and 
 $A_8=A_{24}=\emptyset $
. Hence, all the constraints we impose disappear in these dimensions, and we recover Viazovska’s results. Curiously, the same set of (unscaled) distances
$A_8=A_{24}=\emptyset $
. Hence, all the constraints we impose disappear in these dimensions, and we recover Viazovska’s results. Curiously, the same set of (unscaled) distances 
 $\{\sqrt {m},\sqrt {m+1},\ldots ,\sqrt {n}\}$
 appeared in a recent paper by Naslund on chromatic numbers of
$\{\sqrt {m},\sqrt {m+1},\ldots ,\sqrt {n}\}$
 appeared in a recent paper by Naslund on chromatic numbers of 
 $\mathbb {R}^d$
 [Reference Naslund21]. Other remarks about our results are addressed in Section 2.
$\mathbb {R}^d$
 [Reference Naslund21]. Other remarks about our results are addressed in Section 2.
2 Further main results
 We say that the set 
 $P=X+{\tfrac 12}B_d$
 is a sphere packing of
$P=X+{\tfrac 12}B_d$
 is a sphere packing of 
 $\mathbb {R}^d$
 (associated to a set
$\mathbb {R}^d$
 (associated to a set 
 $X\subset \mathbb {R}^d$
) if
$X\subset \mathbb {R}^d$
) if 
 $|x-y|\in \{0\}\cup [1,\infty )$
 for all
$|x-y|\in \{0\}\cup [1,\infty )$
 for all 
 $x,y\in X$
, where
$x,y\in X$
, where 
 $B_d:=\{y\in \mathbb {R}^d : |y|\leq 1\}$
 is the unit ball and
$B_d:=\{y\in \mathbb {R}^d : |y|\leq 1\}$
 is the unit ball and 
 $|\cdot |$
 is the Euclidean norm. For a sphere packing P, we define its density by
$|\cdot |$
 is the Euclidean norm. For a sphere packing P, we define its density by 
 $$ \begin{align*} \mathrm{dens}(P):=\displaystyle\limsup_{t\rightarrow+\infty} \displaystyle \displaystyle\frac{\mathrm{vol}(P\cap tQ_d)}{\mathrm{vol}(tQ_d)}, \end{align*} $$
$$ \begin{align*} \mathrm{dens}(P):=\displaystyle\limsup_{t\rightarrow+\infty} \displaystyle \displaystyle\frac{\mathrm{vol}(P\cap tQ_d)}{\mathrm{vol}(tQ_d)}, \end{align*} $$
where 
 $Q_d:=\left [-\frac {1}{2},\frac {1}{2}\right ]^d$
 is the unit cube. The setup is as follows.
$Q_d:=\left [-\frac {1}{2},\frac {1}{2}\right ]^d$
 is the unit cube. The setup is as follows.

For now on, we will stick with the formulation using K rather than A (prescribing rather than forbidding), as it fits better our scheme of results and constructions.
 We now introduce some known facts about lattices. A (full rank) lattice 
 $\Lambda \subset \mathbb {R}^d$
 is a discrete subgroup of
$\Lambda \subset \mathbb {R}^d$
 is a discrete subgroup of 
 $(\mathbb {R}^d,+)$
 that contains d linear independent vectors. We let
$(\mathbb {R}^d,+)$
 that contains d linear independent vectors. We let 
 $$ \begin{align*}\ell(\Lambda):=\{|\lambda| : \lambda\in \Lambda\setminus\{0\}\} \end{align*} $$
$$ \begin{align*}\ell(\Lambda):=\{|\lambda| : \lambda\in \Lambda\setminus\{0\}\} \end{align*} $$
denote the lengths of 
 $\Lambda $
 and
$\Lambda $
 and 
 $\min \ell (\Lambda )$
 denote its minimal norm. Given a lattice
$\min \ell (\Lambda )$
 denote its minimal norm. Given a lattice 
 $\Lambda $
, one can associate a sphere packing
$\Lambda $
, one can associate a sphere packing 
 $$ \begin{align*}P_\Lambda := \frac{1}{r}\Lambda + {\tfrac12}B_d \quad (\text{with } \ r=\min \ell(\Lambda)) \end{align*} $$
$$ \begin{align*}P_\Lambda := \frac{1}{r}\Lambda + {\tfrac12}B_d \quad (\text{with } \ r=\min \ell(\Lambda)) \end{align*} $$
and show that
 $$ \begin{align*}\mathrm{dens}(\Lambda):=\mathrm{dens}(P_\Lambda)=\frac{\mathrm{vol}(\tfrac{r}{2}B_d)}{\mathrm{ vol}(\mathbb{R}^d/\Lambda)}.\end{align*} $$
$$ \begin{align*}\mathrm{dens}(\Lambda):=\mathrm{dens}(P_\Lambda)=\frac{\mathrm{vol}(\tfrac{r}{2}B_d)}{\mathrm{ vol}(\mathbb{R}^d/\Lambda)}.\end{align*} $$
We say that a lattice 
 $\Lambda $
 is K-admissible if the packing
$\Lambda $
 is K-admissible if the packing 
 $P_\Lambda $
 above is K-admissible – that is, if
$P_\Lambda $
 above is K-admissible – that is, if 
 $$ \begin{align*}\frac{\ell(\Lambda)}{\min \ell(\Lambda)} \subset K \cup (\sup(K),\infty). \end{align*} $$
$$ \begin{align*}\frac{\ell(\Lambda)}{\min \ell(\Lambda)} \subset K \cup (\sup(K),\infty). \end{align*} $$
An even unimodular lattice 
 $\Lambda $
 is one such that
$\Lambda $
 is one such that 
 $\mathrm {vol}(\mathbb {R}^d/\Lambda )=1$
 and
$\mathrm {vol}(\mathbb {R}^d/\Lambda )=1$
 and 
 $\ell (\Lambda )\subset \{\sqrt {2n} : n\geq 1\}$
 (such lattices are integral and self-dual). These lattices have been widely studied and classified in the literature. It is known that they can only exist in dimensions multiple of
$\ell (\Lambda )\subset \{\sqrt {2n} : n\geq 1\}$
 (such lattices are integral and self-dual). These lattices have been widely studied and classified in the literature. It is known that they can only exist in dimensions multiple of 
 $8$
 and, due to a classical theorem of Voronoi, that there are only finitely many of them in each dimension (modulo symmetries). It is known that (see [Reference Conway and Sloane12, p. 194, Cor. 21])
$8$
 and, due to a classical theorem of Voronoi, that there are only finitely many of them in each dimension (modulo symmetries). It is known that (see [Reference Conway and Sloane12, p. 194, Cor. 21]) 
 $$ \begin{align*}(\min \ell(\Lambda))^2 \leq a_d := 2\bigg\lfloor \frac{d}{24} \bigg\rfloor +2. \end{align*} $$
$$ \begin{align*}(\min \ell(\Lambda))^2 \leq a_d := 2\bigg\lfloor \frac{d}{24} \bigg\rfloor +2. \end{align*} $$
An even unimodular lattice attaining the above bound is called extremal. The 
 $E_8$
,
$E_8$
, 
 $E_8^2, D_{16}^+$
 and Leech lattices are the only even unimodular extremal lattices up to dimension
$E_8^2, D_{16}^+$
 and Leech lattices are the only even unimodular extremal lattices up to dimension 
 $24$
. In dimensions
$24$
. In dimensions 
 $32$
 and
$32$
 and 
 $40$
, there are more than
$40$
, there are more than 
 $10^7$
 and
$10^7$
 and 
 $10^{51}$
 of such lattices, respectively; however, in dimension
$10^{51}$
 of such lattices, respectively; however, in dimension 
 $48$
, there are (so far) only
$48$
, there are (so far) only 
 $4$
 known lattices:
$4$
 known lattices: 
 $P_{48p},P_{48q},P_{48m}$
 and
$P_{48p},P_{48q},P_{48m}$
 and 
 $P_{48n}$
 (see Nebe [Reference Nebe22]). Moreover, it is known that extremal lattices cannot exist in sufficiently large dimensions [Reference Mallows, Odlyzko and Sloane20] (as modular forms with several vanishing Fourier coefficients and very large weight necessarily have negative coefficients). The current best bound is due to Jenkins and Rouse [Reference Jenkins and Rouse19], and it states that
$P_{48n}$
 (see Nebe [Reference Nebe22]). Moreover, it is known that extremal lattices cannot exist in sufficiently large dimensions [Reference Mallows, Odlyzko and Sloane20] (as modular forms with several vanishing Fourier coefficients and very large weight necessarily have negative coefficients). The current best bound is due to Jenkins and Rouse [Reference Jenkins and Rouse19], and it states that 
 $$ \begin{align*}d_{\max} := {\sup}\{\text{rank}(\Lambda) : \Lambda \text{ is an even unimodular extremal lattice} \}\leq 163264. \end{align*} $$
$$ \begin{align*}d_{\max} := {\sup}\{\text{rank}(\Lambda) : \Lambda \text{ is an even unimodular extremal lattice} \}\leq 163264. \end{align*} $$
Indeed, one can show that for any 
 $\beta>0$
, there exists D such that there is no even unimodular lattice of rank
$\beta>0$
, there exists D such that there is no even unimodular lattice of rank 
 $d> D$
 and minimal squared norm larger than
$d> D$
 and minimal squared norm larger than 
 $a_{d}-\beta $
. For more information on extremal lattices, see [Reference Scharlau and Schulze-Pillot26].
$a_{d}-\beta $
. For more information on extremal lattices, see [Reference Scharlau and Schulze-Pillot26].
 We now state three other main results of this paper. The first is an analogue of the Cohn and Elkies linear programming bound for 
 $\Delta _d(K)$
.
$\Delta _d(K)$
.
Theorem 3. Let 
 $K\subset [1,+\infty )$
 be bounded and such that
$K\subset [1,+\infty )$
 be bounded and such that 
 $1\in K$
. Define
$1\in K$
. Define 
 $$ \begin{align*}\Delta_d^{\mathrm{LP}}(K):=\mathrm{vol} \left( {\tfrac12}B_d\right)\inf\displaystyle\frac{F(0)}{\widehat{F}(0)},\end{align*} $$
$$ \begin{align*}\Delta_d^{\mathrm{LP}}(K):=\mathrm{vol} \left( {\tfrac12}B_d\right)\inf\displaystyle\frac{F(0)}{\widehat{F}(0)},\end{align*} $$
where the infimum is taken over all nonzero functions 
 $F\in L^1(\mathbb {R}^d) \cap C(\mathbb {R}^d)$
 such that
$F\in L^1(\mathbb {R}^d) \cap C(\mathbb {R}^d)$
 such that 
 $$ \begin{align*} F(x) \leq 0 \ \text{ for }\ |x|\in K\cup(\sup(K),\infty) \quad \text{and} \quad \widehat{F}(x) \geq 0 \text{ for all } x. \end{align*} $$
$$ \begin{align*} F(x) \leq 0 \ \text{ for }\ |x|\in K\cup(\sup(K),\infty) \quad \text{and} \quad \widehat{F}(x) \geq 0 \text{ for all } x. \end{align*} $$
Then
 $$ \begin{align*} \Delta_d(K)\leq\Delta_d^{\mathrm{LP}}(K). \end{align*} $$
$$ \begin{align*} \Delta_d(K)\leq\Delta_d^{\mathrm{LP}}(K). \end{align*} $$
Theorem 4. Let 
 $8\leq d\leq 1200$
, where d is divisible by
$8\leq d\leq 1200$
, where d is divisible by 
 $8$
 but
$8$
 but  . Define
. Define 
 $l_d$
 as in (1) and
$l_d$
 as in (1) and 
 $$ \begin{align*}K_d = \frac{1}{\sqrt{a_d}}\{\sqrt{a_d},\sqrt{a_d+2},\sqrt{a_d+4},\ldots ,\sqrt{l_d}\}. \end{align*} $$
$$ \begin{align*}K_d = \frac{1}{\sqrt{a_d}}\{\sqrt{a_d},\sqrt{a_d+2},\sqrt{a_d+4},\ldots ,\sqrt{l_d}\}. \end{align*} $$
Also let 
 $c_d$
 be given by Table 1 (
$c_d$
 be given by Table 1 (
 $c_d=0$
 if
$c_d=0$
 if 
 $d=8,24, 48$
). Then there exists a nonzero radial function
$d=8,24, 48$
). Then there exists a nonzero radial function 
 $H:\mathbb {R}^d\to \mathbb {R}$
 of Schwartz class such that
$H:\mathbb {R}^d\to \mathbb {R}$
 of Schwartz class such that 
- 
•  $H(x)\leq 0$
 if $H(x)\leq 0$
 if $|x|^2>l_d$
; $|x|^2>l_d$
;
- 
•  $\widehat H(x)\geq 0$
 if $\widehat H(x)\geq 0$
 if $|x|> c_d$
; $|x|> c_d$
;
- 
•  $H(x)=\widehat H(x)=0$
 if $H(x)=\widehat H(x)=0$
 if $|x|^2 \in \{a_d,a_d+2,\ldots \}$
; $|x|^2 \in \{a_d,a_d+2,\ldots \}$
;
- 
•  $\{|x|^2 : H(x)=0 \text { and } |x|^2> l_d^-\}=\{l_d,l_d+2,\ldots \}$
; $\{|x|^2 : H(x)=0 \text { and } |x|^2> l_d^-\}=\{l_d,l_d+2,\ldots \}$
;
- 
•  $\{|x|^2 : \widehat H(x)=0 \text { and } |x|^2>c_d\}=\{a_d,a_d+2,\ldots \}.$ $\{|x|^2 : \widehat H(x)=0 \text { and } |x|^2>c_d\}=\{a_d,a_d+2,\ldots \}.$
Moreover, if 
 $d=48$
 we additionally have that
$d=48$
 we additionally have that 
 $\{|x|^2 : H(x) < 0\} \cap (0,10) =(6,8)$
.
$\{|x|^2 : H(x) < 0\} \cap (0,10) =(6,8)$
.
Table 1 Values of 
 $c_d$
 for
$c_d$
 for 
 $d=8,16,24,\ldots ,1200$
. One should read it left to right top to bottom. From dimension
$d=8,16,24,\ldots ,1200$
. One should read it left to right top to bottom. From dimension 
 $d=536$
 onwards, computational time was too high, and we simply took
$d=536$
 onwards, computational time was too high, and we simply took 
 $c_d=a_d-2$
, which can be verified much faster. For
$c_d=a_d-2$
, which can be verified much faster. For 
 $d<536$
, the numbers
$d<536$
, the numbers 
 ${c_d}$
 give a good rational approximation of the last sign change of the function
${c_d}$
 give a good rational approximation of the last sign change of the function 
 $s\mapsto \widehat H(\sqrt {s})$
 from Theorem 4. These numbers can also be found in the ancillary file cnumbers on the arXiv submission of this paper (arXiv.org:2308.03925).
$s\mapsto \widehat H(\sqrt {s})$
 from Theorem 4. These numbers can also be found in the ancillary file cnumbers on the arXiv submission of this paper (arXiv.org:2308.03925).

 In the theorem above, 
 $|x|^2>l_d^-$
 means that
$|x|^2>l_d^-$
 means that 
 $|x|^2>l_d-\epsilon _d$
 for some small
$|x|^2>l_d-\epsilon _d$
 for some small 
 $\epsilon _d>0$
. We note that one can indeed build functions H for all dimensions congruent to
$\epsilon _d>0$
. We note that one can indeed build functions H for all dimensions congruent to 
 $16$
 modulo
$16$
 modulo 
 $24$
 using the same techniques of Theorem 4. However, it turns out that
$24$
 using the same techniques of Theorem 4. However, it turns out that 
 $\widehat H(x)\leq 0$
 for
$\widehat H(x)\leq 0$
 for 
 $|x|>o(a_d)$
 (numerically), although
$|x|>o(a_d)$
 (numerically), although 
 $H(x)\leq 0$
 for
$H(x)\leq 0$
 for 
 $|x|^2>l_d$
 and
$|x|^2>l_d$
 and 
 $H(0)=\widehat H(0)>0$
. One should also notice that the numbers
$H(0)=\widehat H(0)>0$
. One should also notice that the numbers 
 $c_d$
 seem to satisfy (for small d)
$c_d$
 seem to satisfy (for small d) 
 $$ \begin{align*}c_d=a_d-2-O(1) \ \text{ if } d\equiv 8 \text{ mod } 24 \quad \text{and} \quad c_d= a_d-6-O(1) \ \text{ if }d\equiv 0 \text{ mod } 24. \end{align*} $$
$$ \begin{align*}c_d=a_d-2-O(1) \ \text{ if } d\equiv 8 \text{ mod } 24 \quad \text{and} \quad c_d= a_d-6-O(1) \ \text{ if }d\equiv 0 \text{ mod } 24. \end{align*} $$
Also, in fact, 
 $c_d$
 is an approximation from the right of the last simple root of
$c_d$
 is an approximation from the right of the last simple root of 
 $\widehat H(x)$
. All these facts give a heuristic explanation why we only get results free from spectral conditions in dimensions
$\widehat H(x)$
. All these facts give a heuristic explanation why we only get results free from spectral conditions in dimensions 
 $8,24$
 and
$8,24$
 and 
 $48$
 (hence a result for all sphere packings, periodic or not). It goes as follows: Experimentally, the
$48$
 (hence a result for all sphere packings, periodic or not). It goes as follows: Experimentally, the 
 $O(1)$
 in
$O(1)$
 in 
 $c_d$
 is less than
$c_d$
 is less than 
 $1$
 for small d and
$1$
 for small d and 
 $c_d$
 increases with d on each equivalence class modulo
$c_d$
 increases with d on each equivalence class modulo 
 $24$
, which means that if
$24$
, which means that if 
 $d\geq 72$
, then
$d\geq 72$
, then 
 $a_d\geq 8$
, and so
$a_d\geq 8$
, and so 
 $c_d\geq 1$
. Thus,
$c_d\geq 1$
. Thus, 
 $\widehat H$
 would never be nonnegative. For
$\widehat H$
 would never be nonnegative. For 
 $d=8,24,48$
, we have
$d=8,24,48$
, we have 
 $c_d=0-O(1)<0$
. Thus,
$c_d=0-O(1)<0$
. Thus, 
 $\widehat H\geq 0$
 (see Figure 1). For the remaining small dimensions not equal to
$\widehat H\geq 0$
 (see Figure 1). For the remaining small dimensions not equal to 
 $16$
 modulo
$16$
 modulo 
 $24$
, which are,
$24$
, which are, 
 $d=32$
 and
$d=32$
 and 
 $d=56$
, we have
$d=56$
, we have 
 $c_{32}=2-O(1)$
 and
$c_{32}=2-O(1)$
 and 
 $c_{56}=4-O(1)$
, which are positive, and so
$c_{56}=4-O(1)$
, which are positive, and so 
 $\widehat H$
 is not nonnegative.
$\widehat H$
 is not nonnegative.
Theorem 5. Let d, 
 $a_d$
,
$a_d$
, 
 $K_d$
 and
$K_d$
 and 
 $c_d$
 be as in Theorem 4. Let
$c_d$
 be as in Theorem 4. Let 
 $P=\Lambda +Y+{\tfrac 12}B_d$
 be some
$P=\Lambda +Y+{\tfrac 12}B_d$
 be some 
 $K_{d}$
-admissible periodic sphere packing such that
$K_{d}$
-admissible periodic sphere packing such that 
 $\min \ell (\Lambda ^*)> \sqrt {c_d}$
. Then
$\min \ell (\Lambda ^*)> \sqrt {c_d}$
. Then 
 $$ \begin{align*}\mathrm{dens}(P)\leq \mathrm{vol} \left( B_d\right) \left( \frac{\sqrt{a_d}}{2}\right)^d.\end{align*} $$
$$ \begin{align*}\mathrm{dens}(P)\leq \mathrm{vol} \left( B_d\right) \left( \frac{\sqrt{a_d}}{2}\right)^d.\end{align*} $$
In case 
 $\#Y=1$
, equality above occurs if and only if
$\#Y=1$
, equality above occurs if and only if 
 $\sqrt {a_d}\Lambda $
 is an even unimodular extremal lattice. We conclude that if
$\sqrt {a_d}\Lambda $
 is an even unimodular extremal lattice. We conclude that if 
 $d\in \{8,24,48\}$
, then
$d\in \{8,24,48\}$
, then 
 $$ \begin{align*}\Delta_d(K_d) = \Delta_d^{\mathrm{LP}}(K_d) = \mathrm{vol} \left( B_d\right) \left( \frac{\sqrt{a_d}}{2}\right)^d. \end{align*} $$
$$ \begin{align*}\Delta_d(K_d) = \Delta_d^{\mathrm{LP}}(K_d) = \mathrm{vol} \left( B_d\right) \left( \frac{\sqrt{a_d}}{2}\right)^d. \end{align*} $$

Figure 1 This is a plot of the functions 
 $s\mapsto \widehat H(\sqrt {s})e^{\pi s}$
 for
$s\mapsto \widehat H(\sqrt {s})e^{\pi s}$
 for 
 $d=8$
 (black),
$d=8$
 (black), 
 $d=24$
 (blue) and
$d=24$
 (blue) and 
 $d=48$
 (red), normalized so
$d=48$
 (red), normalized so 
 $\widehat H(0)=1$
.
$\widehat H(0)=1$
.

Figure 2 This is a plot of the functions 
 $s\mapsto \widehat H(\sqrt {s})e^{\pi s}$
 for
$s\mapsto \widehat H(\sqrt {s})e^{\pi s}$
 for 
 $d=72$
 (red) and
$d=72$
 (red) and 
 $d=80$
 (blue), normalized so
$d=80$
 (blue), normalized so 
 $\widehat H(0)=1$
. For
$\widehat H(0)=1$
. For 
 $d=80$
, we have multiplied the function by
$d=80$
, we have multiplied the function by 
 $(s+1)^2$
 for aesthetic reasons.
$(s+1)^2$
 for aesthetic reasons.
 Note that if 
 $d\in \{8,24,48\}$
, then
$d\in \{8,24,48\}$
, then 
 $c_d=0$
, and this shows that even unimodular extremal lattices maximize density for the among all
$c_d=0$
, and this shows that even unimodular extremal lattices maximize density for the among all 
 $K_d$
-admissible sphere packings (periodic or not). Since
$K_d$
-admissible sphere packings (periodic or not). Since 
 $K_8=K_{24}=\{1\}$
, the packing problem in these dimensions is unconstrained, and the
$K_8=K_{24}=\{1\}$
, the packing problem in these dimensions is unconstrained, and the 
 $E_8$
 and Leech lattices are the only extremal lattices in these dimensions, this shows they have maximal density. The above theorem puts the results of [Reference Cohn, Kumar, Miller, Radchenko and Viazovska10, Reference Viazovska27] in a larger family of packing problems that can be solved by linear programming methods and construction via modular forms. The fact that for
$E_8$
 and Leech lattices are the only extremal lattices in these dimensions, this shows they have maximal density. The above theorem puts the results of [Reference Cohn, Kumar, Miller, Radchenko and Viazovska10, Reference Viazovska27] in a larger family of packing problems that can be solved by linear programming methods and construction via modular forms. The fact that for 
 $d=48$
 we have
$d=48$
 we have 
 $H(x) < 0$
 for
$H(x) < 0$
 for 
 $6<|x|^2 < 8$
, allows us to enlarge
$6<|x|^2 < 8$
, allows us to enlarge 
 $K_{48}$
 to
$K_{48}$
 to 
 $\frac 1{\sqrt {6}}([\sqrt {6},\sqrt {8}]\cup {\sqrt {10}})$
 and deduce Theorem 1. The same enlargement is possible in every dimension d; that is, we could fill
$\frac 1{\sqrt {6}}([\sqrt {6},\sqrt {8}]\cup {\sqrt {10}})$
 and deduce Theorem 1. The same enlargement is possible in every dimension d; that is, we could fill 
 $K_d$
 between a couple of its points and prove a slightly stronger result. However, for simplicity, we left the statement as it is.
$K_d$
 between a couple of its points and prove a slightly stronger result. However, for simplicity, we left the statement as it is.
 One could ask if it is possible to extend Theorems 4 and 5 to all dimensions 
 $d\leq 163264$
. For this, one would need to greatly optimize the numerical procedure we explain in the proof of Theorem 4, and use specialized software and several days of running time to increase
$d\leq 163264$
. For this, one would need to greatly optimize the numerical procedure we explain in the proof of Theorem 4, and use specialized software and several days of running time to increase 
 $1200$
 to something of the order of
$1200$
 to something of the order of 
 $10000$
. Rough experimental estimations show that the running time we have for the proof of Theorem 4 is roughly
$10000$
. Rough experimental estimations show that the running time we have for the proof of Theorem 4 is roughly 
 $O(1.1^{d/8})$
-secs, so it seems the complexity of our algorithm is increasing exponentially. Even if one manages to reduce this ratio to (being generous)
$O(1.1^{d/8})$
-secs, so it seems the complexity of our algorithm is increasing exponentially. Even if one manages to reduce this ratio to (being generous) 
 $1.001$
, reaching
$1.001$
, reaching 
 $d\approx 170000$
 seems unreasonable.
$d\approx 170000$
 seems unreasonable.
 One could also ask if we could prove Theorem 5 with no assumption on the minimal norm on 
 $\Lambda ^*$
. That might be possible, but we believe it to be impossible via the linear programming approach that we use with the same set
$\Lambda ^*$
. That might be possible, but we believe it to be impossible via the linear programming approach that we use with the same set 
 $K_d$
. The functions H computed in Theorem 4 are in a way unique, and one could actually show they are by extending the interpolation formulas of [Reference Cohn, Kumar, Miller, Radchenko and Viazovska11] to all dimensions multiple of
$K_d$
. The functions H computed in Theorem 4 are in a way unique, and one could actually show they are by extending the interpolation formulas of [Reference Cohn, Kumar, Miller, Radchenko and Viazovska11] to all dimensions multiple of 
 $8$
. The issue is that the functions
$8$
. The issue is that the functions 
 $\widehat H(x)$
 of Theorem 4 do have a simple zero very near
$\widehat H(x)$
 of Theorem 4 do have a simple zero very near 
 $|x|^2=c_d$
 and so have negative values in the region
$|x|^2=c_d$
 and so have negative values in the region 
 $0<|x|^2<c_d$
. However, it might be possible to remove the condition on
$0<|x|^2<c_d$
. However, it might be possible to remove the condition on 
 $\Lambda ^*$
 by enlarging
$\Lambda ^*$
 by enlarging 
 $l_d$
 and finding the corresponding ‘magic’ functions. We have tried this approach in small dimensions, replacing
$l_d$
 and finding the corresponding ‘magic’ functions. We have tried this approach in small dimensions, replacing 
 $l_d$
 by
$l_d$
 by 
 $l_d+\delta $
, for some small even
$l_d+\delta $
, for some small even 
 $\delta>0$
, although unsuccessfully. It might be the case that
$\delta>0$
, although unsuccessfully. It might be the case that 
 $\delta $
 needs to be very large; however, that greatly complicates the modular form constructions. We leave this question for future work. Nevertheless, we expect this
$\delta $
 needs to be very large; however, that greatly complicates the modular form constructions. We leave this question for future work. Nevertheless, we expect this 
 $\delta $
 to exist because when
$\delta $
 to exist because when 
 $\delta =\infty $
, the only
$\delta =\infty $
, the only 
 $K_d$
-admissible lattices with minimal norm
$K_d$
-admissible lattices with minimal norm 
 $\sqrt {a_d}$
 are integral even lattices, and such lattices are less dense than extremal ones.
$\sqrt {a_d}$
 are integral even lattices, and such lattices are less dense than extremal ones.
Conjecture 3. Let 
 $\Lambda \subset \mathbb {R}^d$
 be an even unimodular lattice with minimal norm
$\Lambda \subset \mathbb {R}^d$
 be an even unimodular lattice with minimal norm 
 $\sqrt {a}$
, for some even integer a. Then for some even
$\sqrt {a}$
, for some even integer a. Then for some even 
 $l>a$
, we have that
$l>a$
, we have that 
 $\Lambda $
 has maximal density among any
$\Lambda $
 has maximal density among any 
 $\frac 1{\sqrt {a}}\{\sqrt {a},\sqrt {a+2},\ldots ,\sqrt {l}\}$
-admissible sphere packing; that is,
$\frac 1{\sqrt {a}}\{\sqrt {a},\sqrt {a+2},\ldots ,\sqrt {l}\}$
-admissible sphere packing; that is, 
 $$ \begin{align*}\Delta_d\left(\frac1{\sqrt{a}}\{\sqrt{a},\sqrt{a+2},\ldots ,\sqrt{l}\}\right) = \mathrm{dens}(\Lambda). \end{align*} $$
$$ \begin{align*}\Delta_d\left(\frac1{\sqrt{a}}\{\sqrt{a},\sqrt{a+2},\ldots ,\sqrt{l}\}\right) = \mathrm{dens}(\Lambda). \end{align*} $$
 If this conjecture is true in dimension d, then for 
 $2\leq a \leq a_d$
, one could define
$2\leq a \leq a_d$
, one could define 
 $L(a,d)=l$
, where l is the smallest such that Conjecture 3 is true. We already know that
$L(a,d)=l$
, where l is the smallest such that Conjecture 3 is true. We already know that 
 $L(2,8)=2, L(4,24)=4$
, and we have shown that
$L(2,8)=2, L(4,24)=4$
, and we have shown that 
 $L(6,48)\leq 10$
. We believe (and it is somewhat believed in the community) that
$L(6,48)\leq 10$
. We believe (and it is somewhat believed in the community) that 
 $L(6,48)=6$
 and that extremal lattices maximize density with no constraints in dimension
$L(6,48)=6$
 and that extremal lattices maximize density with no constraints in dimension 
 $48$
. It would be also interesting to find
$48$
. It would be also interesting to find 
 $L(2,16)$
 and
$L(2,16)$
 and 
 $L(2,24)$
 and show that the lattices
$L(2,24)$
 and show that the lattices 
 $E_8^2, D_{16}^+$
 and all the
$E_8^2, D_{16}^+$
 and all the 
 $24$
-dimensional Niemeier lattices with root are optimal.
$24$
-dimensional Niemeier lattices with root are optimal.
 Another curious question is: Is there a finite K such that 
 $\mathbb {Z}^2$
 is K-admissible and with maximal density?Footnote 
3
 If so, how small
$\mathbb {Z}^2$
 is K-admissible and with maximal density?Footnote 
3
 If so, how small 
 $\#K$
 can be?
$\#K$
 can be?
2.1 One-dimensional sphere packings
 Unconstrained one-dimensional sphere packings are trivial to construct as unit intervals tile the line. However, finding optimal one-dimensional K-admissible sphere packings for an arbitrary given set K seems to be a difficult question. Here, we are concerned with periodicity: When can we make sure that there exists some optimal one-dimensional packing which is periodic? Unfortunately, greedy choice usually does not give an optimal construction. By greedy choice, we mean one starts with some configuration 
 $\cup _{i=1}^N (a_i+I)$
 for
$\cup _{i=1}^N (a_i+I)$
 for 
 $a_1<a_2<\ldots <a_{N}$
 (with
$a_1<a_2<\ldots <a_{N}$
 (with 
 $I=[0,1]$
) and then takes an interval
$I=[0,1]$
) and then takes an interval 
 $a_{N+1}+I$
 with
$a_{N+1}+I$
 with 
 $a_{N+1}\geq 1+a_N$
 as small as possible so that
$a_{N+1}\geq 1+a_N$
 as small as possible so that 
 $\cup _{i=1}^{N+1} (a_i+I)$
 still is K-admissible. For example, first consider the case where
$\cup _{i=1}^{N+1} (a_i+I)$
 still is K-admissible. For example, first consider the case where 
 $K=\{1,\alpha \}$
 for some
$K=\{1,\alpha \}$
 for some 
 $\alpha>2$
. Then greedy choice gives the packing P where one puts two unit intervals glued together, and then a gap of length
$\alpha>2$
. Then greedy choice gives the packing P where one puts two unit intervals glued together, and then a gap of length 
 $\alpha -1$
, and then repeats this configuration periodically. One can see this is optimal by noting that, in any given K-admissible packing, the distance between the centers of any unit interval and the second one after it must be at least
$\alpha -1$
, and then repeats this configuration periodically. One can see this is optimal by noting that, in any given K-admissible packing, the distance between the centers of any unit interval and the second one after it must be at least 
 $1+\alpha $
. This means that an interval of size
$1+\alpha $
. This means that an interval of size 
 $N(1+\alpha )$
 contains at most
$N(1+\alpha )$
 contains at most 
 $2N$
 unit intervals, which shows that
$2N$
 unit intervals, which shows that 
 $\Delta _1(\{1,\alpha \}) \leq 2/(1+\alpha )$
, and this is attained by P. However, this strategy does not produce the best packing in general. For instance, if
$\Delta _1(\{1,\alpha \}) \leq 2/(1+\alpha )$
, and this is attained by P. However, this strategy does not produce the best packing in general. For instance, if 
 $K=\{1,\alpha ,\beta \}$
 with
$K=\{1,\alpha ,\beta \}$
 with 
 $2\alpha \geq \beta>2\alpha -1>\alpha $
, then greedy choice gives the packing
$2\alpha \geq \beta>2\alpha -1>\alpha $
, then greedy choice gives the packing 
 $P_\beta =I +(1+\beta )\mathbb {Z}+\{0,1\}$
, which has density
$P_\beta =I +(1+\beta )\mathbb {Z}+\{0,1\}$
, which has density 
 $2/(1+\beta )$
. This is not optimal since
$2/(1+\beta )$
. This is not optimal since 
 $P_\alpha =I + \alpha \mathbb {Z} $
 has density
$P_\alpha =I + \alpha \mathbb {Z} $
 has density 
 $1/\alpha>2/(1+\beta )$
. In Lemma 15, we completely solve this problem for all choices of
$1/\alpha>2/(1+\beta )$
. In Lemma 15, we completely solve this problem for all choices of 
 $\alpha $
 and
$\alpha $
 and 
 $\beta $
.
$\beta $
.
 In Proposition 7, we show that when K is a compact set, then optimal packings for 
 $\Delta _d(K)$
 always exist. However, it is not guaranteed that they are periodic, as this is not even known in the unconstrained case. Nevertheless, we expect them to be periodic in the one-dimensional case. The following result proves this in the ‘almost’ finite case.
$\Delta _d(K)$
 always exist. However, it is not guaranteed that they are periodic, as this is not even known in the unconstrained case. Nevertheless, we expect them to be periodic in the one-dimensional case. The following result proves this in the ‘almost’ finite case.
Theorem 6. Let 
 $K\subset [1,\infty )$
 be a compact set such that
$K\subset [1,\infty )$
 be a compact set such that 
 $1\in K$
. Assume that K has no accumulation points from the left and only finitely many accumulation points from the right. Moreover, let
$1\in K$
. Assume that K has no accumulation points from the left and only finitely many accumulation points from the right. Moreover, let 
 $K'$
 be its set of accumulation points and assume that
$K'$
 be its set of accumulation points and assume that 
 $(K'+K') \cap K'=\emptyset $
. Then there exists a K-admissible periodic sphere packing P of
$(K'+K') \cap K'=\emptyset $
. Then there exists a K-admissible periodic sphere packing P of 
 $\mathbb {R}$
 such that
$\mathbb {R}$
 such that 
 $\mathrm {dens}(P)=\Delta _1(K)$
.
$\mathrm {dens}(P)=\Delta _1(K)$
.
In particular, optimal periodic K-admissible packings exist whenever K is finite. However, optimal periodic packings will also exist in the (illustrative) case
 $$ \begin{align*}K=\{1,\sqrt{2}, e,\pi\} + \{10^{-n}\}_{n\geq 1}. \end{align*} $$
$$ \begin{align*}K=\{1,\sqrt{2}, e,\pi\} + \{10^{-n}\}_{n\geq 1}. \end{align*} $$
Conjecture 4. Let 
 $K\subset [1,\infty )$
 be a compact set such that
$K\subset [1,\infty )$
 be a compact set such that 
 $1\in K$
. Then there exists a K-admissible periodic sphere packing of
$1\in K$
. Then there exists a K-admissible periodic sphere packing of 
 $\mathbb {R}$
 with maximal density.
$\mathbb {R}$
 with maximal density.
A compact set K can be classified by its sequence of derived sets; that is,
 $$ \begin{align*}K,K', K", K"',\ldots ,\end{align*} $$
$$ \begin{align*}K,K', K", K"',\ldots ,\end{align*} $$
where 
 $S'$
 is the set of points
$S'$
 is the set of points 
 $p\in S$
 such that
$p\in S$
 such that 
 $(p-\varepsilon ,p+\varepsilon )\cap S \setminus \{ p\} \neq \emptyset $
 for any
$(p-\varepsilon ,p+\varepsilon )\cap S \setminus \{ p\} \neq \emptyset $
 for any 
 $\varepsilon>0$
 (the accumulation points of S). Theorem 6 solves the above conjecture for the case
$\varepsilon>0$
 (the accumulation points of S). Theorem 6 solves the above conjecture for the case 
 $K'=\emptyset $
 (i.e., K is finite) and deals with the case
$K'=\emptyset $
 (i.e., K is finite) and deals with the case 
 $K"=\emptyset $
 (i.e.,
$K"=\emptyset $
 (i.e., 
 $K'$
 is finite) under the condition that points only accumulate from the right and no accumulation point is a sum of two others.
$K'$
 is finite) under the condition that points only accumulate from the right and no accumulation point is a sum of two others.
 We believe that Conjecture 4 could be very hard to prove, perhaps even false, as this is equivalent to (when 
 $\sup (K)\in K$
) a generalization of Theorem 13 (which is about linear domino tilings) for an infinite compact sets of symbols
$\sup (K)\in K$
) a generalization of Theorem 13 (which is about linear domino tilings) for an infinite compact sets of symbols 
 $\Sigma $
 and domino pieces
$\Sigma $
 and domino pieces 
 $\mathcal {D}\subset \Sigma ^*\times \Sigma ^*$
.
$\mathcal {D}\subset \Sigma ^*\times \Sigma ^*$
.
3 Generalities
 In this section, we establish some basic facts about sphere packing with forbidden distances. Throughout this section, 
 $K\subset [1,\infty )$
 will always be a bounded set such that
$K\subset [1,\infty )$
 will always be a bounded set such that 
 $1\in K$
, and the word sphere will be used to denote any
$1\in K$
, and the word sphere will be used to denote any 
 $x+{\tfrac 12}B_d$
 for some
$x+{\tfrac 12}B_d$
 for some 
 $x\in \mathbb {R}^d$
.
$x\in \mathbb {R}^d$
.
Proposition 7. Assume K is compact. Then there exists a packing  such that
 such that 
 $\mathrm {dens}(P)=\Delta _d(K)$
.
$\mathrm {dens}(P)=\Delta _d(K)$
.
Proof. The proof is exactly the same as for unconstrained sphere packings [Reference Groemer17]. Let 
 $(P_n)_{n\geq 1}$
 be a maximizing sequence of sphere packings such that
$(P_n)_{n\geq 1}$
 be a maximizing sequence of sphere packings such that 
 $\mathrm {dens}(P_n)$
 is increasing and converges to
$\mathrm {dens}(P_n)$
 is increasing and converges to 
 $\Delta _d(K)$
. By Proposition 8, we can assume that each
$\Delta _d(K)$
. By Proposition 8, we can assume that each 
 $P_n$
 is
$P_n$
 is 
 ${k_n} \mathbb {Z}^d$
 periodic for some integer
${k_n} \mathbb {Z}^d$
 periodic for some integer 
 $k_n>0$
 such that
$k_n>0$
 such that 
 $k_n\nearrow \infty $
 and that
$k_n\nearrow \infty $
 and that 
 $P_n$
 maximizes the number of spheres one can put inside
$P_n$
 maximizes the number of spheres one can put inside 
 $k_nQ_d$
. Using Hausdorff’s topology for compact sets and a standard Cantor’s diagonal argument, we can assume that
$k_nQ_d$
. Using Hausdorff’s topology for compact sets and a standard Cantor’s diagonal argument, we can assume that 
 $(P_n)_{n\geq 1}$
 converges locally to some packing P, which is K-admissible since K is compact. By maximality, the number of spheres of
$(P_n)_{n\geq 1}$
 converges locally to some packing P, which is K-admissible since K is compact. By maximality, the number of spheres of 
 $P_n$
 inside
$P_n$
 inside 
 $k_mQ_d$
 must not be much smaller than that of
$k_mQ_d$
 must not be much smaller than that of 
 $P_m$
 (the error must be bounded by the surface area of the boundary of
$P_m$
 (the error must be bounded by the surface area of the boundary of 
 $k_mQ_d$
). We obtain
$k_mQ_d$
). We obtain 
 $$ \begin{align*}\mathrm{vol}(P_n \cap k_m Q_d)/\mathrm{vol}(k_m Q_d)> \mathrm{vol}(P_m \cap k_m Q_d)/\mathrm{vol}(k_m Q_d) + O(1/k_m) = \mathrm{dens}(P_m) + O(1/k_m) \end{align*} $$
$$ \begin{align*}\mathrm{vol}(P_n \cap k_m Q_d)/\mathrm{vol}(k_m Q_d)> \mathrm{vol}(P_m \cap k_m Q_d)/\mathrm{vol}(k_m Q_d) + O(1/k_m) = \mathrm{dens}(P_m) + O(1/k_m) \end{align*} $$
for all 
 $n>m$
, where
$n>m$
, where 
 $O(1/k_m)$
 comes from the spheres that touch the boundary of
$O(1/k_m)$
 comes from the spheres that touch the boundary of 
 $k_mQ_d$
. Taking
$k_mQ_d$
. Taking 
 $n\to \infty $
, we obtain
$n\to \infty $
, we obtain 
 $\mathrm {vol}(P \cap k_m Q_d)/\mathrm {vol}(k_m Q_d) \geq \mathrm {dens}(P_m) + O(1/k_m)$
. Taking
$\mathrm {vol}(P \cap k_m Q_d)/\mathrm {vol}(k_m Q_d) \geq \mathrm {dens}(P_m) + O(1/k_m)$
. Taking 
 $m\to \infty $
, we conclude that
$m\to \infty $
, we conclude that 
 $\mathrm {dens}(P)\geq \Delta _d(K)$
, which finishes the proof.
$\mathrm {dens}(P)\geq \Delta _d(K)$
, which finishes the proof.
Proposition 8. Any K-admissible sphere packing can be approximated by a periodic one. In particular, if 
 $N_t$
 denotes the maximum number of spheres one can put inside
$N_t$
 denotes the maximum number of spheres one can put inside 
 $tQ_d$
 such that the configuration is
$tQ_d$
 such that the configuration is 
 $K $
-admissible, then
$K $
-admissible, then 
 $$ \begin{align*}\lim_{t\to\infty} \frac{N_t \mathrm{vol}({\tfrac12}B_d)}{\mathrm{vol}(tQ_d)} = \Delta_d(K). \end{align*} $$
$$ \begin{align*}\lim_{t\to\infty} \frac{N_t \mathrm{vol}({\tfrac12}B_d)}{\mathrm{vol}(tQ_d)} = \Delta_d(K). \end{align*} $$
Proof. Let 
 $P=X+{\tfrac 12}B_d$
 be a K-admissible sphere packing. Then
$P=X+{\tfrac 12}B_d$
 be a K-admissible sphere packing. Then 
 $\widetilde P_t = X\cap tQ_d + (t+\sup (K))\mathbb {Z}^d + {\tfrac 12}B_d$
 is K-admissible, periodic and
$\widetilde P_t = X\cap tQ_d + (t+\sup (K))\mathbb {Z}^d + {\tfrac 12}B_d$
 is K-admissible, periodic and 
 $$ \begin{align*}\mathrm{dens}(\widetilde P_t)=\frac{\mathrm{vol}(P\cap tQ_d)}{\mathrm{vol}(tQ_d)}(1+O(1/t)). \end{align*} $$
$$ \begin{align*}\mathrm{dens}(\widetilde P_t)=\frac{\mathrm{vol}(P\cap tQ_d)}{\mathrm{vol}(tQ_d)}(1+O(1/t)). \end{align*} $$
We obtain 
 $\limsup _{t\to \infty } \mathrm {dens}(\widetilde P_t) = \mathrm {dens}(P)$
. Let
$\limsup _{t\to \infty } \mathrm {dens}(\widetilde P_t) = \mathrm {dens}(P)$
. Let 
 $\delta _t=\frac {N_t \mathrm {vol}({\tfrac 12}B_d)}{\mathrm {vol}(tQ_d)}$
. The same periodization argument shows that
$\delta _t=\frac {N_t \mathrm {vol}({\tfrac 12}B_d)}{\mathrm {vol}(tQ_d)}$
. The same periodization argument shows that 
 $\limsup _{t\to \infty } \delta _t \leq \Delta _d(K)$
. However, if
$\limsup _{t\to \infty } \delta _t \leq \Delta _d(K)$
. However, if 
 $P=X+t\mathbb {Z}^d$
 is a K-admissible periodic sphere packing, by maximality, we must have that
$P=X+t\mathbb {Z}^d$
 is a K-admissible periodic sphere packing, by maximality, we must have that 
 $\#(X \cap tQ_d) \leq N_t$
; hence,
$\#(X \cap tQ_d) \leq N_t$
; hence, 
 $$ \begin{align*}\delta_t \geq \mathrm{dens}(P) + O(1/t), \end{align*} $$
$$ \begin{align*}\delta_t \geq \mathrm{dens}(P) + O(1/t), \end{align*} $$
where 
 $O(1/t)$
 accounts for boundary intersections. We obtain
$O(1/t)$
 accounts for boundary intersections. We obtain 
 $\liminf _{t\to \infty } \delta _t \geq \Delta _d(K)$
. This finishes the lemma.
$\liminf _{t\to \infty } \delta _t \geq \Delta _d(K)$
. This finishes the lemma.
Lemma 9. For any compact K, there is a countable set 
 $\widetilde K$
 such that
$\widetilde K$
 such that 
 $\Delta _d(K)=\Delta _d(\widetilde K)$
.
$\Delta _d(K)=\Delta _d(\widetilde K)$
.
Proof. Since K is compact, there is a packing 
 $P=X+{\tfrac 12}B_d$
 such that
$P=X+{\tfrac 12}B_d$
 such that 
 $\mathrm {dens}(P)=\Delta _d(K)$
. Since X is countable, we can write
$\mathrm {dens}(P)=\Delta _d(K)$
. Since X is countable, we can write 
 $X=\{x_1,x_2,\ldots \}$
. Define the set
$X=\{x_1,x_2,\ldots \}$
. Define the set 
 $$ \begin{align*} K_0 =\{\alpha \in K : |x_i-x_j|=\alpha \text{ for some } i < j\}. \end{align*} $$
$$ \begin{align*} K_0 =\{\alpha \in K : |x_i-x_j|=\alpha \text{ for some } i < j\}. \end{align*} $$
Define 
 $\widetilde {K}:=K_0\cup \{1,\max (K)\}$
. Then,
$\widetilde {K}:=K_0\cup \{1,\max (K)\}$
. Then, 
 $\widetilde {K}\subset K$
 is a countable subset such that
$\widetilde {K}\subset K$
 is a countable subset such that 
 $\max ( K)=\max (\widetilde K)$
, and by construction, P is
$\max ( K)=\max (\widetilde K)$
, and by construction, P is 
 $\widetilde K$
-admissible. We have
$\widetilde K$
-admissible. We have 
 $$ \begin{align*}\Delta_d(\widetilde K)\leq \Delta_d(K) = \mathrm{dens}(P) \leq \Delta_d(\widetilde K). \end{align*} $$
$$ \begin{align*}\Delta_d(\widetilde K)\leq \Delta_d(K) = \mathrm{dens}(P) \leq \Delta_d(\widetilde K). \end{align*} $$
This concludes the proof.
Define
 $$ \begin{align*} n_d(K):=\max \{\#X : X\subset \mathbb{R}^d \text{ and } |x-y|\in K \text{ for all } x,y\in X \text{ with } x\neq y\}. \end{align*} $$
$$ \begin{align*} n_d(K):=\max \{\#X : X\subset \mathbb{R}^d \text{ and } |x-y|\in K \text{ for all } x,y\in X \text{ with } x\neq y\}. \end{align*} $$
Since K is bounded, it is clear that X is finite and any maximal set X (which always exist) can be placed inside a sphere of radii 
 $\sup (K)$
. For instance, if
$\sup (K)$
. For instance, if 
 $K=\{1\}$
, then
$K=\{1\}$
, then 
 $n_d(K)=d+1$
, and this is realized by the
$n_d(K)=d+1$
, and this is realized by the 
 $(d+1)$
-simplex. Let
$(d+1)$
-simplex. Let 
 $\mathrm {kiss}_d$
 denote the kissing number of
$\mathrm {kiss}_d$
 denote the kissing number of 
 $\mathbb {R}^d$
 – that is, the largest number of equal size spheres that can touch a central sphere with no overlapping. Then it is easy to see that
$\mathbb {R}^d$
 – that is, the largest number of equal size spheres that can touch a central sphere with no overlapping. Then it is easy to see that 
 $$ \begin{align*}n_d([1,2]) \geq 1+\mathrm{kiss}_d. \end{align*} $$
$$ \begin{align*}n_d([1,2]) \geq 1+\mathrm{kiss}_d. \end{align*} $$
Conjecture 5. For all d, we have 
 $n_d([1,2]) = 1+\mathrm {kiss}_d$
.
$n_d([1,2]) = 1+\mathrm {kiss}_d$
.
 Trivially, this is attained for 
 $d=1$
. It seems to be the case for
$d=1$
. It seems to be the case for 
 $d=2$
 and unlikely to be false for
$d=2$
 and unlikely to be false for 
 $d=3$
. It turns out that the number
$d=3$
. It turns out that the number 
 $n_d(K)$
 can be extracted from a constrained packing problem if one sets
$n_d(K)$
 can be extracted from a constrained packing problem if one sets 
 $K_\lambda = K \cup \{\lambda \}$
 and sends
$K_\lambda = K \cup \{\lambda \}$
 and sends 
 $\lambda \to \infty $
.
$\lambda \to \infty $
.
Proposition 10. Let 
 $K \subset [1,\infty )$
 be bounded with
$K \subset [1,\infty )$
 be bounded with 
 $1\in K$
 and let
$1\in K$
 and let 
 $ K_\lambda = K \cup \{\lambda \}. $
 Then
$ K_\lambda = K \cup \{\lambda \}. $
 Then 
 $$ \begin{align*}\lim_{\lambda\to\infty} \lambda^d \Delta_d(K_\lambda)=n_d(K)\Delta_d. \end{align*} $$
$$ \begin{align*}\lim_{\lambda\to\infty} \lambda^d \Delta_d(K_\lambda)=n_d(K)\Delta_d. \end{align*} $$
Proof. First, we claim that 
 $\Delta _d(K_\lambda )\geq \frac {n_d(K)\cdot \Delta _d}{\left (\beta +\lambda \right )^d}$
, where
$\Delta _d(K_\lambda )\geq \frac {n_d(K)\cdot \Delta _d}{\left (\beta +\lambda \right )^d}$
, where 
 $\beta =\sup {K}$
. In order to do that, we will construct a packing
$\beta =\sup {K}$
. In order to do that, we will construct a packing 
 $P_\lambda $
 that is
$P_\lambda $
 that is 
 $K_\lambda $
-admissible and show that
$K_\lambda $
-admissible and show that 
 $\mathrm {dens}(P_\lambda )\geq \frac {n_d(K)\cdot \Delta _d}{\left (\beta +\lambda \right )^d}$
. The packing
$\mathrm {dens}(P_\lambda )\geq \frac {n_d(K)\cdot \Delta _d}{\left (\beta +\lambda \right )^d}$
. The packing 
 $P_\lambda $
 will not necessarily have maximal density; however, it will have a nice structure which makes it easy to estimate its density. Let
$P_\lambda $
 will not necessarily have maximal density; however, it will have a nice structure which makes it easy to estimate its density. Let 
 $Y\subset \beta B_d$
 be a maximal cluster of K-admissible points attaining
$Y\subset \beta B_d$
 be a maximal cluster of K-admissible points attaining 
 $\#{Y}=n_d(K)$
. Let
$\#{Y}=n_d(K)$
. Let 
 $\widetilde {P_\lambda }=X_\lambda +\frac {\beta +\lambda }{2} B_d$
 be an unconstrained periodic sphere packing (with spheres of diameter
$\widetilde {P_\lambda }=X_\lambda +\frac {\beta +\lambda }{2} B_d$
 be an unconstrained periodic sphere packing (with spheres of diameter 
 $\beta +\lambda $
) such that
$\beta +\lambda $
) such that 
 $\mathrm {dens}(\widetilde {P_\lambda })>\Delta _d-\varepsilon $
. Define the packing
$\mathrm {dens}(\widetilde {P_\lambda })>\Delta _d-\varepsilon $
. Define the packing 
 $$ \begin{align*}P_\lambda = X_\lambda + Y+{\tfrac12}B_d. \end{align*} $$
$$ \begin{align*}P_\lambda = X_\lambda + Y+{\tfrac12}B_d. \end{align*} $$
We claim 
 $P_\lambda $
 is
$P_\lambda $
 is 
 $K_\lambda $
 admissible. To see this note that if
$K_\lambda $
 admissible. To see this note that if 
 $x_\lambda +y$
 and
$x_\lambda +y$
 and 
 $x_\lambda '+y'$
 are two points in
$x_\lambda '+y'$
 are two points in 
 $X_\lambda +Y$
, then their distance is
$X_\lambda +Y$
, then their distance is 
 $\geq \lambda $
 if
$\geq \lambda $
 if 
 $x_\lambda \neq x_\lambda '$
. If
$x_\lambda \neq x_\lambda '$
. If 
 $x_\lambda =x_\lambda '$
, then their distance is
$x_\lambda =x_\lambda '$
, then their distance is 
 $|y-y'|\in K$
. We obtain
$|y-y'|\in K$
. We obtain 
 $$ \begin{align*} \mathrm{dens}(P_\lambda) & = \lim_{t\to\infty} \frac{\#((X_\lambda+Y)\cap tQ_d) \mathrm{vol}({\tfrac12}B_d)}{\mathrm{vol}(tQ_d)} \\ & = \lim_{t\to\infty} \frac{\#(X_\lambda\cap (t-2\beta -1)Q_d) n_d(K)\mathrm{vol}(\frac{\beta+\lambda}{2} B_d)}{(\beta+\lambda)^d\mathrm{vol}(tQ_d)} \\ & = \frac{n_d(K)\mathrm{dens}(\widetilde{P_\lambda})}{(\beta+\lambda)^d}> \frac{n_d(K)(\Delta_d-\varepsilon)}{(\beta+\lambda)^d}. \end{align*} $$
$$ \begin{align*} \mathrm{dens}(P_\lambda) & = \lim_{t\to\infty} \frac{\#((X_\lambda+Y)\cap tQ_d) \mathrm{vol}({\tfrac12}B_d)}{\mathrm{vol}(tQ_d)} \\ & = \lim_{t\to\infty} \frac{\#(X_\lambda\cap (t-2\beta -1)Q_d) n_d(K)\mathrm{vol}(\frac{\beta+\lambda}{2} B_d)}{(\beta+\lambda)^d\mathrm{vol}(tQ_d)} \\ & = \frac{n_d(K)\mathrm{dens}(\widetilde{P_\lambda})}{(\beta+\lambda)^d}> \frac{n_d(K)(\Delta_d-\varepsilon)}{(\beta+\lambda)^d}. \end{align*} $$
Since both 
 $\widetilde {P_\lambda }$
 and
$\widetilde {P_\lambda }$
 and 
 $P_\lambda $
 are periodic, equality between limits above is justified. Letting
$P_\lambda $
 are periodic, equality between limits above is justified. Letting 
 $\varepsilon \to 0$
 proves our claim.
$\varepsilon \to 0$
 proves our claim.
 Now we claim that 
 $\Delta _d(K_\lambda )\leq \frac {n_d(K)\cdot \Delta _d}{\lambda ^d}$
. Let
$\Delta _d(K_\lambda )\leq \frac {n_d(K)\cdot \Delta _d}{\lambda ^d}$
. Let 
 $Y+{\tfrac 12}B_d$
 be a periodic
$Y+{\tfrac 12}B_d$
 be a periodic 
 $K_\lambda $
-admissible sphere packing such that
$K_\lambda $
-admissible sphere packing such that 
 $\mathrm {dens}(Y_\lambda )>\Delta _d(K_\lambda )-\varepsilon $
. We can assume that
$\mathrm {dens}(Y_\lambda )>\Delta _d(K_\lambda )-\varepsilon $
. We can assume that 
 $\lambda>2\beta $
. Define an equivalence relation in Y by saying that
$\lambda>2\beta $
. Define an equivalence relation in Y by saying that 
 $y_1 \sim y_2$
 if
$y_1 \sim y_2$
 if 
 $|y_1-y_2|\leq \beta $
. This is an equivalence relation since if
$|y_1-y_2|\leq \beta $
. This is an equivalence relation since if 
 $y_1\sim y_2$
 and
$y_1\sim y_2$
 and 
 $y_2\sim y_3$
 but
$y_2\sim y_3$
 but 
 $|y_1-y_3|>\beta $
, then
$|y_1-y_3|>\beta $
, then 
 $|y_1-y_3|\geq \lambda $
, but triangle inequality shows that
$|y_1-y_3|\geq \lambda $
, but triangle inequality shows that 
 $|y_1-y_3|\leq 2\beta < \lambda $
, a contradiction. Let
$|y_1-y_3|\leq 2\beta < \lambda $
, a contradiction. Let 
 $\widetilde Y=\{[y_1],[y_2],\ldots \}$
 be these equivalence classes, where the
$\widetilde Y=\{[y_1],[y_2],\ldots \}$
 be these equivalence classes, where the 
 $y_j$
’s are representatives of each class. Observe that
$y_j$
’s are representatives of each class. Observe that 
 $|y_i-y_j|\geq \lambda $
 if
$|y_i-y_j|\geq \lambda $
 if 
 $i<j$
, that the set
$i<j$
, that the set 
 $[y_j]$
 has only distances in K and is contained in
$[y_j]$
 has only distances in K and is contained in 
 $y_j + {\beta }B_d$
. Thus,
$y_j + {\beta }B_d$
. Thus, 
 $\#[y_j]\leq n_d(K)$
. We obtain
$\#[y_j]\leq n_d(K)$
. We obtain 
 $$ \begin{align*} \Delta_d(K_\lambda) -\varepsilon & < \lim_{t\to\infty} \frac{\#(Y\cap tQ_d) \mathrm{vol}({\tfrac12}B_d)}{\mathrm{vol}(tQ_d)} \\ & \leq \limsup_{t\to\infty} \frac{ \mathrm{vol}({\tfrac12}B_d) \sum_{ [y_j]\cap tQ_d \neq \emptyset } \#[y_j]}{\mathrm{vol}(tQ_d)} \\ & \leq \frac{n_d(K)}{\lambda^d} \limsup_{t\to\infty} \frac{\#(\{y_1,y_2,\ldots \}\cap (t+2\beta)Q_d) \mathrm{vol}(\tfrac{\lambda}{2}B_d)}{\mathrm{vol}(tQ_d)} \\ & \leq \frac{n_d(K)}{\lambda^d} \Delta_d. \end{align*} $$
$$ \begin{align*} \Delta_d(K_\lambda) -\varepsilon & < \lim_{t\to\infty} \frac{\#(Y\cap tQ_d) \mathrm{vol}({\tfrac12}B_d)}{\mathrm{vol}(tQ_d)} \\ & \leq \limsup_{t\to\infty} \frac{ \mathrm{vol}({\tfrac12}B_d) \sum_{ [y_j]\cap tQ_d \neq \emptyset } \#[y_j]}{\mathrm{vol}(tQ_d)} \\ & \leq \frac{n_d(K)}{\lambda^d} \limsup_{t\to\infty} \frac{\#(\{y_1,y_2,\ldots \}\cap (t+2\beta)Q_d) \mathrm{vol}(\tfrac{\lambda}{2}B_d)}{\mathrm{vol}(tQ_d)} \\ & \leq \frac{n_d(K)}{\lambda^d} \Delta_d. \end{align*} $$
Letting 
 $\varepsilon \to 0$
 finishes the proof.
$\varepsilon \to 0$
 finishes the proof.
Observe that we have actually proven the stronger result
 $$ \begin{align*}\frac{n_d(K)\cdot \Delta_d}{\left(\beta+\lambda\right)^d} \leq \Delta_d(K_\lambda) \leq \frac{n_d(K)\cdot \Delta_d}{\lambda^d}. \end{align*} $$
$$ \begin{align*}\frac{n_d(K)\cdot \Delta_d}{\left(\beta+\lambda\right)^d} \leq \Delta_d(K_\lambda) \leq \frac{n_d(K)\cdot \Delta_d}{\lambda^d}. \end{align*} $$
In particular, in conjunction with Theorem 3, we have the new linear program to produce upper bounds for kissing numbers.
Corollary 11. Let 
 $\lambda \geq 4$
. Let
$\lambda \geq 4$
. Let 
 $F:\mathbb {R}^d\to \mathbb {R}$
 be a continuous
$F:\mathbb {R}^d\to \mathbb {R}$
 be a continuous 
 $L^1$
-function such that
$L^1$
-function such that 
 $\widehat F\geq 0$
 and
$\widehat F\geq 0$
 and 
 $F(x)\leq 0$
 if
$F(x)\leq 0$
 if 
 $1<|x|<2$
 or if
$1<|x|<2$
 or if 
 $|x|>\lambda $
. Then
$|x|>\lambda $
. Then 
 $$ \begin{align*}1+\mathrm{kiss}_d \leq \frac{(2+\lambda)^d}{\Delta_d} \frac{F(0)}{\widehat F(0)} \mathrm{vol}({\tfrac12}B_d). \end{align*} $$
$$ \begin{align*}1+\mathrm{kiss}_d \leq \frac{(2+\lambda)^d}{\Delta_d} \frac{F(0)}{\widehat F(0)} \mathrm{vol}({\tfrac12}B_d). \end{align*} $$
 The structure of the best configuration for 
 $d=2$
,
$d=2$
, 
 $K=[1,2]\cup \{\lambda \}$
 and large
$K=[1,2]\cup \{\lambda \}$
 and large 
 $\lambda $
 will look like Figure 3.
$\lambda $
 will look like Figure 3.

Figure 3 Best configuration for 
 $d=2$
 and
$d=2$
 and 
 $K=[1,2]\cup \{4\}$
.
$K=[1,2]\cup \{4\}$
.
 As a proof of concept, we now prove that this linear program is sharp for 
 $d=1$
. In this case, we have the inequality
$d=1$
. In this case, we have the inequality 
 $3\leq (2+\lambda )F(0)/\widehat F(0)$
. Define the following symmetric set
$3\leq (2+\lambda )F(0)/\widehat F(0)$
. Define the following symmetric set 
 $$ \begin{align*}E_\lambda=\bigcup_{n=-N}^{N}[3n-1/2,3n+1/2] \end{align*} $$
$$ \begin{align*}E_\lambda=\bigcup_{n=-N}^{N}[3n-1/2,3n+1/2] \end{align*} $$
with 
 $N=\lfloor (\lambda -1)/6\rfloor $
. Then it is easy to see that
$N=\lfloor (\lambda -1)/6\rfloor $
. Then it is easy to see that 
 $F_\lambda =\mathrm {1}_{E_\lambda }\star \mathrm {1}_{E_\lambda } $
 (where
$F_\lambda =\mathrm {1}_{E_\lambda }\star \mathrm {1}_{E_\lambda } $
 (where 
 $\star $
 is the convolution operator) is positive definite and
$\star $
 is the convolution operator) is positive definite and 
 $F_\lambda (x)=0$
 if
$F_\lambda (x)=0$
 if 
 $|x|>\lambda $
 or if
$|x|>\lambda $
 or if 
 $1<|x|<2$
, since
$1<|x|<2$
, since 
 $E_\lambda +E_\lambda =\cup _{n=-2N}^{2N}[3n-1,3n+1] $
. Moreover,
$E_\lambda +E_\lambda =\cup _{n=-2N}^{2N}[3n-1,3n+1] $
. Moreover, 
 $F_\lambda (0)/\widehat F_\lambda (0)=1/\mathrm {vol}(E_\lambda )=1/(1+2N) \sim 3/\lambda $
. We conclude that
$F_\lambda (0)/\widehat F_\lambda (0)=1/\mathrm {vol}(E_\lambda )=1/(1+2N) \sim 3/\lambda $
. We conclude that 
 $\lim _{\lambda \to \infty } (2+\lambda )F_\lambda (0)/\widehat F_\lambda (0) = 3$
, proving the bound is sharp.
$\lim _{\lambda \to \infty } (2+\lambda )F_\lambda (0)/\widehat F_\lambda (0) = 3$
, proving the bound is sharp.
3.1 Proof of Theorem 3
 In view of Proposition 8, it suffices to consider just periodic sphere packings 
 $P=Y+\Lambda +{\tfrac 12}B_d $
. Assume first F is of Schwartz class. We apply Poisson summation to obtain
$P=Y+\Lambda +{\tfrac 12}B_d $
. Assume first F is of Schwartz class. We apply Poisson summation to obtain 
 $$ \begin{align*}(\#Y) F(0) \geq \sum_{y,y'\in Y}\sum_{\lambda \in \Lambda} F(\lambda+y-y') = \frac{1}{\mathrm{vol}(\mathbb{R}^d/\Lambda)}\sum_{\xi \in \Lambda^*} \widehat F(\xi) \left| \sum_{y\in Y} e^{2\pi iy\cdot \xi}\right|^2 \geq \frac{(\#Y)^2\widehat F(0)}{\mathrm{vol}(\mathbb{R}^d/\Lambda)}. \end{align*} $$
$$ \begin{align*}(\#Y) F(0) \geq \sum_{y,y'\in Y}\sum_{\lambda \in \Lambda} F(\lambda+y-y') = \frac{1}{\mathrm{vol}(\mathbb{R}^d/\Lambda)}\sum_{\xi \in \Lambda^*} \widehat F(\xi) \left| \sum_{y\in Y} e^{2\pi iy\cdot \xi}\right|^2 \geq \frac{(\#Y)^2\widehat F(0)}{\mathrm{vol}(\mathbb{R}^d/\Lambda)}. \end{align*} $$
Rearranging terms, we deduce that 
 $\mathrm {dens}(P)\leq \mathrm {vol}({\tfrac 12}B_d)F(0)/\widehat F(0)$
. In the unconstrained packing problem one could now, by a standard convolution approximation argument, show the same inequality holds when F is only continuous and
$\mathrm {dens}(P)\leq \mathrm {vol}({\tfrac 12}B_d)F(0)/\widehat F(0)$
. In the unconstrained packing problem one could now, by a standard convolution approximation argument, show the same inequality holds when F is only continuous and 
 $L^1$
. However, this trick does not work for constrained sphere packings, since convolutions destroy K-admissibility of functions. Instead, we give below a direct proof based on a new trick involving the Féjer kernel.
$L^1$
. However, this trick does not work for constrained sphere packings, since convolutions destroy K-admissibility of functions. Instead, we give below a direct proof based on a new trick involving the Féjer kernel.
 Let A be a full rank matrix such that 
 $\Lambda =A\cdot \mathbb {Z}^d$
 and let
$\Lambda =A\cdot \mathbb {Z}^d$
 and let 
 $$ \begin{align*}f_\Lambda(x)=\displaystyle\sum_{\lambda\in\Lambda} F(x+\lambda).\end{align*} $$
$$ \begin{align*}f_\Lambda(x)=\displaystyle\sum_{\lambda\in\Lambda} F(x+\lambda).\end{align*} $$
Then we see that 
 $f_\Lambda $
 is
$f_\Lambda $
 is 
 $\Lambda -$
periodic, that the summation above converges a.e. and that
$\Lambda -$
periodic, that the summation above converges a.e. and that 
 $f_\Lambda \in L^1(\mathbb {R}^d/\Lambda )$
. Note also that
$f_\Lambda \in L^1(\mathbb {R}^d/\Lambda )$
. Note also that 
 $$ \begin{align*}f_\Lambda\circ A(x)=\displaystyle\sum_{k\in\mathbb{Z}^d} F\circ A(x+k).\end{align*} $$
$$ \begin{align*}f_\Lambda\circ A(x)=\displaystyle\sum_{k\in\mathbb{Z}^d} F\circ A(x+k).\end{align*} $$
Observe that 
 $f_\Lambda \circ A \in L^1(\mathbb {R}^d/\mathbb {Z}^d)$
 and
$f_\Lambda \circ A \in L^1(\mathbb {R}^d/\mathbb {Z}^d)$
 and 
 $(f_\Lambda \circ A)^\wedge (\alpha )= |\det (A)|^{-1} \widehat F\circ A^{-\top }(\alpha )$
, where
$(f_\Lambda \circ A)^\wedge (\alpha )= |\det (A)|^{-1} \widehat F\circ A^{-\top }(\alpha )$
, where 
 $\mathrm {vol}(\mathbb {R}^d/\Lambda )=|\det (A)|$
 and we use
$\mathrm {vol}(\mathbb {R}^d/\Lambda )=|\det (A)|$
 and we use 
 $\top $
 for transpose. For N a positive integer, consider the N-th Féjer kernel
$\top $
 for transpose. For N a positive integer, consider the N-th Féjer kernel 
 $$ \begin{align*} \mathcal{F}_N(x)=\mathbf{1}_{Q_d}(x)\displaystyle\sum_{\substack{\alpha\in\mathbb{Z}^d\\ |\alpha|_\infty<N}} \displaystyle\prod_{j=1}^{d} \left(1-\displaystyle\frac{|\alpha_j|}{N}\right)e^{2\pi i\alpha\cdot x} = N^d \prod_{j=1}^d \left( \frac{\sin(\pi N x_j)}{N\sin(\pi x_j)} \right)^2 \mathbf{1}_{|x_j|<1/2}. \end{align*} $$
$$ \begin{align*} \mathcal{F}_N(x)=\mathbf{1}_{Q_d}(x)\displaystyle\sum_{\substack{\alpha\in\mathbb{Z}^d\\ |\alpha|_\infty<N}} \displaystyle\prod_{j=1}^{d} \left(1-\displaystyle\frac{|\alpha_j|}{N}\right)e^{2\pi i\alpha\cdot x} = N^d \prod_{j=1}^d \left( \frac{\sin(\pi N x_j)}{N\sin(\pi x_j)} \right)^2 \mathbf{1}_{|x_j|<1/2}. \end{align*} $$
Denote by 
 $\star $
 the convolution operator. It is well known that the
$\star $
 the convolution operator. It is well known that the 
 $\mathcal {F}_N$
 is an approximate identity – that is,
$\mathcal {F}_N$
 is an approximate identity – that is, 
 $\mathcal {F}_N\star G(x)\to G(x)$
 as
$\mathcal {F}_N\star G(x)\to G(x)$
 as 
 $N\to \infty $
, for any x and any bounded continuous function G. The nice bit is that if G is
$N\to \infty $
, for any x and any bounded continuous function G. The nice bit is that if G is 
 $\mathbb {Z}^d$
-periodic, then convolution simply multiplies Fourier coefficients. Routine computations show that
$\mathbb {Z}^d$
-periodic, then convolution simply multiplies Fourier coefficients. Routine computations show that 
 $$ \begin{align*}(f_\Lambda\circ A) \star \mathcal{F}_N(x) = \frac{1}{\mathrm{vol}(\mathbb{R}^d/\Lambda)}\sum_{\substack{\alpha\in\mathbb{Z}^d\\ |\alpha|_\infty<N}} \widehat F\circ A^{-\top}(\alpha) \displaystyle\prod_{j=1}^{d} \left(1-\displaystyle\frac{|\alpha_j|}{N}\right) e^{2\pi i \alpha \cdot x} \end{align*} $$
$$ \begin{align*}(f_\Lambda\circ A) \star \mathcal{F}_N(x) = \frac{1}{\mathrm{vol}(\mathbb{R}^d/\Lambda)}\sum_{\substack{\alpha\in\mathbb{Z}^d\\ |\alpha|_\infty<N}} \widehat F\circ A^{-\top}(\alpha) \displaystyle\prod_{j=1}^{d} \left(1-\displaystyle\frac{|\alpha_j|}{N}\right) e^{2\pi i \alpha \cdot x} \end{align*} $$
is indeed a trigonometric polynomial. We conclude that
 $$ \begin{align*} \sum_{y,y'\in Y} (f_\Lambda\circ A) \star \mathcal{F}_N(A^{-1}(y-y')) \geq \frac{(\#Y)^2}{\mathrm{vol}(\mathbb{R}^d/\Lambda)} \widehat F(0). \end{align*} $$
$$ \begin{align*} \sum_{y,y'\in Y} (f_\Lambda\circ A) \star \mathcal{F}_N(A^{-1}(y-y')) \geq \frac{(\#Y)^2}{\mathrm{vol}(\mathbb{R}^d/\Lambda)} \widehat F(0). \end{align*} $$
However, letting 
 $m:=\max _{y\neq y'} {|y-y'|}+\sup (K)+\max _{x\in \mathbb {R}^d/\Lambda } |x|$
, the left-hand side above is equal to
$m:=\max _{y\neq y'} {|y-y'|}+\sup (K)+\max _{x\in \mathbb {R}^d/\Lambda } |x|$
, the left-hand side above is equal to 
 $$ \begin{align*} &\sum_{y,y'\in Y}\displaystyle\int_{Q_d} \mathcal{F}_N(x)\left(f_\Lambda\circ A\right)\left(A^{-1}(y-y')-x\right)dx\\ & = \frac{1}{|\det(A)|}\displaystyle\sum_{y,y'\in Y}\displaystyle\int_{\mathbb{R}^d/\Lambda} \mathcal{F}_N(A^{-1}x)f_\Lambda\left(y-y'- x\right)dx\\ &\leq\displaystyle\frac{1}{\mathrm{vol}(\mathbb{R}^d/\Lambda)}\displaystyle\sum_{y,y'\in Y}\displaystyle\sum_{\substack{\lambda\in\Lambda\\ |\lambda|\leq m}} \displaystyle\int_{\mathbb{R}^d/\Lambda} \mathcal{F}_N(A^{-1}x)F(y-y'-x+\lambda)dx\\ &=\displaystyle\sum_{y,y'\in Y}\displaystyle\sum_{\substack{\lambda\in\Lambda\\ |\lambda|\leq m}} \mathcal{F}_N\star(F\circ A)(A^{-1}(y-y'+\lambda))\\ &\xrightarrow{N\rightarrow\infty} \displaystyle\sum_{y,y'\in Y}\displaystyle\sum_{\substack{\lambda\in\Lambda\\ |\lambda|\leq m}} (F\circ A)(A^{-1}(y-y'+\lambda))\\ &=\displaystyle\sum_{y,y'\in Y}\displaystyle\sum_{\substack{\lambda\in\Lambda\\ |\lambda|\leq m}} F(y-y'+\lambda)\\ &\leq \#Y\cdot F(0). \end{align*} $$
$$ \begin{align*} &\sum_{y,y'\in Y}\displaystyle\int_{Q_d} \mathcal{F}_N(x)\left(f_\Lambda\circ A\right)\left(A^{-1}(y-y')-x\right)dx\\ & = \frac{1}{|\det(A)|}\displaystyle\sum_{y,y'\in Y}\displaystyle\int_{\mathbb{R}^d/\Lambda} \mathcal{F}_N(A^{-1}x)f_\Lambda\left(y-y'- x\right)dx\\ &\leq\displaystyle\frac{1}{\mathrm{vol}(\mathbb{R}^d/\Lambda)}\displaystyle\sum_{y,y'\in Y}\displaystyle\sum_{\substack{\lambda\in\Lambda\\ |\lambda|\leq m}} \displaystyle\int_{\mathbb{R}^d/\Lambda} \mathcal{F}_N(A^{-1}x)F(y-y'-x+\lambda)dx\\ &=\displaystyle\sum_{y,y'\in Y}\displaystyle\sum_{\substack{\lambda\in\Lambda\\ |\lambda|\leq m}} \mathcal{F}_N\star(F\circ A)(A^{-1}(y-y'+\lambda))\\ &\xrightarrow{N\rightarrow\infty} \displaystyle\sum_{y,y'\in Y}\displaystyle\sum_{\substack{\lambda\in\Lambda\\ |\lambda|\leq m}} (F\circ A)(A^{-1}(y-y'+\lambda))\\ &=\displaystyle\sum_{y,y'\in Y}\displaystyle\sum_{\substack{\lambda\in\Lambda\\ |\lambda|\leq m}} F(y-y'+\lambda)\\ &\leq \#Y\cdot F(0). \end{align*} $$
The limit above is justified because we have a finite sum. The theorem follows.
4 One-dimensional packings and dominos
 We now focus on the one-dimensional case, and we ask for the existence of periodic packings with the maximal density. Let 
 $I=[0,1]$
 be the unit interval. We begin with the observation that we can restrict our attention to packings of the half-line
$I=[0,1]$
 be the unit interval. We begin with the observation that we can restrict our attention to packings of the half-line 
 $[0,\infty )$
 only; that is,
$[0,\infty )$
 only; that is, 
 $$ \begin{align*}\Delta_1(K)=\sup_{P \in \mathcal{P}_1(K) \text{ and } P\subset [0,\infty)} \mathrm{dens}^+(P), \end{align*} $$
$$ \begin{align*}\Delta_1(K)=\sup_{P \in \mathcal{P}_1(K) \text{ and } P\subset [0,\infty)} \mathrm{dens}^+(P), \end{align*} $$
where 
 $\mathrm {dens}^+(P)=\limsup _{t\to \infty } \mathrm {vol}(P\cap [0,t])/t$
. Indeed, if
$\mathrm {dens}^+(P)=\limsup _{t\to \infty } \mathrm {vol}(P\cap [0,t])/t$
. Indeed, if 
 $P\subset (-\infty ,\infty )$
 is a K-admissible periodic packing, then
$P\subset (-\infty ,\infty )$
 is a K-admissible periodic packing, then 
 $$ \begin{align*}\mathrm{dens}(P) \leq \max\{\mathrm{dens}^+(P\cap \mathbb{R}_+),\mathrm{dens}^+(P \cap \mathbb{R}_-)\}.\end{align*} $$
$$ \begin{align*}\mathrm{dens}(P) \leq \max\{\mathrm{dens}^+(P\cap \mathbb{R}_+),\mathrm{dens}^+(P \cap \mathbb{R}_-)\}.\end{align*} $$
Now note that for any K-admissible packing of 
 $[0,\infty )$
, we can assume that I starts at
$[0,\infty )$
, we can assume that I starts at 
 $0$
 and so the packing can be uniquely described as a sequence
$0$
 and so the packing can be uniquely described as a sequence 
 $$ \begin{align*}w=a_{1}a_{2}\ldots a_{k}\ldots , \end{align*} $$
$$ \begin{align*}w=a_{1}a_{2}\ldots a_{k}\ldots , \end{align*} $$
where 
 $a_j\in K\cup (\sup (K),\infty )$
 represent the distance between consecutive centers of intervals in the packing. From now on, we assume that
$a_j\in K\cup (\sup (K),\infty )$
 represent the distance between consecutive centers of intervals in the packing. From now on, we assume that 
 $\sup (K)\in K$
, and we set
$\sup (K)\in K$
, and we set 
 $N:=\lceil \sup (K)\rceil $
. Hence, we can always assume that
$N:=\lceil \sup (K)\rceil $
. Hence, we can always assume that 
 $a_j\in K$
 for all j since otherwise, we can reduce that distance without destroying K-admissibility and obtain a denser packing. For simplicity, we just write
$a_j\in K$
 for all j since otherwise, we can reduce that distance without destroying K-admissibility and obtain a denser packing. For simplicity, we just write  for K-admissible packings of
 for K-admissible packings of 
 $[0,\infty )$
 with distances between adjacent centers of intervals drawn from K that start with I touching
$[0,\infty )$
 with distances between adjacent centers of intervals drawn from K that start with I touching 
 $0$
.
$0$
.
 A word will be a finite ordered sequence of elements of the alphabet 
 $\Sigma =K$
. For instance,
$\Sigma =K$
. For instance, 
 $w=a_{1}a_{2}\ldots a_{k}$
 is a word of length
$w=a_{1}a_{2}\ldots a_{k}$
 is a word of length 
 $\#w=k$
. It will be useful to consider the empty word, denoted by
$\#w=k$
. It will be useful to consider the empty word, denoted by 
 $\varnothing $
, which has no elements and has length
$\varnothing $
, which has no elements and has length 
 $\#\varnothing =0$
. We can also define the norm of w by
$\#\varnothing =0$
. We can also define the norm of w by 
 $$ \begin{align*}|w|=\sum_{i=1}^k a_i. \end{align*} $$
$$ \begin{align*}|w|=\sum_{i=1}^k a_i. \end{align*} $$
We denote by 
 $\Sigma ^*$
 the set of all finite words. We will now construct a domino set
$\Sigma ^*$
 the set of all finite words. We will now construct a domino set 
 $\mathcal {D}$
 by
$\mathcal {D}$
 by 
 $$ \begin{align*} \mathcal{D}_K:=\big\{(w,w')\in\Sigma^*\times\Sigma^*: & \#w=\#w'=N \text{ and any subword } {s} \text{ of } ww' \\ & \text{ satisfies } |s| \in K \cup (\sup(K),\infty) \big\}. \end{align*} $$
$$ \begin{align*} \mathcal{D}_K:=\big\{(w,w')\in\Sigma^*\times\Sigma^*: & \#w=\#w'=N \text{ and any subword } {s} \text{ of } ww' \\ & \text{ satisfies } |s| \in K \cup (\sup(K),\infty) \big\}. \end{align*} $$
Thus, 
 $\mathcal {D}_K\subset \Sigma ^* \times \Sigma ^*$
. Here,
$\mathcal {D}_K\subset \Sigma ^* \times \Sigma ^*$
. Here, 
 $w{w'}$
 is the concatenated word. A linear domino tiling from
$w{w'}$
 is the concatenated word. A linear domino tiling from 
 $\mathcal {D}_K$
 is an infinite word
$\mathcal {D}_K$
 is an infinite word 
 $$ \begin{align*}\gamma=w_1w_2w_3\ldots \end{align*} $$
$$ \begin{align*}\gamma=w_1w_2w_3\ldots \end{align*} $$
where 
 $(w_i,w_{i+1})$
 is a domino piece from
$(w_i,w_{i+1})$
 is a domino piece from 
 $\mathcal {D}_K$
. We let
$\mathcal {D}_K$
. We let 
 $\mathcal {T}(\mathcal {D}_K)$
 be the set of domino tiling built this way. Given a tiling
$\mathcal {T}(\mathcal {D}_K)$
 be the set of domino tiling built this way. Given a tiling 
 $\gamma \in \mathcal {T}(\mathcal {D}_K)$
, we let
$\gamma \in \mathcal {T}(\mathcal {D}_K)$
, we let 
 $$ \begin{align*}\mathrm{dens}(\gamma) = \limsup_{t\to\infty} \frac{\#(w_1\ldots w_t)}{|w_1\ldots .w_t|}. \end{align*} $$
$$ \begin{align*}\mathrm{dens}(\gamma) = \limsup_{t\to\infty} \frac{\#(w_1\ldots w_t)}{|w_1\ldots .w_t|}. \end{align*} $$
We say 
 $\gamma $
 is periodic if for some n, we have
$\gamma $
 is periodic if for some n, we have 
 $w_{i+n}=w_i$
 for all i.
$w_{i+n}=w_i$
 for all i.
Proposition 12. There is a canonical bijection between  . This bijection maps periodic to periodic and satisfies
. This bijection maps periodic to periodic and satisfies 
 $$ \begin{align*}\mathrm{dens}^+(P)=\mathrm{dens}(\gamma_P). \end{align*} $$
$$ \begin{align*}\mathrm{dens}^+(P)=\mathrm{dens}(\gamma_P). \end{align*} $$
Proof. Indeed, given a packing  , we can write P as (infinite) sequence
, we can write P as (infinite) sequence 
 $a_1a_2\ldots $
, with
$a_1a_2\ldots $
, with 
 $a_{j}\in K$
. We then break this sequence into pieces of the form
$a_{j}\in K$
. We then break this sequence into pieces of the form 
 $w_{m+1}=a_{mN+1}\ldots a_{(m+1)N}$
, for
$w_{m+1}=a_{mN+1}\ldots a_{(m+1)N}$
, for 
 $m\in \mathbb {Z}_{\geq 0}$
, which are words belonging to
$m\in \mathbb {Z}_{\geq 0}$
, which are words belonging to 
 $\Sigma ^*$
. By construction, the pairs
$\Sigma ^*$
. By construction, the pairs 
 $(w_m,w_{m+1})\in \mathcal {D}_K$
, and then we can associate P to the tiling
$(w_m,w_{m+1})\in \mathcal {D}_K$
, and then we can associate P to the tiling  . Clearly, this map is injective. To show it is surjective, let
. Clearly, this map is injective. To show it is surjective, let  be any tiling. Then, by the choice of N, the packing P whose sequence of distances between consecutive centers is given by the concatenation
 be any tiling. Then, by the choice of N, the packing P whose sequence of distances between consecutive centers is given by the concatenation 
 $w_1w_2w_3\ldots $
 belongs to
$w_1w_2w_3\ldots $
 belongs to  , and its image is the tiling
, and its image is the tiling 
 $\gamma $
. This establishes a bijection between
$\gamma $
. This establishes a bijection between 
 $\mathcal {P}_+(K)$
 and
$\mathcal {P}_+(K)$
 and  . Moreover, it is easy to check that P is periodic if and only if
. Moreover, it is easy to check that P is periodic if and only if 
 $\gamma _P$
 is and that
$\gamma _P$
 is and that 
 $\mathrm {dens}^+(P)=\mathrm {dens}(\gamma _P)$
 holds for any packing
$\mathrm {dens}^+(P)=\mathrm {dens}(\gamma _P)$
 holds for any packing 
 $P \in \mathcal {P}_+(K)$
.
$P \in \mathcal {P}_+(K)$
.
 In general, we define a linear domino game as a tuple 
 $(\Sigma ,\mathcal {D})$
, where
$(\Sigma ,\mathcal {D})$
, where 
 $\Sigma $
 is a set of symbols and
$\Sigma $
 is a set of symbols and 
 $\mathcal {D}\subset \Sigma ^*\times \Sigma ^*$
 are domino pieces, where
$\mathcal {D}\subset \Sigma ^*\times \Sigma ^*$
 are domino pieces, where 
 $\Sigma ^*$
 is the set of all finite words in the alphabet
$\Sigma ^*$
 is the set of all finite words in the alphabet 
 $\Sigma $
. The set of linear domino tilings
$\Sigma $
. The set of linear domino tilings 
 $\mathcal {T}(\mathcal {D})$
 are those infinite words such that
$\mathcal {T}(\mathcal {D})$
 are those infinite words such that 
 $\gamma =w_1w_2w_3\ldots $
, where
$\gamma =w_1w_2w_3\ldots $
, where 
 $(w_i,w_{i+1})\in \mathcal {D}$
 for all i. We say that a map
$(w_i,w_{i+1})\in \mathcal {D}$
 for all i. We say that a map 
 $f:\Sigma ^* \to \mathbb {R}_+$
 is a norm function when it satisfies the following properties:
$f:\Sigma ^* \to \mathbb {R}_+$
 is a norm function when it satisfies the following properties: 
- 
(a) For any  $w_1,w_2,w_3\in \Sigma ^*$
, the function $w_1,w_2,w_3\in \Sigma ^*$
, the function $k \geq 0 \mapsto \frac {\#(w_1w_2^kw_3)}{f(w_1w_2^kw_3)}$
 is monotone; $k \geq 0 \mapsto \frac {\#(w_1w_2^kw_3)}{f(w_1w_2^kw_3)}$
 is monotone;
- 
(b) The function  $k>0\mapsto \frac {\#(w_2^k)}{f(w_2^k)}$
 is a positive constant; $k>0\mapsto \frac {\#(w_2^k)}{f(w_2^k)}$
 is a positive constant;
- 
(c) For any  $\epsilon>0$
, there is $\epsilon>0$
, there is $\delta>0$
 such that if $\delta>0$
 such that if $w'$
 is a sub-word of w with $w'$
 is a sub-word of w with $\#w-\#w'\leq \epsilon $
, then $\#w-\#w'\leq \epsilon $
, then $|f(w)-f(w')|\leq \delta $
. $|f(w)-f(w')|\leq \delta $
.
Note that if f is a norm function, then
 $$ \begin{align*}\frac{\#(w_1w_2^kw_3)}{f(w_1w_2^kw_3)} = \frac{\#(w_2^k)+O(1)}{f(w_2^k)+O(1)} = \frac{\#(w_2^k)+O(1)}{\frac{f(w_2)}{\#w_2}\#(w_2^k)+O(1)} = \frac{\#w_2}{f(w_2)}+O(1/k) \end{align*} $$
$$ \begin{align*}\frac{\#(w_1w_2^kw_3)}{f(w_1w_2^kw_3)} = \frac{\#(w_2^k)+O(1)}{f(w_2^k)+O(1)} = \frac{\#(w_2^k)+O(1)}{\frac{f(w_2)}{\#w_2}\#(w_2^k)+O(1)} = \frac{\#w_2}{f(w_2)}+O(1/k) \end{align*} $$
as 
 $k\to \infty $
. For a norm function f and a linear domino tiling
$k\to \infty $
. For a norm function f and a linear domino tiling 
 $\gamma =w_1w_2w_3\ldots \in \mathcal {T}(\mathcal {D})$
, we let
$\gamma =w_1w_2w_3\ldots \in \mathcal {T}(\mathcal {D})$
, we let 
 $$ \begin{align*}\mathrm{dens}_f(\gamma)=\limsup_{t\to\infty} \frac{\#(w_1\ldots .w_t)}{f(w_1\ldots .w_t)}. \end{align*} $$
$$ \begin{align*}\mathrm{dens}_f(\gamma)=\limsup_{t\to\infty} \frac{\#(w_1\ldots .w_t)}{f(w_1\ldots .w_t)}. \end{align*} $$
In particular, 
 $\mathrm {dens}_f(\beta \beta \beta \ldots )=\frac {\#\beta }{f(\beta )}$
. This is a generalization of the scenario described before by taking
$\mathrm {dens}_f(\beta \beta \beta \ldots )=\frac {\#\beta }{f(\beta )}$
. This is a generalization of the scenario described before by taking 
 $f=|\cdot |$
 and
$f=|\cdot |$
 and 
 $\mathcal {D}=\mathcal {D}_K$
.
$\mathcal {D}=\mathcal {D}_K$
.
Theorem 13. Let 
 $\Sigma $
 be a set of symbols and
$\Sigma $
 be a set of symbols and 
 $\mathcal {D}\subset \Sigma ^*\times \Sigma ^*$
 be a finite domino set. Let
$\mathcal {D}\subset \Sigma ^*\times \Sigma ^*$
 be a finite domino set. Let 
 $f:\Sigma ^* \to \mathbb {R}_+$
 be a norm function. Assume that
$f:\Sigma ^* \to \mathbb {R}_+$
 be a norm function. Assume that 
 $\sup _{\gamma \in \mathcal {T}(\mathcal {D})} \mathrm {dens}_f(\gamma ) \in (0,\infty )$
. Then there exists a periodic linear domino tiling
$\sup _{\gamma \in \mathcal {T}(\mathcal {D})} \mathrm {dens}_f(\gamma ) \in (0,\infty )$
. Then there exists a periodic linear domino tiling 
 $\gamma \in \mathcal {T}(\mathcal {D})$
, with period
$\gamma \in \mathcal {T}(\mathcal {D})$
, with period 
 $\leq \#\mathcal {D}$
, such that
$\leq \#\mathcal {D}$
, such that 
 $$ \begin{align*}\mathrm{ dens}_f(\gamma)=\sup_{\alpha\in\mathcal{T}(\mathcal{D})} \mathrm{dens}_f(\alpha).\end{align*} $$
$$ \begin{align*}\mathrm{ dens}_f(\gamma)=\sup_{\alpha\in\mathcal{T}(\mathcal{D})} \mathrm{dens}_f(\alpha).\end{align*} $$
 The following corollary is an immediate consequence of the above theorem by using 
 $\Sigma =K$
 and
$\Sigma =K$
 and 
 $f=|\cdot |$
.
$f=|\cdot |$
.
Corollary 14. If K is finite, then there exists a periodic K-admissible sphere packing of 
 $\mathbb {R}$
 of maximal density.
$\mathbb {R}$
 of maximal density.
 In order to prove Theorem 13, we need to introduce some terminology. Let 
 $V:= \{w\in \Sigma ^* : \exists w'\ s.t. \ (w,w')\in \mathcal {D} \text { or } (w',w)\in \mathcal {D}\}$
. We then can define a directed graph by
$V:= \{w\in \Sigma ^* : \exists w'\ s.t. \ (w,w')\in \mathcal {D} \text { or } (w',w)\in \mathcal {D}\}$
. We then can define a directed graph by 
 $\mathcal {G}=(V,\mathcal {D})$
, with vertex set V and directed edges
$\mathcal {G}=(V,\mathcal {D})$
, with vertex set V and directed edges 
 $\mathcal {D}$
. From now on, in
$\mathcal {D}$
. From now on, in 
 $\mathcal {G}$
, we only consider directed paths (i.e., finite sequences of the form
$\mathcal {G}$
, we only consider directed paths (i.e., finite sequences of the form 
 $\gamma =w_1\ldots w_m$
 such that
$\gamma =w_1\ldots w_m$
 such that 
 $(w_j,w_{j+1}) \in \mathcal {D}$
 for any j). We say that the path length of
$(w_j,w_{j+1}) \in \mathcal {D}$
 for any j). We say that the path length of 
 $\gamma $
 is m. We also say that
$\gamma $
 is m. We also say that 
 $\gamma $
 is a closed path when
$\gamma $
 is a closed path when 
 $(w_m,w_1)\in \mathcal {D}$
 and open otherwise. An atom is a simple closed path (closed and with no self-intersections).
$(w_m,w_1)\in \mathcal {D}$
 and open otherwise. An atom is a simple closed path (closed and with no self-intersections).
Proof of Theorem 13.
 Since 
 $\mathcal {D}$
 is finite, then V is finite and the set of atoms
$\mathcal {D}$
 is finite, then V is finite and the set of atoms 
 $\mathcal {A}$
 is also finite. First, we claim that for any closed path
$\mathcal {A}$
 is also finite. First, we claim that for any closed path 
 $\beta =w_1\ldots w_m$
 in
$\beta =w_1\ldots w_m$
 in 
 $\mathcal {G}$
, it holds that
$\mathcal {G}$
, it holds that 
 $$ \begin{align*} \frac{\#\beta}{f(\beta)} \leq \max_{\alpha\in\mathcal{A}} \frac{\#\alpha}{f(\alpha)}. \end{align*} $$
$$ \begin{align*} \frac{\#\beta}{f(\beta)} \leq \max_{\alpha\in\mathcal{A}} \frac{\#\alpha}{f(\alpha)}. \end{align*} $$
The inequality is trivial if 
 $\beta $
 is an atom. Assume by induction the claim is true if the path length of
$\beta $
 is an atom. Assume by induction the claim is true if the path length of 
 $\beta $
 is
$\beta $
 is 
 $\leq M$
. For
$\leq M$
. For 
 $m=M+1$
 and
$m=M+1$
 and 
 $\beta $
 not an atom, then
$\beta $
 not an atom, then 
 $\beta $
 must have some self-intersection (i.e., there exist
$\beta $
 must have some self-intersection (i.e., there exist 
 $1\leq i<j\leq M+1$
 such that
$1\leq i<j\leq M+1$
 such that 
 $w_i=w_j$
). Let
$w_i=w_j$
). Let 
 $v_1=w_1\ldots w_{i-1}$
,
$v_1=w_1\ldots w_{i-1}$
, 
 $v_2=w_i\ldots w_{j-1}$
 and
$v_2=w_i\ldots w_{j-1}$
 and 
 $v_3=w_j\ldots w_{M+1}$
. Then
$v_3=w_j\ldots w_{M+1}$
. Then 
 $v_1,v_2,v_3\in \Sigma ^*$
,
$v_1,v_2,v_3\in \Sigma ^*$
, 
 $v_1v_3$
 and
$v_1v_3$
 and 
 $v_2$
 are closed paths in
$v_2$
 are closed paths in 
 $\mathcal {G}$
 with path lengths
$\mathcal {G}$
 with path lengths 
 $\leq M$
 (note that we may have
$\leq M$
 (note that we may have 
 $v_1$
 or
$v_1$
 or 
 $v_3$
 the empty word, but not both at the same time). By monotonicity hypothesis and the induction hypothesis, we deduce
$v_3$
 the empty word, but not both at the same time). By monotonicity hypothesis and the induction hypothesis, we deduce 
 $$ \begin{align*} \frac{\#\beta}{f(\beta)}=\frac{\#(v_1v_2v_3)}{f(v_1v_2v_3)}\leq \max\left\{\frac{\#(v_1v_3)}{f(v_1v_3)},\frac{\#v_2}{f(v_2)}\right\}\leq \max_{\alpha\in\mathcal{A}} \frac{\#\alpha}{f(\alpha)}, \end{align*} $$
$$ \begin{align*} \frac{\#\beta}{f(\beta)}=\frac{\#(v_1v_2v_3)}{f(v_1v_2v_3)}\leq \max\left\{\frac{\#(v_1v_3)}{f(v_1v_3)},\frac{\#v_2}{f(v_2)}\right\}\leq \max_{\alpha\in\mathcal{A}} \frac{\#\alpha}{f(\alpha)}, \end{align*} $$
as desired. Let now 
 $\varepsilon>0$
 be sufficiently small and
$\varepsilon>0$
 be sufficiently small and 
 $\gamma =w_1w_2w_3\ldots \in \mathcal {T}(\mathcal {D})$
 be such that
$\gamma =w_1w_2w_3\ldots \in \mathcal {T}(\mathcal {D})$
 be such that 
 $\mathrm { dens}_f(\gamma )+\varepsilon> \sup _{\alpha \in \mathcal {T}(\mathcal {D})} \mathrm {dens}_f(\alpha )>\varepsilon $
. Let
$\mathrm { dens}_f(\gamma )+\varepsilon> \sup _{\alpha \in \mathcal {T}(\mathcal {D})} \mathrm {dens}_f(\alpha )>\varepsilon $
. Let 
 $m_n\uparrow \infty $
 be a sequence such that
$m_n\uparrow \infty $
 be a sequence such that 
 $$ \begin{align*}\mathrm{dens}_f(\gamma)=\lim_{n\rightarrow\infty} \frac{\#(w_1\ldots w_{m_n})}{f(w_1\ldots w_{m_n})}.\end{align*} $$
$$ \begin{align*}\mathrm{dens}_f(\gamma)=\lim_{n\rightarrow\infty} \frac{\#(w_1\ldots w_{m_n})}{f(w_1\ldots w_{m_n})}.\end{align*} $$
Since 
 $\#\mathcal {D}$
 is finite, there exists a word w which appears infinitely many times in the sequence of
$\#\mathcal {D}$
 is finite, there exists a word w which appears infinitely many times in the sequence of 
 $\gamma $
. We may assume such word is
$\gamma $
. We may assume such word is 
 $w_1$
 since the properties of f imply that
$w_1$
 since the properties of f imply that 
 $$ \begin{align*}\lim_{n\rightarrow\infty} \frac{\#(w_1\ldots w_{m_n})}{f(w_1\ldots w_{m_n})} = \lim_{n\rightarrow\infty} \frac{\#(w_i\ldots w_{m_n})}{f(w_i\ldots w_{m_n})} \end{align*} $$
$$ \begin{align*}\lim_{n\rightarrow\infty} \frac{\#(w_1\ldots w_{m_n})}{f(w_1\ldots w_{m_n})} = \lim_{n\rightarrow\infty} \frac{\#(w_i\ldots w_{m_n})}{f(w_i\ldots w_{m_n})} \end{align*} $$
for any i. For each n, we fix a path 
 $\gamma _{(w_{m_n},w)}$
 in
$\gamma _{(w_{m_n},w)}$
 in 
 $\mathcal {G}$
 from
$\mathcal {G}$
 from 
 $w_{m_n}$
 to w (such a path exists since w appears infinitely many times in
$w_{m_n}$
 to w (such a path exists since w appears infinitely many times in 
 $\gamma $
). By removing atoms, we may assume that
$\gamma $
). By removing atoms, we may assume that 
 $\gamma _{(w_{m_n},w)}$
 is simple, so that
$\gamma _{(w_{m_n},w)}$
 is simple, so that 
 $\gamma _{(w_{m_n},w)}$
 has path length at most the cardinality of
$\gamma _{(w_{m_n},w)}$
 has path length at most the cardinality of 
 $\mathcal {D}$
. Since
$\mathcal {D}$
. Since 
 $\mathcal {D}$
 is finite, we have just finitely many simple paths
$\mathcal {D}$
 is finite, we have just finitely many simple paths 
 $\gamma _{(w_{m_n},w)}$
, so
$\gamma _{(w_{m_n},w)}$
, so 
 $\#\gamma _{(w_{m_n},w)}=O(1)$
. Let
$\#\gamma _{(w_{m_n},w)}=O(1)$
. Let 
 $\gamma _{(w_{m_n},w)}^*$
 be the path
$\gamma _{(w_{m_n},w)}^*$
 be the path 
 $\gamma _{(w_{m_n},w)}$
 without the endpoints
$\gamma _{(w_{m_n},w)}$
 without the endpoints 
 $w_{m_n}$
 and w, so that
$w_{m_n}$
 and w, so that 
 $\gamma _{(w_{m_n},w)}=w_{m_n}\gamma _{(w_{m_n},w)}^*w_1$
. Hence,
$\gamma _{(w_{m_n},w)}=w_{m_n}\gamma _{(w_{m_n},w)}^*w_1$
. Hence, 
 $w_1\ldots w_{m_n}\gamma _{(w_{m_n},w)}^*$
 is a closed path. We can now use the properties of f to conclude
$w_1\ldots w_{m_n}\gamma _{(w_{m_n},w)}^*$
 is a closed path. We can now use the properties of f to conclude 
 $$ \begin{align*} \lim_{n\to\infty} \frac{\#(w_1\ldots w_{m_n}\gamma_{(w_{m_n},w)}^*)}{f(w_1\ldots w_{m_n}\gamma_{(w_{m_n},w)}^*)} = \lim_{n\to\infty} \frac{\#(w_1\ldots w_{m_n})}{f(w_1\ldots w_{m_n})}=\mathrm{dens}_f(\gamma). \end{align*} $$
$$ \begin{align*} \lim_{n\to\infty} \frac{\#(w_1\ldots w_{m_n}\gamma_{(w_{m_n},w)}^*)}{f(w_1\ldots w_{m_n}\gamma_{(w_{m_n},w)}^*)} = \lim_{n\to\infty} \frac{\#(w_1\ldots w_{m_n})}{f(w_1\ldots w_{m_n})}=\mathrm{dens}_f(\gamma). \end{align*} $$
However, 
 $\frac {\#(w_1\ldots w_{m_n}\gamma _{(w_{m_n},w)}^*)}{f(w_1\ldots w_{m_n}\gamma _{(w_{m_n},w)}^*)}\leq \max _{\alpha \in \mathcal {A}} \frac {\#\alpha }{f(\alpha )}$
. This concludes the proof.
$\frac {\#(w_1\ldots w_{m_n}\gamma _{(w_{m_n},w)}^*)}{f(w_1\ldots w_{m_n}\gamma _{(w_{m_n},w)}^*)}\leq \max _{\alpha \in \mathcal {A}} \frac {\#\alpha }{f(\alpha )}$
. This concludes the proof.

Figure 4 A visualization of the graph 
 $\mathcal {G}$
 for
$\mathcal {G}$
 for 
 $K=\{1,2,\beta \}$
 and
$K=\{1,2,\beta \}$
 and 
 $3<\beta \leq 4$
 via higher-dimensional embedding.
$3<\beta \leq 4$
 via higher-dimensional embedding.
 The proof of Theorem 13 does not work for an arbitrary compact 
 $1\in K \subset [1,\infty )$
 since it strongly relied on the fact that the graph
$1\in K \subset [1,\infty )$
 since it strongly relied on the fact that the graph 
 $\mathcal {G}$
 (or the domino set
$\mathcal {G}$
 (or the domino set 
 $\mathcal {D}$
) was finite, so that any closed path could be decomposed into atoms, and hence, in this case, the atoms control the value
$\mathcal {D}$
) was finite, so that any closed path could be decomposed into atoms, and hence, in this case, the atoms control the value 
 $\Delta _1(K)$
. Nevertheless, our proof describes an algorithm to find optimal K-admissible sphere packings in the case K is finite.
$\Delta _1(K)$
. Nevertheless, our proof describes an algorithm to find optimal K-admissible sphere packings in the case K is finite.
We now analyse the case when K has 3 elements.
Lemma 15. Let 
 $1<\alpha <\beta $
 and
$1<\alpha <\beta $
 and 
 $K=\{1,\alpha ,\beta \}$
 with
$K=\{1,\alpha ,\beta \}$
 with 
 $1<\alpha <\beta $
. If
$1<\alpha <\beta $
. If 
 $\beta \leq 2$
, the periodic packing
$\beta \leq 2$
, the periodic packing 
 $1111\ldots $
 has maximal density. If
$1111\ldots $
 has maximal density. If 
 $\beta>2$
, we have the following cases:
$\beta>2$
, we have the following cases:

Proof of Lemma 15.
 Let 
 $P\in \mathcal {P}_+(K)$
 be a K-admissible periodic packing and let
$P\in \mathcal {P}_+(K)$
 be a K-admissible periodic packing and let 
 $\gamma $
 be its sequence of distances. We have two cases: the one in which
$\gamma $
 be its sequence of distances. We have two cases: the one in which 
 $\beta $
 does not appear in
$\beta $
 does not appear in 
 $\gamma $
 and the second one in which
$\gamma $
 and the second one in which 
 $\beta $
 appears infinitely many times in
$\beta $
 appears infinitely many times in 
 $\gamma $
. In the second case, using the graph language, we break
$\gamma $
. In the second case, using the graph language, we break 
 $\gamma $
 into simple closed paths with endpoints
$\gamma $
 into simple closed paths with endpoints 
 $\beta $
, and we try maximize the density of such paths.
$\beta $
, and we try maximize the density of such paths.
Case 1. It is trivial.
 
Case 2. If 
 $\beta \leq 4$
, in the first case (
$\beta \leq 4$
, in the first case (
 $\beta $
 does not appear in
$\beta $
 does not appear in 
 $\gamma $
), we must have
$\gamma $
), we must have 
 $\gamma =222\ldots $
 whose density is 1/2. In the second case, the densest path is
$\gamma =222\ldots $
 whose density is 1/2. In the second case, the densest path is 
 $\beta 11$
, with density
$\beta 11$
, with density 
 $3/(2+\beta )$
 which gives the packing
$3/(2+\beta )$
 which gives the packing 
 $\beta 11\beta 11\ldots $
. Since
$\beta 11\beta 11\ldots $
. Since 
 $3/(2+\beta )\geq 1/2$
, the result follows. Now, if
$3/(2+\beta )\geq 1/2$
, the result follows. Now, if 
 $\beta>4$
, for the first case, there is no periodic packing, and for the second one, the densest path is again
$\beta>4$
, for the first case, there is no periodic packing, and for the second one, the densest path is again 
 $\beta 11$
.
$\beta 11$
.
 
Case 3. For the first case, 
 $1\alpha 1\alpha \ldots $
 is the densest possibility. For the second, the paths
$1\alpha 1\alpha \ldots $
 is the densest possibility. For the second, the paths 
 $\beta (1\alpha 1)^k$
 for
$\beta (1\alpha 1)^k$
 for 
 $k\rightarrow \infty $
 have increasing density, and they converge to
$k\rightarrow \infty $
 have increasing density, and they converge to 
 $1\alpha 1\alpha \ldots $
, which is the densest periodic packing in this case.
$1\alpha 1\alpha \ldots $
, which is the densest periodic packing in this case.
 
Case 4. In this case, the pairs 
 $(1,1)$
 and
$(1,1)$
 and 
 $(1,\alpha )$
 cannot be consecutive distances. For the first case, we case the sequence
$(1,\alpha )$
 cannot be consecutive distances. For the first case, we case the sequence 
 $\alpha \alpha \ldots $
 with density
$\alpha \alpha \ldots $
 with density 
 $1/\alpha $
. For the second case, we have the paths
$1/\alpha $
. For the second case, we have the paths 
 $\beta \alpha ^k$
 for
$\beta \alpha ^k$
 for 
 $k\geq 1$
 and
$k\geq 1$
 and 
 $\beta 1$
. The densest packing is
$\beta 1$
. The densest packing is 
 $\alpha \alpha \ldots $
. If
$\alpha \alpha \ldots $
. If 
 $2\alpha =\beta +1$
, then
$2\alpha =\beta +1$
, then 
 $1\beta 1\beta \ldots $
 has also maximal density.
$1\beta 1\beta \ldots $
 has also maximal density.
 
Case 5. By the same arguments as in Case 4, we deduce that the densest packing is 
 $1\beta 1\beta \ldots $
.
$1\beta 1\beta \ldots $
.
 
Case 6. We have to consider just the second case. Since the pairs 
 $(1,1)$
,
$(1,1)$
, 
 $(1,\alpha )$
 and
$(1,\alpha )$
 and 
 $(\alpha ,\alpha )$
 cannot be consecutive distances, the densest path is
$(\alpha ,\alpha )$
 cannot be consecutive distances, the densest path is 
 $\beta 1$
, which provides the packing
$\beta 1$
, which provides the packing 
 $\beta 1\beta 1\ldots $
.
$\beta 1\beta 1\ldots $
.
5 Proof of Theorem 6
 Let 
 $K'=\{\alpha _1,\ldots ,\alpha _N\}$
 the set of limit points of K. We can then write K as follows:
$K'=\{\alpha _1,\ldots ,\alpha _N\}$
 the set of limit points of K. We can then write K as follows: 
 $$ \begin{align*} K=\widehat{K}\cup\displaystyle\bigcup_{j=1}^{N} \left\{\alpha_j+\lambda_k^j : k\geq1\right\}, \end{align*} $$
$$ \begin{align*} K=\widehat{K}\cup\displaystyle\bigcup_{j=1}^{N} \left\{\alpha_j+\lambda_k^j : k\geq1\right\}, \end{align*} $$
where 
 $\widehat {K}:=\left \{\alpha _1,\ldots ,\alpha _N,\beta _1,\ldots ,\beta _M\right \}$
, with
$\widehat {K}:=\left \{\alpha _1,\ldots ,\alpha _N,\beta _1,\ldots ,\beta _M\right \}$
, with 
 $1\in \widehat {K}$
, and such that
$1\in \widehat {K}$
, and such that 
- 
(i)  $\alpha _i+\alpha _j\not \in \left \{\alpha _r : 1\leq r\leq N\right \};$ $\alpha _i+\alpha _j\not \in \left \{\alpha _r : 1\leq r\leq N\right \};$
- 
(ii)  $0<\lambda _k^j<\frac {\delta }{2}$
 for any $0<\lambda _k^j<\frac {\delta }{2}$
 for any $j,k$
, where $j,k$
, where $\delta :=\displaystyle \min _{1\leq i<j\leq N} \left |\alpha _i-\alpha _j\right |$
; $\delta :=\displaystyle \min _{1\leq i<j\leq N} \left |\alpha _i-\alpha _j\right |$
;
- 
(iii) For any fixed j, we have  $\lambda _k^j\downarrow 0$
 when $\lambda _k^j\downarrow 0$
 when $k\rightarrow \infty $
; $k\rightarrow \infty $
;
- 
(iv)  $\beta _M=\max {K}$
. $\beta _M=\max {K}$
.
We will show that under such conditions, for every packing  , one can construct another one
, one can construct another one 
 $\widetilde P$
 with
$\widetilde P$
 with 
 $\mathrm { dens}^+(\widetilde P)\geq \mathrm {dens}^+(P)$
 and such that the set of distances of
$\mathrm { dens}^+(\widetilde P)\geq \mathrm {dens}^+(P)$
 and such that the set of distances of 
 $\widetilde P$
 lies in a finite set
$\widetilde P$
 lies in a finite set 
 $\widetilde K \subset K$
. Thus, by Lemma 9 and Corollary 14, there exists a K-admissible periodic sphere packing of maximal density.
$\widetilde K \subset K$
. Thus, by Lemma 9 and Corollary 14, there exists a K-admissible periodic sphere packing of maximal density.
 For 
 $\gamma \in K$
 and
$\gamma \in K$
 and 
 $1\leq i,r\leq N$
, we set
$1\leq i,r\leq N$
, we set 
 $$ \begin{align*} J\left(\gamma,\alpha_i,r\right) :=\left\{s\geq 1 : \gamma+\alpha_i+\lambda_s^r\in K\cup\left(\beta_M,\infty\right)\right\} \ \text{ and } \ M\left(\gamma,\alpha_i,r\right) :=\displaystyle\sup{J\left(\gamma,\alpha_i,r\right)}. \end{align*} $$
$$ \begin{align*} J\left(\gamma,\alpha_i,r\right) :=\left\{s\geq 1 : \gamma+\alpha_i+\lambda_s^r\in K\cup\left(\beta_M,\infty\right)\right\} \ \text{ and } \ M\left(\gamma,\alpha_i,r\right) :=\displaystyle\sup{J\left(\gamma,\alpha_i,r\right)}. \end{align*} $$
Observe that, for fixed 
 $i,j$
, we may have
$i,j$
, we may have 
 $\alpha _j+\lambda _k^j+\alpha _i=\alpha _w$
 for some w. In this case, the index k with such property is unique because of (ii). Therefore, we may write
$\alpha _j+\lambda _k^j+\alpha _i=\alpha _w$
 for some w. In this case, the index k with such property is unique because of (ii). Therefore, we may write 
 $k(j,i)$
 to denote precisely this index k, whenever it exists. Observe also that if
$k(j,i)$
 to denote precisely this index k, whenever it exists. Observe also that if 
 $M\left (\gamma ,\alpha _i,r\right )=\infty $
, then
$M\left (\gamma ,\alpha _i,r\right )=\infty $
, then 
 $\gamma +\alpha _i$
 is an accumulation point and either
$\gamma +\alpha _i$
 is an accumulation point and either 
 $\gamma +\alpha _i=\alpha _w$
 for some w or
$\gamma +\alpha _i=\alpha _w$
 for some w or 
 $\gamma +\alpha _i\geq \beta _M$
. In particular, if
$\gamma +\alpha _i\geq \beta _M$
. In particular, if 
 $k\neq k(i,j)$
, then
$k\neq k(i,j)$
, then 
 $M\left (\alpha _j+\lambda _k^j,\alpha _i,r\right )=\infty $
 if and only if
$M\left (\alpha _j+\lambda _k^j,\alpha _i,r\right )=\infty $
 if and only if 
 $\alpha _j+\lambda _k^j+\alpha _i\geq \beta _M$
. Our first step is to ask how large
$\alpha _j+\lambda _k^j+\alpha _i\geq \beta _M$
. Our first step is to ask how large 
 $M(\gamma ,\alpha _i,r)$
 can be when it is finite.
$M(\gamma ,\alpha _i,r)$
 can be when it is finite.
 
Step 1. We claim that there is 
 $C>0$
 such that for all
$C>0$
 such that for all 
 $1\leq i,j,r\leq N$
 and
$1\leq i,j,r\leq N$
 and 
 $k\geq 1$
, with
$k\geq 1$
, with 
 $k\neq k(i,j)$
, we have
$k\neq k(i,j)$
, we have 
 $M\left (\alpha _j+\lambda _k^j,\alpha _i,r\right )\leq C$
 whenever it is finite. Indeed, assume by contradiction this does not happen. Then, for each
$M\left (\alpha _j+\lambda _k^j,\alpha _i,r\right )\leq C$
 whenever it is finite. Indeed, assume by contradiction this does not happen. Then, for each 
 $C\in \mathbb {Z}_+$
 there is
$C\in \mathbb {Z}_+$
 there is 
 $s=s(C)\geq C$
,
$s=s(C)\geq C$
, 
 $k\geq 1$
 (
$k\geq 1$
 (
 $k\neq k(i,j)$
) and
$k\neq k(i,j)$
) and 
 $1\leq i,j,r\leq N$
 such that
$1\leq i,j,r\leq N$
 such that 
 $\alpha _j+\lambda ^j_k+\alpha _i+\lambda ^r_s \in K\cup (\beta _M,\infty )$
 but
$\alpha _j+\lambda ^j_k+\alpha _i+\lambda ^r_s \in K\cup (\beta _M,\infty )$
 but 
 $M\left (\alpha _j+\lambda _k^j,\alpha _i,r\right )<\infty $
. Thus, as
$M\left (\alpha _j+\lambda _k^j,\alpha _i,r\right )<\infty $
. Thus, as 
 $s\to \infty $
, some triple
$s\to \infty $
, some triple 
 $(i,j,r)$
 is repeated infinitely often, and we choose such triple. If
$(i,j,r)$
 is repeated infinitely often, and we choose such triple. If 
 $k=k(C)=O(1)$
, then for some
$k=k(C)=O(1)$
, then for some 
 $k_0\neq k(i,j)$
, we have that
$k_0\neq k(i,j)$
, we have that 
 $\alpha _j+\lambda ^j_{k_0}+\alpha _i \in K\cup (\beta _M,\infty )$
 is an accumulation point and
$\alpha _j+\lambda ^j_{k_0}+\alpha _i \in K\cup (\beta _M,\infty )$
 is an accumulation point and 
 $M\left (\alpha _j+\lambda _{k_0}^j,\alpha _i,r\right )<\infty $
. Since
$M\left (\alpha _j+\lambda _{k_0}^j,\alpha _i,r\right )<\infty $
. Since 
 $k_0\neq k(i,j)$
, we have that
$k_0\neq k(i,j)$
, we have that 
 $\alpha _j+\lambda ^j_{k_0}+\alpha _i \geq \beta _M$
, but this is absurd since we would have that
$\alpha _j+\lambda ^j_{k_0}+\alpha _i \geq \beta _M$
, but this is absurd since we would have that 
 $M\left (\alpha _j+\lambda _{k_0}^j,\alpha _i,r\right )=\infty $
, which is not the case. Thus,
$M\left (\alpha _j+\lambda _{k_0}^j,\alpha _i,r\right )=\infty $
, which is not the case. Thus, 
 $k=k(C)$
 is unbounded, and so
$k=k(C)$
 is unbounded, and so 
 $\alpha _j+\alpha _i \in K\cup (\beta _M,\infty )$
 is an accumulation point. Condition (i) implies that
$\alpha _j+\alpha _i \in K\cup (\beta _M,\infty )$
 is an accumulation point. Condition (i) implies that 
 $\alpha _j+\alpha _i \geq \beta _M$
, and again we reach a contradiction since this implies that
$\alpha _j+\alpha _i \geq \beta _M$
, and again we reach a contradiction since this implies that 
 $M\left (\alpha _j+\lambda _{k}^j,\alpha _i,r\right )=\infty $
 for all k.
$M\left (\alpha _j+\lambda _{k}^j,\alpha _i,r\right )=\infty $
 for all k.
 
Step 2. Let 
 $C>0$
 be the constant from the previous step. Enlarge C if necessary so that we also have
$C>0$
 be the constant from the previous step. Enlarge C if necessary so that we also have 
 $$ \begin{align*}C\geq M(\gamma,\alpha_i,r) \end{align*} $$
$$ \begin{align*}C\geq M(\gamma,\alpha_i,r) \end{align*} $$
for all 
 $\gamma \in \widehat K$
 and
$\gamma \in \widehat K$
 and 
 $1\leq i,r\leq N$
 such that
$1\leq i,r\leq N$
 such that 
 $M(\gamma ,\alpha _i,r)<\infty $
. Define the set
$M(\gamma ,\alpha _i,r)<\infty $
. Define the set 
 $\widetilde {K}$
 by
$\widetilde {K}$
 by 
 $$ \begin{align*} \widetilde{K}:=\widehat{K}\cup\displaystyle\bigcup_{j=1}^{N} \left\{\alpha_j+\lambda_k^j; \text{ } 1\leq k\leq C\right\} \subset K. \end{align*} $$
$$ \begin{align*} \widetilde{K}:=\widehat{K}\cup\displaystyle\bigcup_{j=1}^{N} \left\{\alpha_j+\lambda_k^j; \text{ } 1\leq k\leq C\right\} \subset K. \end{align*} $$
Let  be a packing where
 be a packing where 
 $d_i\in K$
. By an inductive argument, we will replace
$d_i\in K$
. By an inductive argument, we will replace 
 $d_i$
 by
$d_i$
 by 
 $\widetilde {d_i}\leq d_i$
, with
$\widetilde {d_i}\leq d_i$
, with 
 $\widetilde {d_i}\in \widetilde {K}$
, in such a way that
$\widetilde {d_i}\in \widetilde {K}$
, in such a way that 
 $\widetilde P=\widetilde d_1 \widetilde d_2 \ldots \in \mathcal {P}_+(\widetilde K) \subset \mathcal {P}_+(K)$
. This clearly implies that
$\widetilde P=\widetilde d_1 \widetilde d_2 \ldots \in \mathcal {P}_+(\widetilde K) \subset \mathcal {P}_+(K)$
. This clearly implies that 
 $\mathrm {dens}^+(\widetilde P)\geq \mathrm {dens}^+(P)$
.
$\mathrm {dens}^+(\widetilde P)\geq \mathrm {dens}^+(P)$
.
 We start with the base case. If 
 $d_1\in \widetilde {K}$
, there is nothing to prove. Assume we have
$d_1\in \widetilde {K}$
, there is nothing to prove. Assume we have 
 $d_1\not \in \widetilde {K}$
; hence,
$d_1\not \in \widetilde {K}$
; hence, 
 $d_1\not \in \widehat {K}$
. Therefore, we have
$d_1\not \in \widehat {K}$
. Therefore, we have 
 $d_1=\alpha _i+\lambda _s^i$
 for some
$d_1=\alpha _i+\lambda _s^i$
 for some 
 $1\leq i\leq N$
 and
$1\leq i\leq N$
 and 
 $s>C$
. We claim that
$s>C$
. We claim that 
 $M(d_2,\alpha _i,i)=\infty $
. Indeed, if it were finite, then
$M(d_2,\alpha _i,i)=\infty $
. Indeed, if it were finite, then 
 $M(d_2,\alpha _i,i)\leq C$
, and hence,
$M(d_2,\alpha _i,i)\leq C$
, and hence, 
 $s\leq C$
, a contradiction. Therefore,
$s\leq C$
, a contradiction. Therefore, 
 $M(d_2,\alpha _i,i)=\infty $
; hence,
$M(d_2,\alpha _i,i)=\infty $
; hence, 
 $d_2+\alpha _i+\lambda _t^i\in K\cup \left (\beta _M,\infty \right )$
 for infinitely many indices t. Therefore, we must have
$d_2+\alpha _i+\lambda _t^i\in K\cup \left (\beta _M,\infty \right )$
 for infinitely many indices t. Therefore, we must have 
 $d_2+\alpha _i\in K\cup \left (\beta _M,\infty \right )$
. We now claim that we can replace
$d_2+\alpha _i\in K\cup \left (\beta _M,\infty \right )$
. We now claim that we can replace 
 $d_1=\alpha _i+\lambda _s^i$
 by
$d_1=\alpha _i+\lambda _s^i$
 by 
 $\widetilde {d_1}:=\alpha _i$
. In other words, we must verify that
$\widetilde {d_1}:=\alpha _i$
. In other words, we must verify that 
 $\widetilde {d_1}$
 is compatible with
$\widetilde {d_1}$
 is compatible with 
 $d_2,\ldots ,d_{1+\left \lceil \beta _M\right \rceil }$
. This is the reason why we considered the more general sets
$d_2,\ldots ,d_{1+\left \lceil \beta _M\right \rceil }$
. This is the reason why we considered the more general sets 
 $J(\gamma ,\alpha _i,r)$
 with
$J(\gamma ,\alpha _i,r)$
 with 
 $r\neq i$
. Since
$r\neq i$
. Since 
 $d_2+\alpha _i\in K\cup \left (\beta _M,\infty \right )$
, it follows that
$d_2+\alpha _i\in K\cup \left (\beta _M,\infty \right )$
, it follows that 
 $\widetilde {d_1}$
 is compatible with
$\widetilde {d_1}$
 is compatible with 
 $d_2$
. If
$d_2$
. If 
 $\alpha _i+d_2\geq \beta _M$
, then
$\alpha _i+d_2\geq \beta _M$
, then 
 $\alpha _i+d_2+\ldots +d_w\geq \beta _M$
 for any
$\alpha _i+d_2+\ldots +d_w\geq \beta _M$
 for any 
 $w\geq 3$
; hence,
$w\geq 3$
; hence, 
 $\widetilde {d_1}$
 satisfies all the required compatibility conditions. Assume we have
$\widetilde {d_1}$
 satisfies all the required compatibility conditions. Assume we have 
 $\alpha _i+d_2<\beta _M$
. Since
$\alpha _i+d_2<\beta _M$
. Since 
 $\alpha _i+d_2+\lambda _t^i\in K\cup \left (\beta _M,\infty \right )$
 for infinitely many t, it must be the case in which
$\alpha _i+d_2+\lambda _t^i\in K\cup \left (\beta _M,\infty \right )$
 for infinitely many t, it must be the case in which 
 $\alpha _i+d_2=\alpha _r$
 for some r. We claim that
$\alpha _i+d_2=\alpha _r$
 for some r. We claim that 
 $M(d_3,\alpha _r,i)=\infty $
. Indeed, if it were
$M(d_3,\alpha _r,i)=\infty $
. Indeed, if it were 
 $<\infty $
, then
$<\infty $
, then 
 $M(d_3,\alpha _r,i)\leq C$
, and, hence
$M(d_3,\alpha _r,i)\leq C$
, and, hence 
 $s\leq C$
, a contradiction. Therefore, we have
$s\leq C$
, a contradiction. Therefore, we have 
 $\alpha _r+d_3+\lambda _t^i\in K\cup \left (\beta _M,\infty \right )$
 for infinitely many t, and hence,
$\alpha _r+d_3+\lambda _t^i\in K\cup \left (\beta _M,\infty \right )$
 for infinitely many t, and hence, 
 $\alpha _i+d_2+d_3=\alpha _r+d_3\in K\cup \left (\beta _M,\infty \right )$
 which proves
$\alpha _i+d_2+d_3=\alpha _r+d_3\in K\cup \left (\beta _M,\infty \right )$
 which proves 
 $\widetilde {d_1}$
 is also compatible with
$\widetilde {d_1}$
 is also compatible with 
 $d_3$
. If
$d_3$
. If 
 $\alpha _r+d_3\geq \beta _M$
, then we are done. Otherwise, we apply the same procedure to show that
$\alpha _r+d_3\geq \beta _M$
, then we are done. Otherwise, we apply the same procedure to show that 
 $\widetilde {d_1}$
 is compatible with
$\widetilde {d_1}$
 is compatible with 
 $d_4$
, and so on. By repeating this process at most
$d_4$
, and so on. By repeating this process at most 
 $\left \lceil \beta _M\right \rceil $
 times, we conclude that, indeed, it is possible to replace
$\left \lceil \beta _M\right \rceil $
 times, we conclude that, indeed, it is possible to replace 
 $d_1$
 by
$d_1$
 by 
 $\widetilde {d_1}=\alpha _i$
.
$\widetilde {d_1}=\alpha _i$
.
 Assume that we have replaced 
 $d_1,\ldots ,d_n$
 by
$d_1,\ldots ,d_n$
 by 
 $\widetilde {d_1},\ldots ,\widetilde {d_n}\in \widetilde {K}$
. If
$\widetilde {d_1},\ldots ,\widetilde {d_n}\in \widetilde {K}$
. If 
 $d_{n+1}\in \widetilde {K}$
, then we are done. If not, we repeat the same procedure as for
$d_{n+1}\in \widetilde {K}$
, then we are done. If not, we repeat the same procedure as for 
 $d_1$
, but now for both the right- and the left-hand side of
$d_1$
, but now for both the right- and the left-hand side of 
 $d_{n+1}$
. This completes the induction argument. Observe that
$d_{n+1}$
. This completes the induction argument. Observe that 
 $d_n\neq \widetilde {d_n}$
 precisely when
$d_n\neq \widetilde {d_n}$
 precisely when 
 $d_n=\alpha _i+\lambda _k^i$
, for
$d_n=\alpha _i+\lambda _k^i$
, for 
 $k>C$
, and in this case, we took
$k>C$
, and in this case, we took 
 $\widetilde {d_n}=\alpha _i<d_n$
. This process does not reduce the density of the packing.
$\widetilde {d_n}=\alpha _i<d_n$
. This process does not reduce the density of the packing.
Remark 1. The main idea of this proof was to take a packing of maximal density and reduce to the finite case by replacing the distances close enough to an accumulation point by this point. Such technique relies a lot on the structure of the set K (existence of left or right limit points and the arithmetic structure of 
 $K'$
). As the complexity of K grows, such technique becomes very hard to implement. Nevertheless, the above proof gives an algorithm to find the best packing in such a case.
$K'$
). As the complexity of K grows, such technique becomes very hard to implement. Nevertheless, the above proof gives an algorithm to find the best packing in such a case.
6 Constructions via modular forms
 In this section, we present some constructions via modular forms that generalize the ones in [Reference Cohn and Gonçalves9, Reference Cohn, Kumar, Miller, Radchenko and Viazovska10, Reference Viazovska27] to all dimensions divisible by 
 $4$
.
$4$
.
 Throughout the rest of the paper, we will always use z for a variable in the upper-half plane 
 $\mathbb {H}=\{x+it: x\in \mathbb {R}, t>0\}$
. We will use the convention
$\mathbb {H}=\{x+it: x\in \mathbb {R}, t>0\}$
. We will use the convention 
 $q=e^{2\pi i z}$
 and
$q=e^{2\pi i z}$
 and 
 $r=e^{\pi i z}$
 for
$r=e^{\pi i z}$
 for 
 $z\in \mathbb {H}$
. We will be handling holomorphic modular forms
$z\in \mathbb {H}$
. We will be handling holomorphic modular forms 
 $f:\mathbb {H}\to \mathbb {C}$
 over the principal congruence subgroups
$f:\mathbb {H}\to \mathbb {C}$
 over the principal congruence subgroups 
 $$ \begin{align*}\Gamma(N) = \{\gamma\in \mathrm{SL}_2(\mathbb{Z}) : \gamma \equiv \text{Id} \ (\text{mod } N) \} \end{align*} $$
$$ \begin{align*}\Gamma(N) = \{\gamma\in \mathrm{SL}_2(\mathbb{Z}) : \gamma \equiv \text{Id} \ (\text{mod } N) \} \end{align*} $$
(note 
 $\Gamma (1)=\mathrm {SL}_2(\mathbb {Z})$
). A holomorphic modular form of weight k for a subgroup
$\Gamma (1)=\mathrm {SL}_2(\mathbb {Z})$
). A holomorphic modular form of weight k for a subgroup 
 $\Gamma <\Gamma (1)$
 is a holomorphic function
$\Gamma <\Gamma (1)$
 is a holomorphic function 
 $f: \mathbb {H} \to \mathbb {C}$
 invariant by the slash operation
$f: \mathbb {H} \to \mathbb {C}$
 invariant by the slash operation 
 $$ \begin{align*}f|_k\gamma(z) := (cz+d)^{-k}f\bigg(\frac{az+b}{cz+d}\bigg)=f(z), \ \ \text{ for all } z\in \mathbb{H} \text{ and } \gamma=\left(\begin{matrix} a & b\\ c & d\end{matrix}\right)\in \Gamma, \end{align*} $$
$$ \begin{align*}f|_k\gamma(z) := (cz+d)^{-k}f\bigg(\frac{az+b}{cz+d}\bigg)=f(z), \ \ \text{ for all } z\in \mathbb{H} \text{ and } \gamma=\left(\begin{matrix} a & b\\ c & d\end{matrix}\right)\in \Gamma, \end{align*} $$
and such that
 $$ \begin{align*}f|_k\gamma(z) = O(1) \ \ \text{ as } \mathrm{Im}\, z\to\infty. \end{align*} $$
$$ \begin{align*}f|_k\gamma(z) = O(1) \ \ \text{ as } \mathrm{Im}\, z\to\infty. \end{align*} $$
We denote by 
 $M_k(\Gamma )$
 for the space of holomorphic modular forms
$M_k(\Gamma )$
 for the space of holomorphic modular forms 
 $f:\mathbb {H}\to \mathbb {C}$
 of weight k for
$f:\mathbb {H}\to \mathbb {C}$
 of weight k for 
 $\Gamma $
. We simply write
$\Gamma $
. We simply write 
 $M_k$
 for
$M_k$
 for 
 $M_k(\text {SL}_2(\mathbb {Z}))$
. We let
$M_k(\text {SL}_2(\mathbb {Z}))$
. We let 
 $$ \begin{align*}T = \left( \begin{matrix} 1 & 1\\ 0 & 1\end{matrix}\right) \ \ \text{and} \ \ S = \left( \begin{matrix} 0 & -1\\ 1 & 0\end{matrix}\right). \end{align*} $$
$$ \begin{align*}T = \left( \begin{matrix} 1 & 1\\ 0 & 1\end{matrix}\right) \ \ \text{and} \ \ S = \left( \begin{matrix} 0 & -1\\ 1 & 0\end{matrix}\right). \end{align*} $$
If 
 $T^2 \in \Gamma $
, then any
$T^2 \in \Gamma $
, then any 
 $f\in M_k(\Gamma )$
 has a Fourier r-series of the form
$f\in M_k(\Gamma )$
 has a Fourier r-series of the form 
 $$ \begin{align*}f(z) = \sum_{n\geq 0} a_n r^n. \end{align*} $$
$$ \begin{align*}f(z) = \sum_{n\geq 0} a_n r^n. \end{align*} $$
The Eisenstein series
 $$ \begin{align*} E_4(z) = 1+240 \sum_{n\geq 1} \sigma_{3}(n)q^{n} \ \ \text{ and } \ \ E_6(z) =1- 504 \sum_{n\geq 1} \sigma_{5}(n)q^{n}, \end{align*} $$
$$ \begin{align*} E_4(z) = 1+240 \sum_{n\geq 1} \sigma_{3}(n)q^{n} \ \ \text{ and } \ \ E_6(z) =1- 504 \sum_{n\geq 1} \sigma_{5}(n)q^{n}, \end{align*} $$
are classical examples of modular forms in 
 $M_4$
 and
$M_4$
 and 
 $M_6$
, respectively. It is easy to see that
$M_6$
, respectively. It is easy to see that 
 $M_k$
 is trivial if k is odd or if
$M_k$
 is trivial if k is odd or if 
 $k<4$
 is nonzero, while
$k<4$
 is nonzero, while 
 $M_0$
 contains only constants. Indeed, a fundamental result is that
$M_0$
 contains only constants. Indeed, a fundamental result is that 
 $$ \begin{align*}\bigoplus_{j\in \mathbb{Z}} M_{j} = \mathbb{C}[E_4,E_6]. \end{align*} $$
$$ \begin{align*}\bigoplus_{j\in \mathbb{Z}} M_{j} = \mathbb{C}[E_4,E_6]. \end{align*} $$
We will also need Ramanujan’s cusp form of weight 
 $12$
$12$
 
 $$ \begin{align*}\Delta(z)= \frac{E_4^3(z)-E_6^2(z)}{1728} = q \prod_{n\geq 1}(1-q^n)^{24} \in M_{12}, \end{align*} $$
$$ \begin{align*}\Delta(z)= \frac{E_4^3(z)-E_6^2(z)}{1728} = q \prod_{n\geq 1}(1-q^n)^{24} \in M_{12}, \end{align*} $$
which clearly never vanishes for 
 $z\in \mathbb {H}$
. We will also need the Jacobi theta functions defined by
$z\in \mathbb {H}$
. We will also need the Jacobi theta functions defined by 
 $$ \begin{align*} \Theta_{00}(z) = \sum_{n \in \mathbb{Z}} r^{n^2}, \quad \Theta_{10}(z) = \sum_{n \in \mathbb{Z}} r^{ (n+1/2)^2}\quad \text{and} \quad \Theta_{01}(z) = \sum_{n \in \mathbb{Z}} (-1)^n r^{n^2}. \end{align*} $$
$$ \begin{align*} \Theta_{00}(z) = \sum_{n \in \mathbb{Z}} r^{n^2}, \quad \Theta_{10}(z) = \sum_{n \in \mathbb{Z}} r^{ (n+1/2)^2}\quad \text{and} \quad \Theta_{01}(z) = \sum_{n \in \mathbb{Z}} (-1)^n r^{n^2}. \end{align*} $$
We define their fourth powers by
 $$ \begin{align*}U=\Theta_{00}^4, \quad V=\Theta_{10}^4\quad \text{and} \quad W=\Theta_{01}^4. \end{align*} $$
$$ \begin{align*}U=\Theta_{00}^4, \quad V=\Theta_{10}^4\quad \text{and} \quad W=\Theta_{01}^4. \end{align*} $$
These are modular forms of weight 
 $2$
 that satisfy the Jacobi identity
$2$
 that satisfy the Jacobi identity 
 $$ \begin{align*}U=V+W \end{align*} $$
$$ \begin{align*}U=V+W \end{align*} $$
and the transformation laws
 $$ \begin{align*} & U|_2T = W, \ \ V|_2T = -V, \ \ W|_2T = U,\\ & U|_2S = -U, \ \ V|_2S = -W, \ \ W|_2S = -V. \end{align*} $$
$$ \begin{align*} & U|_2T = W, \ \ V|_2T = -V, \ \ W|_2T = U,\\ & U|_2S = -U, \ \ V|_2S = -W, \ \ W|_2S = -V. \end{align*} $$
The functions 
 $U,V,W$
 are examples of modular forms of weight
$U,V,W$
 are examples of modular forms of weight 
 $2$
 for
$2$
 for 
 $\Gamma (2)$
. Another fundamental result is that
$\Gamma (2)$
. Another fundamental result is that 
 $$ \begin{align*}\bigoplus_{j\in \mathbb{Z}} M_{j}(\Gamma(2)) = \mathbb{C}[U,V,W]. \end{align*} $$
$$ \begin{align*}\bigoplus_{j\in \mathbb{Z}} M_{j}(\Gamma(2)) = \mathbb{C}[U,V,W]. \end{align*} $$
Indeed, 
 $M_k(\Gamma (2))$
, for even
$M_k(\Gamma (2))$
, for even 
 $k\geq 2$
, coincides with the space of homogeneous polynomials of degree
$k\geq 2$
, coincides with the space of homogeneous polynomials of degree 
 $k/2$
 in any two of the
$k/2$
 in any two of the 
 $U,V,W$
. Finally, we let
$U,V,W$
. Finally, we let 
 $$ \begin{align*}E_2(z) = 1-24 \sum_{n\geq 1} \sigma_{1}(n)q^{n} \end{align*} $$
$$ \begin{align*}E_2(z) = 1-24 \sum_{n\geq 1} \sigma_{1}(n)q^{n} \end{align*} $$
be the quasimodular Eisenstein series of weight 
 $2$
. It satisfies the transformation rules
$2$
. It satisfies the transformation rules 
 $$ \begin{align*}E_2(z+1)=E_2(z) \text{ and } E_2(-1/z)z^{-2} = E_2(z) + \frac{6}{\pi i z}. \end{align*} $$
$$ \begin{align*}E_2(z+1)=E_2(z) \text{ and } E_2(-1/z)z^{-2} = E_2(z) + \frac{6}{\pi i z}. \end{align*} $$
We define the space of holomorphic quasimodular forms of weight k and depth p over a subgroup 
 $\Gamma $
 by
$\Gamma $
 by 
 $$ \begin{align} M_k^{\leq p}(\Gamma) = \bigoplus_{j=0}^p E_2^jM_{k-2j}(\Gamma). \end{align} $$
$$ \begin{align} M_k^{\leq p}(\Gamma) = \bigoplus_{j=0}^p E_2^jM_{k-2j}(\Gamma). \end{align} $$
We again omit 
 $\Gamma $
 when
$\Gamma $
 when 
 $\Gamma =\mathrm {SL}_2(\mathbb {Z})$
. For more details about all these modular forms, we recommend [Reference Zagier28].
$\Gamma =\mathrm {SL}_2(\mathbb {Z})$
. For more details about all these modular forms, we recommend [Reference Zagier28].
The following proposition is key to build admissible functions for the linear programming bounds we have developed.
Proposition 16. Let 
 $\Lambda \subset \mathbb {R}$
 be finite, with
$\Lambda \subset \mathbb {R}$
 be finite, with 
 $0\in \Lambda $
 and such that
$0\in \Lambda $
 and such that 
 $-1/\lambda \in \Lambda $
 whenever
$-1/\lambda \in \Lambda $
 whenever 
 $\lambda \in \Lambda $
 and
$\lambda \in \Lambda $
 and 
 $\lambda \neq 0$
. Let
$\lambda \neq 0$
. Let 
 $$ \begin{align*}p(s) = \sum_{\lambda\in \Lambda} a_\lambda e^{\pi i s \lambda} \end{align*} $$
$$ \begin{align*}p(s) = \sum_{\lambda\in \Lambda} a_\lambda e^{\pi i s \lambda} \end{align*} $$
be a trigonometric polynomial. Let 
 $\varepsilon \in \{-1,1\}$
,
$\varepsilon \in \{-1,1\}$
, 
 $d\geq 1$
 be an integer and
$d\geq 1$
 be an integer and 
 $f:\mathbb {H}\to \mathbb {C}$
 be analytic. Suppose that
$f:\mathbb {H}\to \mathbb {C}$
 be analytic. Suppose that 
- 
(a) We have  $$ \begin{align*}\int_0^1|f(it)|t^{-d/2} \mathrm{d} t <\infty; \end{align*} $$ $$ \begin{align*}\int_0^1|f(it)|t^{-d/2} \mathrm{d} t <\infty; \end{align*} $$
- 
(b) There is  $\delta>0$
 such that for any $\delta>0$
 such that for any $c>0$
, we have if $c>0$
, we have if $$ \begin{align*}f(z)=O_c(e^{\pi \delta \Im z}) \end{align*} $$ $$ \begin{align*}f(z)=O_c(e^{\pi \delta \Im z}) \end{align*} $$ $\Im z> c > |\Re z| $
; $\Im z> c > |\Re z| $
;
- 
(c) For all  $\lambda \in \Lambda \setminus \{0\}$
 and $\lambda \in \Lambda \setminus \{0\}$
 and $z\in \mathbb {H}$
, we have $z\in \mathbb {H}$
, we have $$ \begin{align*}a_\lambda f(z-\lambda) = -\varepsilon a_{-1/\lambda} (z/i)^{d/2-2}f(-1/z+1/\lambda); \end{align*} $$ $$ \begin{align*}a_\lambda f(z-\lambda) = -\varepsilon a_{-1/\lambda} (z/i)^{d/2-2}f(-1/z+1/\lambda); \end{align*} $$
- 
(d) For all  $z\in \mathbb {H}$
, we have $z\in \mathbb {H}$
, we have $$ \begin{align*}\sum_{\lambda \in \Lambda} a_\lambda f(z-\lambda) = \varepsilon a_0 (z/i)^{d/2-2} f(-1/z). \end{align*} $$ $$ \begin{align*}\sum_{\lambda \in \Lambda} a_\lambda f(z-\lambda) = \varepsilon a_0 (z/i)^{d/2-2} f(-1/z). \end{align*} $$
Then the function
 $$ \begin{align*}h(s) = p(s)\int_{0}^{\infty i} f(z)e^{\pi i z s} \mathrm{d} z \end{align*} $$
$$ \begin{align*}h(s) = p(s)\int_{0}^{\infty i} f(z)e^{\pi i z s} \mathrm{d} z \end{align*} $$
defines an analytic function for 
 $\Re s>0$
 that extends to an continuous function in
$\Re s>0$
 that extends to an continuous function in 
 $\Re s\geq 0$
, and satisfies the identity
$\Re s\geq 0$
, and satisfies the identity 
 $$ \begin{align} & h(s)\notag \\ & = \sum_{\substack{\lambda\in \Lambda \\ \lambda>0}} \int_\lambda^i a_\lambda f(z-\lambda)(e^{\pi i z s } +\varepsilon (i/z)^{d/2}e^{\pi i (-1/z) s})\mathrm{d} z + a_0\int_0^i f(z)(e^{\pi i z s } + \varepsilon(i/z)^{d/2}e^{\pi i (-1/z) s})\mathrm{d} z \end{align} $$
$$ \begin{align} & h(s)\notag \\ & = \sum_{\substack{\lambda\in \Lambda \\ \lambda>0}} \int_\lambda^i a_\lambda f(z-\lambda)(e^{\pi i z s } +\varepsilon (i/z)^{d/2}e^{\pi i (-1/z) s})\mathrm{d} z + a_0\int_0^i f(z)(e^{\pi i z s } + \varepsilon(i/z)^{d/2}e^{\pi i (-1/z) s})\mathrm{d} z \end{align} $$
if 
 $\Re s \geq 0$
. In particular, the function
$\Re s \geq 0$
. In particular, the function 
 $ F(x)=h(|x|^2) $
 belongs to
$ F(x)=h(|x|^2) $
 belongs to 
 $L^1(\mathbb {R}^d) \cap C^\infty (\mathbb {R}^d)$
 and
$L^1(\mathbb {R}^d) \cap C^\infty (\mathbb {R}^d)$
 and 
 $\widehat F(x) = \varepsilon F(x)$
.
$\widehat F(x) = \varepsilon F(x)$
.
Proof. Conditions (a) and (b) guarantee that 
 $h(s)$
 is analytic in the region
$h(s)$
 is analytic in the region 
 $\Re s>\delta $
. The analyticity of
$\Re s>\delta $
. The analyticity of 
 $h(s)$
 for
$h(s)$
 for 
 $0<\Re s <2\delta $
 and continuity of
$0<\Re s <2\delta $
 and continuity of 
 $h(s)$
 for
$h(s)$
 for 
 $\Re s=0$
 follows straightforwardly by identity (3) and condition (b). The fact that
$\Re s=0$
 follows straightforwardly by identity (3) and condition (b). The fact that 
 $F(x)$
 defines a radial
$F(x)$
 defines a radial 
 $L^1$
-function and
$L^1$
-function and 
 $\widehat F(x) = \varepsilon F(x)$
 follows by identity (3), condition (a) and the fact that
$\widehat F(x) = \varepsilon F(x)$
 follows by identity (3), condition (a) and the fact that 
 $x\in \mathbb {R}^d \to (e^{\pi i z |x|^2 } +\varepsilon (i/z)^{d/2}e^{\pi i (-1/z) |x|^2})$
 is a eigenfunction of the Fourier transform in
$x\in \mathbb {R}^d \to (e^{\pi i z |x|^2 } +\varepsilon (i/z)^{d/2}e^{\pi i (-1/z) |x|^2})$
 is a eigenfunction of the Fourier transform in 
 $\mathbb {R}^d$
 with eigenvalue
$\mathbb {R}^d$
 with eigenvalue 
 $\varepsilon $
. It remains to prove identity (3). By analytic continuation (and condition (b)), it is enough to prove it for
$\varepsilon $
. It remains to prove identity (3). By analytic continuation (and condition (b)), it is enough to prove it for 
 $\Re s> \delta $
. We then have
$\Re s> \delta $
. We then have 
 $$ \begin{align*} h(s) & = \sum_{\lambda \in \Lambda} a_\lambda \int_{\lambda}^{\lambda+\infty i} f(z-\lambda)e^{\pi i z s}\mathrm{d} z \\ & = \sum_{\substack{\lambda\in \Lambda \\ \lambda \neq 0}} a_\lambda \int_{\lambda}^{i} f(z-\lambda)e^{\pi i z s}\mathrm{d} z + \int_{i}^{\infty i} \big(\sum_{\lambda \in \Lambda} a_\lambda f(z-\lambda)\big) e^{\pi i z s} \mathrm{d} z + a_0\int_0^i f(z) e^{\pi i z s} \mathrm{d} z, \end{align*} $$
$$ \begin{align*} h(s) & = \sum_{\lambda \in \Lambda} a_\lambda \int_{\lambda}^{\lambda+\infty i} f(z-\lambda)e^{\pi i z s}\mathrm{d} z \\ & = \sum_{\substack{\lambda\in \Lambda \\ \lambda \neq 0}} a_\lambda \int_{\lambda}^{i} f(z-\lambda)e^{\pi i z s}\mathrm{d} z + \int_{i}^{\infty i} \big(\sum_{\lambda \in \Lambda} a_\lambda f(z-\lambda)\big) e^{\pi i z s} \mathrm{d} z + a_0\int_0^i f(z) e^{\pi i z s} \mathrm{d} z, \end{align*} $$
where in the second line above, we applied condition (b) to split the integral from 
 $\lambda $
 to i and i to
$\lambda $
 to i and i to 
 $\infty i$
. We obtain
$\infty i$
. We obtain 
 $$ \begin{align*} & h(s) \\ & = \sum_{\substack{\lambda\in \Lambda \\ \lambda> 0}} \bigg(a_\lambda \int_{\lambda}^{i} f(z-\lambda)e^{\pi i z s}\mathrm{d} z + a_{-1/\lambda} \int_{-1/\lambda}^{i} f(z+1/\lambda)e^{\pi i z s}\mathrm{d} z\bigg) \\ & \quad + a_0\int_{i}^{\infty i} \varepsilon (z/i)^{d/2-2} f(-1/z) e^{\pi i z s} \mathrm{d} z + a_0\int_0^i f(z) e^{\pi i z s} \mathrm{d} z \\ & = \sum_{\substack{\lambda\in \Lambda \\ \lambda > 0}} \int_{\lambda}^{i} \big(a_\lambda f(z-\lambda)e^{\pi i z s}\mathrm{d} z + a_{-1/\lambda} f(-1/z+1/\lambda)e^{\pi i (-1/z) s}z^{-2}\big)\mathrm{d} z \\ & \quad + a_0\int_{0}^{i}\big(\varepsilon (i/z)^{d/2} e^{\pi i (-1/z) s} + e^{\pi i z s}\big)f(z) \mathrm{d} z \\ & = \sum_{\substack{\lambda\in \Lambda \\ \lambda > 0}} \int_{\lambda}^{i} a_\lambda f(z-\lambda)\big(e^{\pi i z s} + \varepsilon(i/z)^{d/2}e^{\pi i (-1/z) s}\big)\mathrm{d} z + a_0\int_{0}^{i}\big(\varepsilon (i/z)^{d/2} e^{\pi i (-1/z) s} + e^{\pi i z s}\big)f(z) \mathrm{d} z, \end{align*} $$
$$ \begin{align*} & h(s) \\ & = \sum_{\substack{\lambda\in \Lambda \\ \lambda> 0}} \bigg(a_\lambda \int_{\lambda}^{i} f(z-\lambda)e^{\pi i z s}\mathrm{d} z + a_{-1/\lambda} \int_{-1/\lambda}^{i} f(z+1/\lambda)e^{\pi i z s}\mathrm{d} z\bigg) \\ & \quad + a_0\int_{i}^{\infty i} \varepsilon (z/i)^{d/2-2} f(-1/z) e^{\pi i z s} \mathrm{d} z + a_0\int_0^i f(z) e^{\pi i z s} \mathrm{d} z \\ & = \sum_{\substack{\lambda\in \Lambda \\ \lambda > 0}} \int_{\lambda}^{i} \big(a_\lambda f(z-\lambda)e^{\pi i z s}\mathrm{d} z + a_{-1/\lambda} f(-1/z+1/\lambda)e^{\pi i (-1/z) s}z^{-2}\big)\mathrm{d} z \\ & \quad + a_0\int_{0}^{i}\big(\varepsilon (i/z)^{d/2} e^{\pi i (-1/z) s} + e^{\pi i z s}\big)f(z) \mathrm{d} z \\ & = \sum_{\substack{\lambda\in \Lambda \\ \lambda > 0}} \int_{\lambda}^{i} a_\lambda f(z-\lambda)\big(e^{\pi i z s} + \varepsilon(i/z)^{d/2}e^{\pi i (-1/z) s}\big)\mathrm{d} z + a_0\int_{0}^{i}\big(\varepsilon (i/z)^{d/2} e^{\pi i (-1/z) s} + e^{\pi i z s}\big)f(z) \mathrm{d} z, \end{align*} $$
where in the first equality, we have applied condition (d) and that 
 $\Lambda $
 is closed by
$\Lambda $
 is closed by 
 $\lambda \to -1/\lambda $
, in the second equality, we used the change of variables
$\lambda \to -1/\lambda $
, in the second equality, we used the change of variables 
 $z\to -1/z$
, and in the last, we have applied condition (c).
$z\to -1/z$
, and in the last, we have applied condition (c).
Remark 2. It is straightforward to show that if we strengthen condition (a) to
 $$ \begin{align*}\int_0^1|f(it)|t^{-k} \mathrm{d} t <\infty; \end{align*} $$
$$ \begin{align*}\int_0^1|f(it)|t^{-k} \mathrm{d} t <\infty; \end{align*} $$
for all 
 $k>0$
, then
$k>0$
, then 
 $\partial _{x}^\alpha F \in L^1(\mathbb {R}^d)$
 for all multi-indexes
$\partial _{x}^\alpha F \in L^1(\mathbb {R}^d)$
 for all multi-indexes 
 $\alpha \in \mathbb {Z}_+^d$
, and since
$\alpha \in \mathbb {Z}_+^d$
, and since 
 $\widehat F=\varepsilon F$
, we conclude that F is of Schwartz class.
$\widehat F=\varepsilon F$
, we conclude that F is of Schwartz class.
 This integral transform was used by Viazovska et al. in [Reference Cohn, Kumar, Miller, Radchenko and Viazovska10, Reference Viazovska27] for 
 $p(s)=\sin ^2(\pi s/2)$
 to build the magic functions for the packing problem, and also by Radchenko and Viazovska in [Reference Radchenko and Viazovska23], for
$p(s)=\sin ^2(\pi s/2)$
 to build the magic functions for the packing problem, and also by Radchenko and Viazovska in [Reference Radchenko and Viazovska23], for 
 $p(s)=\sin (\pi s)$
, to construct Fourier interpolation formulae with
$p(s)=\sin (\pi s)$
, to construct Fourier interpolation formulae with 
 $\sqrt {n}$
-nodes. For our purposes, we wish to investigate the case when
$\sqrt {n}$
-nodes. For our purposes, we wish to investigate the case when 
 $p(s)=\sin ^2(\pi s/2)$
. The following lemmas generalize the constructions in [Reference Cohn, Kumar, Miller, Radchenko and Viazovska10, Reference Viazovska27] to all dimensions multiple of
$p(s)=\sin ^2(\pi s/2)$
. The following lemmas generalize the constructions in [Reference Cohn, Kumar, Miller, Radchenko and Viazovska10, Reference Viazovska27] to all dimensions multiple of 
 $4$
.
$4$
.
Remark 3. To make computations simpler we will, from now on, adopt the nonstandard notation that
 $$ \begin{align*}f_T(z) =f|_kT(z)=f(z+1) \text{ and } f_S(z)=f|_kS(z)=f(-1/z)z^{-k}, \end{align*} $$
$$ \begin{align*}f_T(z) =f|_kT(z)=f(z+1) \text{ and } f_S(z)=f|_kS(z)=f(-1/z)z^{-k}, \end{align*} $$
whenever it can be inferred from the context that f has weight k; that is, 
 $f\in M_k^{\leq p}(\Gamma )$
, for some
$f\in M_k^{\leq p}(\Gamma )$
, for some 
 $\Gamma $
, k and p.
$\Gamma $
, k and p.
Lemma 17 (
 $\Gamma (2)$
-construction).
$\Gamma (2)$
-construction).
 Let 
 $d\geq 4$
 be an integer divisible by
$d\geq 4$
 be an integer divisible by 
 $4$
. Let
$4$
. Let 
 $l\geq d/12$
 be an even integer and set
$l\geq d/12$
 be an even integer and set 
 $$ \begin{align*}k=2-d/2+6l \text{ and } \varepsilon=(-1)^{d/4+1}. \end{align*} $$
$$ \begin{align*}k=2-d/2+6l \text{ and } \varepsilon=(-1)^{d/4+1}. \end{align*} $$
Consider the following linear operatorFootnote 4
 $$ \begin{align*} L: \varphi \in M_k(\Gamma(2)) & \mapsto (\varphi_T+\varphi_S - \varphi,\, [r^0] \varphi_S,\, [r]\varphi_S, \ldots , \, [r^l]\varphi_S). \end{align*} $$
$$ \begin{align*} L: \varphi \in M_k(\Gamma(2)) & \mapsto (\varphi_T+\varphi_S - \varphi,\, [r^0] \varphi_S,\, [r]\varphi_S, \ldots , \, [r^l]\varphi_S). \end{align*} $$
Then any function in the vector space
 $$ \begin{align*}\mathcal{F}_{d,l}:=\frac{1}{\Delta^{l/2}}\ker(L) \end{align*} $$
$$ \begin{align*}\mathcal{F}_{d,l}:=\frac{1}{\Delta^{l/2}}\ker(L) \end{align*} $$
satisfies all conditions in Proposition 16 for 
 $\varepsilon $
, d and
$\varepsilon $
, d and 
 $p(s)=\sin ^2(\tfrac {\pi }{2} s)$
. In particular, for any
$p(s)=\sin ^2(\tfrac {\pi }{2} s)$
. In particular, for any 
 $f\in \mathcal {F}_{d,l}$
, we have an associated radial Schwartz function
$f\in \mathcal {F}_{d,l}$
, we have an associated radial Schwartz function 
 $F_f:\mathbb {R}^d\to \mathbb {C}$
 such that
$F_f:\mathbb {R}^d\to \mathbb {C}$
 such that 
 $\widehat {F_f}=\varepsilon F_f$
 and
$\widehat {F_f}=\varepsilon F_f$
 and 
 $$ \begin{align*}F_f(x) = \sin^2(\tfrac{\pi}{2} |x|^2)\int_0^{\infty i} f(z)e^{\pi i z |x|^2}\frac{\mathrm{d} z}{i} \end{align*} $$
$$ \begin{align*}F_f(x) = \sin^2(\tfrac{\pi}{2} |x|^2)\int_0^{\infty i} f(z)e^{\pi i z |x|^2}\frac{\mathrm{d} z}{i} \end{align*} $$
if 
 $|x|^2>l$
.
$|x|^2>l$
.
Proof. We will show that all conditions in Proposition 16 are satisfied for 
 $p(s)=\sin ^2(\tfrac {\pi }{2}s)$
. First, observe that if
$p(s)=\sin ^2(\tfrac {\pi }{2}s)$
. First, observe that if 
 $f\in \mathcal {F}_{d,l}$
, then condition (a) in Proposition 16 is equivalent to
$f\in \mathcal {F}_{d,l}$
, then condition (a) in Proposition 16 is equivalent to 
 $$ \begin{align*}\int_{i}^{\infty i} |f|_kS(z)||z|^{6l} |\mathrm{d} z| <\infty. \end{align*} $$
$$ \begin{align*}\int_{i}^{\infty i} |f|_kS(z)||z|^{6l} |\mathrm{d} z| <\infty. \end{align*} $$
This is true because 
 $f=\varphi /\Delta ^{l/2}$
 and
$f=\varphi /\Delta ^{l/2}$
 and 
 $$ \begin{align*}z^{6l}f|_kS =\frac{\varphi_S(z)}{\Delta^{l/2}(z) }, \end{align*} $$
$$ \begin{align*}z^{6l}f|_kS =\frac{\varphi_S(z)}{\Delta^{l/2}(z) }, \end{align*} $$
and so we conclude the Fourier expansion of 
 $z^{6l}f|_kS$
 starts at r. Condition (b) in Proposition 16 is trivial since f is
$z^{6l}f|_kS$
 starts at r. Condition (b) in Proposition 16 is trivial since f is 
 $2$
-periodic and has Fourier expansion starting at
$2$
-periodic and has Fourier expansion starting at 
 $r^{-l}$
. A simple computation shows that condition (d) implies (c) under the
$r^{-l}$
. A simple computation shows that condition (d) implies (c) under the 
 $2$
-periodicity of f. Using the modular properties of
$2$
-periodicity of f. Using the modular properties of 
 $\Delta (z)$
, we see that condition (d) in Proposition 16 is equivalent to
$\Delta (z)$
, we see that condition (d) in Proposition 16 is equivalent to 
 $$ \begin{align*}\varphi = \varphi_S+\varphi_T, \end{align*} $$
$$ \begin{align*}\varphi = \varphi_S+\varphi_T, \end{align*} $$
which holds true.
Remark 4. It is worth pointing out that by the fact that (see [Reference Eichler and Zagier13, Remark after Theorem 8.4] and [Reference Cohn, Kumar, Miller, Radchenko and Viazovska11, Equation (2.13)])
 $$ \begin{align*}M_k(\Gamma(2)) = M_k\oplus UM_{k-2}\oplus VM_{k-2}\oplus U^2M_{k-4}\oplus V^2M_{k-4}\oplus UVWM_{k-6}, \end{align*} $$
$$ \begin{align*}M_k(\Gamma(2)) = M_k\oplus UM_{k-2}\oplus VM_{k-2}\oplus U^2M_{k-4}\oplus V^2M_{k-4}\oplus UVWM_{k-6}, \end{align*} $$
routine computations show that the kernel of 
 $\varphi \mapsto \varphi _T+\varphi _S - \varphi $
 in
$\varphi \mapsto \varphi _T+\varphi _S - \varphi $
 in 
 $M_k(\Gamma (2))$
 coincides with
$M_k(\Gamma (2))$
 coincides with 
 $$ \begin{align*} (U-V)M_{k-2} \oplus (U^2 - V^2)M_{k-4}, \end{align*} $$
$$ \begin{align*} (U-V)M_{k-2} \oplus (U^2 - V^2)M_{k-4}, \end{align*} $$
which has dimension 
 $ \lceil k/6 \rceil $
 for
$ \lceil k/6 \rceil $
 for 
 $k\geq 6$
, but is trivial otherwise. One can also show that
$k\geq 6$
, but is trivial otherwise. One can also show that 
 $$ \begin{align*}\dim \mathcal{F}_{d,l}=\bigg\lceil \frac{k}{6} \bigg\rceil-\frac{l}{2}=\frac{l}{2} -\bigg \lfloor \frac{d-4}{12} \bigg\rfloor. \end{align*} $$
$$ \begin{align*}\dim \mathcal{F}_{d,l}=\bigg\lceil \frac{k}{6} \bigg\rceil-\frac{l}{2}=\frac{l}{2} -\bigg \lfloor \frac{d-4}{12} \bigg\rfloor. \end{align*} $$
Lemma 18 (
 $\Gamma (1)$
-construction).
$\Gamma (1)$
-construction).
 Let 
 $d\geq 4$
 be an integer divisible by
$d\geq 4$
 be an integer divisible by 
 $4$
. Let
$4$
. Let 
 $l\geq d/12$
 be an even integer and set
$l\geq d/12$
 be an even integer and set 
 $$ \begin{align*}k=2-d/2+6l \quad \text{ and } \quad \varepsilon=(-1)^{d/4}. \end{align*} $$
$$ \begin{align*}k=2-d/2+6l \quad \text{ and } \quad \varepsilon=(-1)^{d/4}. \end{align*} $$
Consider the following linear operator:
 $$ \begin{align*} L: \psi \in M_{k+2}^{\leq 2} & \mapsto ([q^0] \psi,\, [q^{1}]\psi, \ldots , \, [q^{l/2}]\psi). \end{align*} $$
$$ \begin{align*} L: \psi \in M_{k+2}^{\leq 2} & \mapsto ([q^0] \psi,\, [q^{1}]\psi, \ldots , \, [q^{l/2}]\psi). \end{align*} $$
Then any function in the vector space
 $$ \begin{align*}\mathcal{G}_{d,l}:=\frac1{\Delta^{l/2}}(z^2\ker(L)_S), \end{align*} $$
$$ \begin{align*}\mathcal{G}_{d,l}:=\frac1{\Delta^{l/2}}(z^2\ker(L)_S), \end{align*} $$
where 
 $z^2\ker (L)_S:=\{z\mapsto z^2 \psi |_{k+2}S(z): \psi \in \ker (L)\}$
, satisfies all conditions in Proposition 16 for
$z^2\ker (L)_S:=\{z\mapsto z^2 \psi |_{k+2}S(z): \psi \in \ker (L)\}$
, satisfies all conditions in Proposition 16 for 
 $\varepsilon $
, d and
$\varepsilon $
, d and 
 $p(s)=\sin ^2(\tfrac {\pi }{2} s)$
. In particular, for any
$p(s)=\sin ^2(\tfrac {\pi }{2} s)$
. In particular, for any 
 $g\in \mathcal {G}_{d,l}$
, we have an associated radial Schwartz function
$g\in \mathcal {G}_{d,l}$
, we have an associated radial Schwartz function 
 $G_g:\mathbb {R}^d\to \mathbb {C}$
 such that
$G_g:\mathbb {R}^d\to \mathbb {C}$
 such that 
 $\widehat {G_g}=\varepsilon G_g$
 and
$\widehat {G_g}=\varepsilon G_g$
 and 
 $$ \begin{align*}G_g(x) =\sin^2(\tfrac{\pi}{2} |x|^2)\int_0^{\infty i} g(z)e^{\pi i z |x|^2}\frac{\mathrm{d} z}{i} \end{align*} $$
$$ \begin{align*}G_g(x) =\sin^2(\tfrac{\pi}{2} |x|^2)\int_0^{\infty i} g(z)e^{\pi i z |x|^2}\frac{\mathrm{d} z}{i} \end{align*} $$
if 
 $|x|^2>l$
.
$|x|^2>l$
.
Proof. We will show that all conditions in Proposition 16 are satisfied for 
 $p(s)=\sin ^2(\tfrac {\pi }{2} s)$
. Conditions (a) and (b) follow in a similar manner as in the proof of Lemma 17. Setting
$p(s)=\sin ^2(\tfrac {\pi }{2} s)$
. Conditions (a) and (b) follow in a similar manner as in the proof of Lemma 17. Setting 
 $g=\psi |_kS/\Delta ^{l/2}$
, condition
$g=\psi |_kS/\Delta ^{l/2}$
, condition 
 $(c)$
 for g is then equivalent to
$(c)$
 for g is then equivalent to 
 $$ \begin{align*}\psi|_kST^{-1}=\varepsilon(-1)^{d/4}\psi|_kSTS, \end{align*} $$
$$ \begin{align*}\psi|_kST^{-1}=\varepsilon(-1)^{d/4}\psi|_kSTS, \end{align*} $$
which is true since 
 $\psi $
 is
$\psi $
 is 
 $1$
-periodic,
$1$
-periodic, 
 $\varepsilon (-1)^{d/4}=1$
 and
$\varepsilon (-1)^{d/4}=1$
 and 
 $ST^{-1}(STS)^{-1}=T$
. Condition
$ST^{-1}(STS)^{-1}=T$
. Condition 
 $(d)$
 for g is equivalent to
$(d)$
 for g is equivalent to 
 $$ \begin{align*}\widetilde \psi(z)-\tfrac12(\widetilde \psi(z+1)+\widetilde \psi(z-1)) = \psi(z), \end{align*} $$
$$ \begin{align*}\widetilde \psi(z)-\tfrac12(\widetilde \psi(z+1)+\widetilde \psi(z-1)) = \psi(z), \end{align*} $$
where 
 $\widetilde \psi (z) =\psi |_kS(z)$
. However, simple computations show that this equation holds true for any function
$\widetilde \psi (z) =\psi |_kS(z)$
. However, simple computations show that this equation holds true for any function 
 $\psi \in M_{k+2}^{\leq 2}$
 using the characterization (2) and the functional equation of
$\psi \in M_{k+2}^{\leq 2}$
 using the characterization (2) and the functional equation of 
 $E_2(z)$
.
$E_2(z)$
.
Remark 5. It is not hard to show any function 
 $g\in \mathcal {G}_{d,l}$
 has an q-expansion of the form
$g\in \mathcal {G}_{d,l}$
 has an q-expansion of the form 
 $$ \begin{align*}g=\sum_{n= -l/2}^\infty a_n q^{n}, \end{align*} $$
$$ \begin{align*}g=\sum_{n= -l/2}^\infty a_n q^{n}, \end{align*} $$
where 
 $a_n$
 is a quadratic polynomial in z for
$a_n$
 is a quadratic polynomial in z for 
 $n\geq 1$
, but affine for
$n\geq 1$
, but affine for 
 $n=-l,\ldots ,0$
.
$n=-l,\ldots ,0$
.
The following lemma is reminiscent of the numerical method employed in [Reference Cohn, Kumar, Miller, Radchenko and Viazovska10].
Lemma 19 (Effective tail bounds).
 Let 
 $P(X,Y,Z)$
 and
$P(X,Y,Z)$
 and 
 $Q(X,Y,Z)$
 be homogeneous polynomials of degree
$Q(X,Y,Z)$
 be homogeneous polynomials of degree 
 $k/2$
 and
$k/2$
 and 
 $k+2$
, respectively, where k is even. Let
$k+2$
, respectively, where k is even. Let 
 $|P|$
 and
$|P|$
 and 
 $|Q|$
 denote the homogeneous polynomials derived from P and Q, where each coefficient is replaced by its absolute value. Assume that Q has no power of X larger than
$|Q|$
 denote the homogeneous polynomials derived from P and Q, where each coefficient is replaced by its absolute value. Assume that Q has no power of X larger than 
 $2$
. Define the following holomorphic modular forms:
$2$
. Define the following holomorphic modular forms: 
 $$ \begin{align*}\varphi= P(U,V,W) \ \ \text{ and } \ \ \psi= Q(E_2,E_4,E_6). \end{align*} $$
$$ \begin{align*}\varphi= P(U,V,W) \ \ \text{ and } \ \ \psi= Q(E_2,E_4,E_6). \end{align*} $$
Let 
 $\varphi _M$
 and
$\varphi _M$
 and 
 $\psi _M$
 denote the tail of their respective r-series and q-series from the
$\psi _M$
 denote the tail of their respective r-series and q-series from the 
 $(M+1)$
-term onward. Let
$(M+1)$
-term onward. Let 
 $$ \begin{align*}\varphi_S= P(U_S,V_S,W_S) \end{align*} $$
$$ \begin{align*}\varphi_S= P(U_S,V_S,W_S) \end{align*} $$
and 
 $(\varphi _S)_M$
 be the tail of the r-series of the above function from the
$(\varphi _S)_M$
 be the tail of the r-series of the above function from the 
 $r^{M+1}$
-term Furthermore, letting
$r^{M+1}$
-term Furthermore, letting 
 $w=-\pi i z$
 and
$w=-\pi i z$
 and 
 $$ \begin{align*}w^2 \psi_S = w^2 Q((E_2)_S,E_4,E_6), \end{align*} $$
$$ \begin{align*}w^2 \psi_S = w^2 Q((E_2)_S,E_4,E_6), \end{align*} $$
denote by 
 $(w^2\psi _S)_M$
 the tail of the q-series above from the
$(w^2\psi _S)_M$
 the tail of the q-series above from the 
 $q^{M+1}$
-term. Finally, let
$q^{M+1}$
-term. Finally, let 
 $$ \begin{align*}R_M(p,j)=\sum_{n>M}{(n+1)^p}e^{-\pi{(n-j)}} \ \ \text{ and } \ \ S_M(p,j)=\sum_{n>M}{(n+1)^p}e^{-2\pi{(n-j)}}. \end{align*} $$
$$ \begin{align*}R_M(p,j)=\sum_{n>M}{(n+1)^p}e^{-\pi{(n-j)}} \ \ \text{ and } \ \ S_M(p,j)=\sum_{n>M}{(n+1)^p}e^{-2\pi{(n-j)}}. \end{align*} $$
Then for 
 $j\leq M+1$
,
$j\leq M+1$
, 
 $t\geq 1$
,
$t\geq 1$
, 
 $r=e^{-\pi t}$
 and
$r=e^{-\pi t}$
 and 
 $q=r^2$
, we have
$q=r^2$
, we have 
- 
(1)  $|\varphi _M(it)| \leq |P|(8,8,8) R_M(\tfrac {3k-2}{2},j)r^j$
; $|\varphi _M(it)| \leq |P|(8,8,8) R_M(\tfrac {3k-2}{2},j)r^j$
;
- 
(2)  $|\psi _M(it)| \leq |Q|(24,240,504) S_M(\tfrac {5k+10}{4},j)q^j$
; $|\psi _M(it)| \leq |Q|(24,240,504) S_M(\tfrac {5k+10}{4},j)q^j$
;
- 
(3)  $|(\varphi _S)_{M}(it)| \leq |P|(8,8,8)R_{M}(\tfrac {3k-2}{2},j)r^{j}$
; $|(\varphi _S)_{M}(it)| \leq |P|(8,8,8)R_{M}(\tfrac {3k-2}{2},j)r^{j}$
;
- 
(4)  $|(w^2 \psi _S)_M(it)| \leq 13|Q|(24,240,504)|S_M(\tfrac {5k+10}{4},j)q^j$
. $|(w^2 \psi _S)_M(it)| \leq 13|Q|(24,240,504)|S_M(\tfrac {5k+10}{4},j)q^j$
.
Proof. First we prove (1). Observe that by Jacobi’s four-square theorem, the coefficient of 
 $r^n$
 in the r-series of each of the functions
$r^n$
 in the r-series of each of the functions 
 $U,V$
 and W is bounded by
$U,V$
 and W is bounded by 
 $8(n+1)^2$
. Also note that whenever we multiply m power series
$8(n+1)^2$
. Also note that whenever we multiply m power series 
 $\sum _{n\geq 0} (n+1)^{a_j} r^n$
 for
$\sum _{n\geq 0} (n+1)^{a_j} r^n$
 for 
 $j=1,\ldots ,m$
, the coefficient of
$j=1,\ldots ,m$
, the coefficient of 
 $r^n$
 in the product is bounded by
$r^n$
 in the product is bounded by 
 $(n+1)^{a_1+\ldots +a_m+m-1}$
. We deduce that the coefficient of
$(n+1)^{a_1+\ldots +a_m+m-1}$
. We deduce that the coefficient of 
 $r^n$
 in the r-series of
$r^n$
 in the r-series of 
 $\varphi $
 is bounded by
$\varphi $
 is bounded by 
 $|P|(8,8,8) (n+1)^{(3k-2)/2}$
. Since
$|P|(8,8,8) (n+1)^{(3k-2)/2}$
. Since 
 $t\geq 1$
, we have
$t\geq 1$
, we have 
 $0\leq r\leq e^{-\pi }$
. This easily implies item (1). The same argument shows item (3). Essentially the same argument shows item (2) by realizing that the coefficient of
$0\leq r\leq e^{-\pi }$
. This easily implies item (1). The same argument shows item (3). Essentially the same argument shows item (2) by realizing that the coefficient of 
 $q^n$
 in the q-series of each of the functions
$q^n$
 in the q-series of each of the functions 
 $E_2,E_4$
 and
$E_2,E_4$
 and 
 $E_6$
 are bounded by
$E_6$
 are bounded by 
 $24(n+1)^2$
,
$24(n+1)^2$
, 
 $240(n+1)^4$
 and
$240(n+1)^4$
 and 
 $504(n+1)^6$
, respectively. We deduce that the coefficient of
$504(n+1)^6$
, respectively. We deduce that the coefficient of 
 $q^n$
 in the q-series of
$q^n$
 in the q-series of 
 $\psi $
 is bounded by
$\psi $
 is bounded by 
 $ |Q|(24,240,504) (n+1)^{a+b+c+k+1}$
, where
$ |Q|(24,240,504) (n+1)^{a+b+c+k+1}$
, where 
 $a+b+c$
 is maximal among nonnegative integers
$a+b+c$
 is maximal among nonnegative integers 
 $a,b$
 and c such that
$a,b$
 and c such that 
 $2a+4b+6c=k+2$
 and
$2a+4b+6c=k+2$
 and 
 $0\leq a\leq 2$
. Greedy choice shows that the sum
$0\leq a\leq 2$
. Greedy choice shows that the sum 
 $a+b+c$
 is maximized (or bounded by) when
$a+b+c$
 is maximized (or bounded by) when 
 $(a,b,c)=(2,(k-2)/4,0)$
, and thus, the coefficient of
$(a,b,c)=(2,(k-2)/4,0)$
, and thus, the coefficient of 
 $q^n$
 is bounded by
$q^n$
 is bounded by 
 $|Q|(24,240,504) (n+1)^{(5k+10)/4}$
. This proves item (2). Finally, item (4) is more nuanced since we have the presence of w. Let
$|Q|(24,240,504) (n+1)^{(5k+10)/4}$
. This proves item (2). Finally, item (4) is more nuanced since we have the presence of w. Let 
 $$ \begin{align*}Q(X,Y,Z) = Q_0(Y,Z) + XQ_1(Y,Z)+X^2 Q_2(Y,Z), \end{align*} $$
$$ \begin{align*}Q(X,Y,Z) = Q_0(Y,Z) + XQ_1(Y,Z)+X^2 Q_2(Y,Z), \end{align*} $$
so that 
 $|Q(24,240,504)|=|Q_0|(240,504)+24|Q_1|(240,504)+24^2|Q_2|(240,504)$
 and
$|Q(24,240,504)|=|Q_0|(240,504)+24|Q_1|(240,504)+24^2|Q_2|(240,504)$
 and 
 $$ \begin{align*} w^2 \psi_S & = w^2Q_0(E_4,E_6) + ({w^2}E_2-{6w})Q_1(E_4,E_6) + ({w}E_2-6)^2Q_2(E_4,E_6) \\ & = Qw^2 + (-12Q_2E_2 - 6Q_1)w + 36Q_2. \end{align*} $$
$$ \begin{align*} w^2 \psi_S & = w^2Q_0(E_4,E_6) + ({w^2}E_2-{6w})Q_1(E_4,E_6) + ({w}E_2-6)^2Q_2(E_4,E_6) \\ & = Qw^2 + (-12Q_2E_2 - 6Q_1)w + 36Q_2. \end{align*} $$
For 
 $z=it$
 and
$z=it$
 and 
 $t\geq 1$
, we have
$t\geq 1$
, we have 
 $\pi \leq w=\pi t \leq \tfrac 1{7r}$
, and we obtain
$\pi \leq w=\pi t \leq \tfrac 1{7r}$
, and we obtain 
 $$ \begin{align*} {|(w^2 \psi_S)_M(it)|} & \leq (\tfrac1{7r})^2{|Q|(24,240,504) }S_M(\tfrac{5k+10}{4},j+1)q^{j+1} \\ & \quad + \tfrac1{7r} (288|Q_2|(240,504)+6|Q_1|(240,504))S_M(\tfrac{5k}{4},j+1/2)q^{j+1/2}\\ & \quad +36|Q_2|(240,504)S_M(\tfrac{5k-10}{4},j)q^j \\ & \leq (\tfrac{e^{2\pi}}{49}{|Q|(24,240,504) } + \tfrac{e^{\pi}}{7} (288|Q_2|(240,504)+6|Q_1|(240,504))\\ & \quad +36|Q_2|(240,504))S_M(\tfrac{5k+10}{4},j)q^j \\ & < (11|Q_0|(240,504) + 283|Q_1|(240,504) + 7283|Q_2|(240,504))S_M(\tfrac{5k+10}{4},j)q^j\\ & <13|Q|(24,240,504)S_M(\tfrac{5k+10}{4},j)q^j \end{align*} $$
$$ \begin{align*} {|(w^2 \psi_S)_M(it)|} & \leq (\tfrac1{7r})^2{|Q|(24,240,504) }S_M(\tfrac{5k+10}{4},j+1)q^{j+1} \\ & \quad + \tfrac1{7r} (288|Q_2|(240,504)+6|Q_1|(240,504))S_M(\tfrac{5k}{4},j+1/2)q^{j+1/2}\\ & \quad +36|Q_2|(240,504)S_M(\tfrac{5k-10}{4},j)q^j \\ & \leq (\tfrac{e^{2\pi}}{49}{|Q|(24,240,504) } + \tfrac{e^{\pi}}{7} (288|Q_2|(240,504)+6|Q_1|(240,504))\\ & \quad +36|Q_2|(240,504))S_M(\tfrac{5k+10}{4},j)q^j \\ & < (11|Q_0|(240,504) + 283|Q_1|(240,504) + 7283|Q_2|(240,504))S_M(\tfrac{5k+10}{4},j)q^j\\ & <13|Q|(24,240,504)S_M(\tfrac{5k+10}{4},j)q^j \end{align*} $$
This proves item (4).
7 Proof of Theorem 1
 We assume Theorem 4. Let 
 $d=48$
 and
$d=48$
 and 
 $K=\frac {1}{\sqrt {6}}([\sqrt {6},\sqrt {8}]\cup \{\sqrt {10}\})$
. Let
$K=\frac {1}{\sqrt {6}}([\sqrt {6},\sqrt {8}]\cup \{\sqrt {10}\})$
. Let 
 $\Lambda \subset \mathbb {R}^{48}$
 be an even unimodular extremal lattice. In particular,
$\Lambda \subset \mathbb {R}^{48}$
 be an even unimodular extremal lattice. In particular, 
 $\Lambda $
 is self-dual and
$\Lambda $
 is self-dual and 
 $\ell (\Lambda )=\{\sqrt {6},\sqrt {8},\ldots \}$
. It is trivial to see
$\ell (\Lambda )=\{\sqrt {6},\sqrt {8},\ldots \}$
. It is trivial to see 
 $\Lambda $
 is K-admissible and that
$\Lambda $
 is K-admissible and that 
 $$ \begin{align*}\mathrm{dens}(\Lambda)= \mathrm{vol} \left( B_{48}\right) \left( \frac{\sqrt{6}}{2}\right)^{48}=\frac{(3\pi/2)^{24}}{24!}. \end{align*} $$
$$ \begin{align*}\mathrm{dens}(\Lambda)= \mathrm{vol} \left( B_{48}\right) \left( \frac{\sqrt{6}}{2}\right)^{48}=\frac{(3\pi/2)^{24}}{24!}. \end{align*} $$
Consider 
 $F(x)=H(\sqrt {6}x)$
, with H as in Theorem 4 for
$F(x)=H(\sqrt {6}x)$
, with H as in Theorem 4 for 
 $d=48$
. Poisson summation over
$d=48$
. Poisson summation over 
 $\Lambda $
 shows that
$\Lambda $
 shows that 
 $H(0)=\widehat H(0)>0$
. The properties of H imply that F satisfies all conditions of Theorem 3, and hence,
$H(0)=\widehat H(0)>0$
. The properties of H imply that F satisfies all conditions of Theorem 3, and hence, 
 $$ \begin{align*}\mathrm{dens}(\Lambda) \leq \Delta_d(K) \leq \mathrm{vol}(\tfrac12B_{48} ) \frac{F(0)}{\widehat F(0)}= \mathrm{vol} \left( B_{48}\right) \left( \frac{\sqrt{6}}{2}\right)^{48}. \end{align*} $$
$$ \begin{align*}\mathrm{dens}(\Lambda) \leq \Delta_d(K) \leq \mathrm{vol}(\tfrac12B_{48} ) \frac{F(0)}{\widehat F(0)}= \mathrm{vol} \left( B_{48}\right) \left( \frac{\sqrt{6}}{2}\right)^{48}. \end{align*} $$
This shows that equality above is attained and 
 $\Lambda $
 is optimal; that is,
$\Lambda $
 is optimal; that is, 
 $\Delta _d(K) = \mathrm {dens}(\Lambda )$
.
$\Delta _d(K) = \mathrm {dens}(\Lambda )$
.
 Now we prove uniqueness among all periodic packings. We follow the same strategy as in [Reference Cohn and Elkies8, Section 8]. Let 
 $P=L+Y+\frac {1}{2}B_d$
 be an optimal admissible periodic packing for some lattice L and a set of translations
$P=L+Y+\frac {1}{2}B_d$
 be an optimal admissible periodic packing for some lattice L and a set of translations 
 $Y=\{v_1,\ldots ,v_M\}$
. By Poisson Summation,
$Y=\{v_1,\ldots ,v_M\}$
. By Poisson Summation, 
 $$ \begin{align*} \sum_{j,l=1}^{M} \sum_{x\in L} F(x+v_j-v_l)=\frac{1}{|L|}\sum_{y\in L^*} \widehat{F}(y)\left|\sum_{j=1}^{M} e^{2\pi i yv_j}\right|^2, \end{align*} $$
$$ \begin{align*} \sum_{j,l=1}^{M} \sum_{x\in L} F(x+v_j-v_l)=\frac{1}{|L|}\sum_{y\in L^*} \widehat{F}(y)\left|\sum_{j=1}^{M} e^{2\pi i yv_j}\right|^2, \end{align*} $$
from which we derive
 $$ \begin{align*} M F(0)\geq\frac{1}{|L|}\widehat{F}(0) M^2. \end{align*} $$
$$ \begin{align*} M F(0)\geq\frac{1}{|L|}\widehat{F}(0) M^2. \end{align*} $$
Since P is optimal, we have equality above, from which we derive that 
 $|\sqrt {6}L|=M$
 and that
$|\sqrt {6}L|=M$
 and that 
 $\{x+v_j-v_l : x\in L, \, 1\leq j,l\leq M\}$
 is contained in the set of zeros of F. By Theorem 4, we deduce that
$\{x+v_j-v_l : x\in L, \, 1\leq j,l\leq M\}$
 is contained in the set of zeros of F. By Theorem 4, we deduce that 
 $\{\sqrt {6}|x+v_j-v_l| : x\in L, \, 1\leq j,l\leq M\}\subset \{0,\sqrt {6},\sqrt {8},\sqrt {10},\ldots \}$
. By [Reference Cohn and Elkies8, Lemma 8.2], we conclude that the subgroup G of
$\{\sqrt {6}|x+v_j-v_l| : x\in L, \, 1\leq j,l\leq M\}\subset \{0,\sqrt {6},\sqrt {8},\sqrt {10},\ldots \}$
. By [Reference Cohn and Elkies8, Lemma 8.2], we conclude that the subgroup G of 
 $\mathbb {R}^{48}$
 generated by the set
$\mathbb {R}^{48}$
 generated by the set 
 $\sqrt {6}(L+Y)$
 is an even integral lattice with minimal norm
$\sqrt {6}(L+Y)$
 is an even integral lattice with minimal norm 
 $\geq \sqrt {6}$
. It also follows that the volume
$\geq \sqrt {6}$
. It also follows that the volume 
 $|G|=\sqrt {N}$
, for some integer N, and hence, G has at most one point per unit of volume in
$|G|=\sqrt {N}$
, for some integer N, and hence, G has at most one point per unit of volume in 
 $\mathbb {R}^{48}$
. However, since
$\mathbb {R}^{48}$
. However, since 
 $|\sqrt {6}L|=M$
, the packing
$|\sqrt {6}L|=M$
, the packing 
 $\sqrt {6}(L+Y)+\frac {\sqrt {6}}{2}B_d$
 has one sphere per unit of volume. Therefore, G has exactly one point per unit volume, which implies that
$\sqrt {6}(L+Y)+\frac {\sqrt {6}}{2}B_d$
 has one sphere per unit of volume. Therefore, G has exactly one point per unit volume, which implies that 
 $N=1$
, G is unimodular and
$N=1$
, G is unimodular and 
 $G=\sqrt {6}(L+Y)$
. Therefore, G must be an extremal lattice. This finishes the proof of Theorem 1.
$G=\sqrt {6}(L+Y)$
. Therefore, G must be an extremal lattice. This finishes the proof of Theorem 1.
8 Proof of Theorem 4
 Let 
 $8\leq d \leq 1200$
 be a multiple of
$8\leq d \leq 1200$
 be a multiple of 
 $8$
,
$8$
, 
 $a=a_d$
,
$a=a_d$
, 
 $l= l_d$
,
$l= l_d$
, 
 $c=c_d$
 and
$c=c_d$
 and 
 $ K=K_d=\frac {1}{\sqrt {a}}\{\sqrt {a},\sqrt {a+2},\ldots ,\sqrt {l}\} $
. In what follows, we set
$ K=K_d=\frac {1}{\sqrt {a}}\{\sqrt {a},\sqrt {a+2},\ldots ,\sqrt {l}\} $
. In what follows, we set 
 $k=2-d/2+6l$
 (which is congruent to
$k=2-d/2+6l$
 (which is congruent to 
 $2$
 modulo
$2$
 modulo 
 $4$
),
$4$
), 
 $\varepsilon =-1$
,
$\varepsilon =-1$
, 
 $$ \begin{align*}\mathfrak{b}=\frac{l}{2} - \bigg\lfloor \frac{d-4}{12} \bigg\rfloor, \end{align*} $$
$$ \begin{align*}\mathfrak{b}=\frac{l}{2} - \bigg\lfloor \frac{d-4}{12} \bigg\rfloor, \end{align*} $$
 $w=-\pi i z$
,
$w=-\pi i z$
, 
 $r=e^{\pi i z}$
 and
$r=e^{\pi i z}$
 and 
 $q=r^2$
. We will abuse notation and write
$q=r^2$
. We will abuse notation and write 
 $u(z)=O(r^k)$
 if for some
$u(z)=O(r^k)$
 if for some 
 $C>0$
, we have
$C>0$
, we have 
 $|u(z)|\leq C |z|^C e^{-\pi k \Im z }$
 for
$|u(z)|\leq C |z|^C e^{-\pi k \Im z }$
 for 
 $\Im z>C$
.
$\Im z>C$
.
The assertions below were done with rational arithmetic via PARI/GP [Reference Batut, Belabas, Benardi, Cohen and Olivier3] computer algebra system. Below, we will make certain claims, and we will indicate precisely how to prove them. This proof is computer assisted; hence, the necessary ancillary files can be found with the arXiv submission of this paper (arXiv:2308.03925).
 
Step 1. We apply Lemma 17 and compute a basis for the vector space 
 $\mathcal {F}_{d,l}$
 collected as a row vector of functions
$\mathcal {F}_{d,l}$
 collected as a row vector of functions 
 $$ \begin{align*}[f_1,\ldots ,f_{\mathfrak{b}}] = \Delta^{-l/2} [\varphi_1,\varphi_2,\ldots ,\varphi_{\mathfrak{b}}], \end{align*} $$
$$ \begin{align*}[f_1,\ldots ,f_{\mathfrak{b}}] = \Delta^{-l/2} [\varphi_1,\varphi_2,\ldots ,\varphi_{\mathfrak{b}}], \end{align*} $$
where 
 $\dim \mathcal {F}_{d,l} = \mathfrak {b}$
 and
$\dim \mathcal {F}_{d,l} = \mathfrak {b}$
 and 
 $$ \begin{align*} \Phi &= [\varphi_1,\varphi_2,\ldots ,\varphi_{\mathfrak{b}}] = W^{l+1}(\mathcal{M}_\varphi \mathbf{\Theta}^\top)^\top, \\ \mathcal{M}_\varphi & \in \mathbb{Q}^{\mathfrak{b} \times (k/2-l )}, \\ \mathbf{\Theta} & = [W^{j-1} V^{k/2-l-j}]_{j=1,\ldots ,k/2-l}. \end{align*} $$
$$ \begin{align*} \Phi &= [\varphi_1,\varphi_2,\ldots ,\varphi_{\mathfrak{b}}] = W^{l+1}(\mathcal{M}_\varphi \mathbf{\Theta}^\top)^\top, \\ \mathcal{M}_\varphi & \in \mathbb{Q}^{\mathfrak{b} \times (k/2-l )}, \\ \mathbf{\Theta} & = [W^{j-1} V^{k/2-l-j}]_{j=1,\ldots ,k/2-l}. \end{align*} $$
We use the symbol 
 $^\top $
 for transpose.
$^\top $
 for transpose. 
 $\Theta $
 is a row vector of basis functions for
$\Theta $
 is a row vector of basis functions for 
 $M_{k-2l-2}(\Gamma (2))$
. It is easy to show that any function in
$M_{k-2l-2}(\Gamma (2))$
. It is easy to show that any function in 
 $\Delta ^{l/2}\mathcal {F}_{d,l}$
 must be divisible by
$\Delta ^{l/2}\mathcal {F}_{d,l}$
 must be divisible by 
 $W^{l+1}$
, and this is the reason why we have isolated it in
$W^{l+1}$
, and this is the reason why we have isolated it in 
 $\Phi $
. To make sure
$\Phi $
. To make sure 
 $\Phi $
 is uniquely defined (and so
$\Phi $
 is uniquely defined (and so 
 $\mathcal {M}_\varphi $
), we normalize
$\mathcal {M}_\varphi $
), we normalize 
 $\varphi _j$
 so that
$\varphi _j$
 so that 
 $$ \begin{align*}{\varphi_j} = r^{2(j-1)} + O(r^{2\mathfrak{b}}). \end{align*} $$
$$ \begin{align*}{\varphi_j} = r^{2(j-1)} + O(r^{2\mathfrak{b}}). \end{align*} $$
Step 2. We apply Lemma 18 and then proceed to find a basis
 $$ \begin{align*}[g_1,\ldots ,g_{\mathfrak{c}}] = \Delta^{-l/2} [w^2(\psi_1)_S,\ldots ,w^2(\psi_{\mathfrak{c}})_S], \end{align*} $$
$$ \begin{align*}[g_1,\ldots ,g_{\mathfrak{c}}] = \Delta^{-l/2} [w^2(\psi_1)_S,\ldots ,w^2(\psi_{\mathfrak{c}})_S], \end{align*} $$
collected as a row vector, for the subspace of functions 
 $g\in \mathcal {G}_{d,l}$
, with
$g\in \mathcal {G}_{d,l}$
, with 
 $g=w^2 \psi _S/\Delta ^{l/2}$
, and such that
$g=w^2 \psi _S/\Delta ^{l/2}$
, and such that 
 $$ \begin{align*}[w r^{j}](w^2 \Delta^{-l/2} \psi_S) =0 \end{align*} $$
$$ \begin{align*}[w r^{j}](w^2 \Delta^{-l/2} \psi_S) =0 \end{align*} $$
for 
 $j\in \{-l,\ldots ,-a\}$
. By the choice of l and a, it turns out that
$j\in \{-l,\ldots ,-a\}$
. By the choice of l and a, it turns out that 
 $\mathfrak {c}=\mathfrak {b}$
 for all cases, we have computed (the proof that these dimensions coincide for all d is lengthy and not worth to include here since we are doing this numerically anyways). Here, we set
$\mathfrak {c}=\mathfrak {b}$
 for all cases, we have computed (the proof that these dimensions coincide for all d is lengthy and not worth to include here since we are doing this numerically anyways). Here, we set 
 $$ \begin{align*} \Psi & = [\psi_1,\psi_2,\ldots ,\psi_{\mathfrak{b}}] = (\mathcal{M}_\psi \mathbf{E}^\top)^\top, \\ \mathcal{M}_\psi & \in \mathbb{Q}^{ \mathfrak{b} \times (k+6)/4},\\ \mathbf{E} & = [E_2^{i}E_4^{j}E_6^n]_{\substack{2i+4j+6n=k+2 \\ j =0,\ldots ,(k+2)/4}}. \end{align*} $$
$$ \begin{align*} \Psi & = [\psi_1,\psi_2,\ldots ,\psi_{\mathfrak{b}}] = (\mathcal{M}_\psi \mathbf{E}^\top)^\top, \\ \mathcal{M}_\psi & \in \mathbb{Q}^{ \mathfrak{b} \times (k+6)/4},\\ \mathbf{E} & = [E_2^{i}E_4^{j}E_6^n]_{\substack{2i+4j+6n=k+2 \\ j =0,\ldots ,(k+2)/4}}. \end{align*} $$
 $\textbf {E}$
 is a row vector of size
$\textbf {E}$
 is a row vector of size 
 $(k+6)/4$
 that contains the basis functions for
$(k+6)/4$
 that contains the basis functions for 
 $M_{k+2}$
 (for each
$M_{k+2}$
 (for each 
 $j=0,..,(k+2)/4$
, the tuple
$j=0,..,(k+2)/4$
, the tuple 
 $(i,n)$
 is given by
$(i,n)$
 is given by 
 $i=((k+2)/2-2j) \text { mod } 3$
 and
$i=((k+2)/2-2j) \text { mod } 3$
 and 
 $n=(k+2-2i-4j)/6$
). To make sure that
$n=(k+2-2i-4j)/6$
). To make sure that 
 $\Psi $
 is uniquely defined, we impose that
$\Psi $
 is uniquely defined, we impose that 
 $$ \begin{align*}{w^2(\psi_j)_S} = r^{2(j-1)} + O(r^{2\mathfrak{b}}) \end{align*} $$
$$ \begin{align*}{w^2(\psi_j)_S} = r^{2(j-1)} + O(r^{2\mathfrak{b}}) \end{align*} $$
for 
 $j=1,\ldots ,\mathfrak {b}$
.
$j=1,\ldots ,\mathfrak {b}$
.
Step 3. We now solve a linear system of homogeneous equations and set
 $$ \begin{align*} \varphi = \mathcal{V}_\varphi \mathcal{M}_\varphi {\boldsymbol \Theta}^\top\ \text{ and } \ \psi & = \mathcal{V}_\psi \mathcal{M}_\psi \mathbf{E}^\top, \end{align*} $$
$$ \begin{align*} \varphi = \mathcal{V}_\varphi \mathcal{M}_\varphi {\boldsymbol \Theta}^\top\ \text{ and } \ \psi & = \mathcal{V}_\psi \mathcal{M}_\psi \mathbf{E}^\top, \end{align*} $$
where 
 $ \mathcal {V}_\varphi $
 and
$ \mathcal {V}_\varphi $
 and 
 $\mathcal {V}_\psi $
 are row vectors of size
$\mathcal {V}_\psi $
 are row vectors of size 
 $\mathfrak {b}$
 (the solutions) that enforce the following r-expansion shapes:
$\mathfrak {b}$
 (the solutions) that enforce the following r-expansion shapes: 
 $$ \begin{align*} {-w^2\psi _S- \varphi} &= \sum_{n= 0}^{l-a} \alpha_n r^{n} +\sum_{n=l - a+1}^{l} (\alpha_n + \alpha_n'w) r^{n} + O(r^{l+1}),\\ {-w^2\psi_S + \varphi} &= \sum_{n= l - a+1}^{l} (\beta_n + \beta'_{n}w) r^{n} + O(r^{l+1}), \end{align*} $$
$$ \begin{align*} {-w^2\psi _S- \varphi} &= \sum_{n= 0}^{l-a} \alpha_n r^{n} +\sum_{n=l - a+1}^{l} (\alpha_n + \alpha_n'w) r^{n} + O(r^{l+1}),\\ {-w^2\psi_S + \varphi} &= \sum_{n= l - a+1}^{l} (\beta_n + \beta'_{n}w) r^{n} + O(r^{l+1}), \end{align*} $$
for some 
 $\alpha _n,\alpha _n',\beta _n,\beta _n'\in \mathbb {Q}$
. Recall that by Remark 5,
$\alpha _n,\alpha _n',\beta _n,\beta _n'\in \mathbb {Q}$
. Recall that by Remark 5, 
 $[w^2 r^j](-w^2\psi _S)=0$
 for
$[w^2 r^j](-w^2\psi _S)=0$
 for 
 $j\leq 0$
. Note also that, by construction, we already have that
$j\leq 0$
. Note also that, by construction, we already have that 
 $\alpha _n,\alpha _n',\beta _n,\beta _n'$
 vanish for odd n in the range
$\alpha _n,\alpha _n',\beta _n,\beta _n'$
 vanish for odd n in the range 
 $0\leq n\leq l$
. More precisely, given all the previous constraints,
$0\leq n\leq l$
. More precisely, given all the previous constraints, 
 $ \mathcal {V}_\varphi $
 and
$ \mathcal {V}_\varphi $
 and 
 $\mathcal {V}_\psi $
 are solutions of the homogeneous equations
$\mathcal {V}_\psi $
 are solutions of the homogeneous equations 
 $$ \begin{align*}[w^0 r^j]({-w^2\psi_S + \varphi})=0 \end{align*} $$
$$ \begin{align*}[w^0 r^j]({-w^2\psi_S + \varphi})=0 \end{align*} $$
for 
 $j\in \{0,2,\ldots ,l-a\}$
. It turns out that
$j\in \{0,2,\ldots ,l-a\}$
. It turns out that 
 $\mathcal {V}_\varphi $
 and
$\mathcal {V}_\varphi $
 and 
 $\mathcal {V}_\psi $
 are uniquely defined modulo scaling. We then define the row vectors
$\mathcal {V}_\psi $
 are uniquely defined modulo scaling. We then define the row vectors 
 $$ \begin{align*}C_\varphi = {n}\mathcal{V}_\varphi \mathcal{M}_\varphi \ \text{ and } \ C_\psi={n}\mathcal{V}_\psi \mathcal{M}_\psi, \end{align*} $$
$$ \begin{align*}C_\varphi = {n}\mathcal{V}_\varphi \mathcal{M}_\varphi \ \text{ and } \ C_\psi={n}\mathcal{V}_\psi \mathcal{M}_\psi, \end{align*} $$
where we choose 
 $n\in \mathbb {Z}$
 so that
$n\in \mathbb {Z}$
 so that 
 $C_\varphi $
 and
$C_\varphi $
 and 
 $C_\psi $
 are vectors of integers where
$C_\psi $
 are vectors of integers where 
 $\gcd (C_\varphi \cup C_\psi )=1$
 and the first nonzero coordinate of
$\gcd (C_\varphi \cup C_\psi )=1$
 and the first nonzero coordinate of 
 $C_\varphi $
 is positive. In this way,
$C_\varphi $
 is positive. In this way, 
 $C_\varphi $
 and
$C_\varphi $
 and 
 $C_\psi $
 are uniquely defined. For instance, for
$C_\psi $
 are uniquely defined. For instance, for 
 $d=48$
, we have
$d=48$
, we have 
 $$ \begin{align*} C_\varphi &=2^7\times 3^8 \times [29393, 117572, 307819, 511955, 539410, 362729, 152114, 36480, 3840] \\ C_\psi & = [565675, 7394933, -38880096, 44550063, 41316945, -107522880, 39169185, \\ & \quad \ \ 40077567, -32756064, 5294597, 790075]. \end{align*} $$
$$ \begin{align*} C_\varphi &=2^7\times 3^8 \times [29393, 117572, 307819, 511955, 539410, 362729, 152114, 36480, 3840] \\ C_\psi & = [565675, 7394933, -38880096, 44550063, 41316945, -107522880, 39169185, \\ & \quad \ \ 40077567, -32756064, 5294597, 790075]. \end{align*} $$
These vectors cannot be simplified much further nor have some easy to guess combinatorial formula since, for instance, the 
 $8$
th entry of
$8$
th entry of 
 $C_\psi $
 is divisible by the large prime
$C_\psi $
 is divisible by the large prime 
 $4453063$
 and
$4453063$
 and 
 $7$
th entry of
$7$
th entry of 
 $C_\varphi $
 is divisible by the prime
$C_\varphi $
 is divisible by the prime 
 $4003$
. Experimentally, large primes are often found in the vectors
$4003$
. Experimentally, large primes are often found in the vectors 
 $C_\varphi $
 and
$C_\varphi $
 and 
 $C_\psi $
 as dimension grows. A list of all vectors
$C_\psi $
 as dimension grows. A list of all vectors 
 $C_\varphi $
 and
$C_\varphi $
 and 
 $C_\psi $
 for each dimension
$C_\psi $
 for each dimension 
 $d\leq 1200$
 multiple of
$d\leq 1200$
 multiple of 
 $8$
 can be found on the ancillary files in the arXiv submission of this paper (a file named Cvectors).
$8$
 can be found on the ancillary files in the arXiv submission of this paper (a file named Cvectors).
 
Step 4. We use Lemmas 17 and 18 to create a radial Schwartz function 
 $H:\mathbb {R}^d\to \mathbb {R}$
 and obtain the integral representations
$H:\mathbb {R}^d\to \mathbb {R}$
 and obtain the integral representations 
 $$ \begin{align*} H(x)& =\sin^2(\tfrac{\pi}{2} |x|^2)\int_0^{\infty } \frac{-\pi^2 t^2\psi_S(it)-\varphi(it)}{\Delta^{l/2}(it)}e^{- \pi t |x|^2}\mathrm{d} t \\ \widehat H(x)& =\sin^2(\tfrac{\pi}{2} |x|^2)\int_0^{\infty} \frac{-\pi^2 t^2\psi_S(it)+\varphi(it)}{\Delta^{l/2}(it)}e^{ -\pi t |x|^2}\mathrm{d} t, \end{align*} $$
$$ \begin{align*} H(x)& =\sin^2(\tfrac{\pi}{2} |x|^2)\int_0^{\infty } \frac{-\pi^2 t^2\psi_S(it)-\varphi(it)}{\Delta^{l/2}(it)}e^{- \pi t |x|^2}\mathrm{d} t \\ \widehat H(x)& =\sin^2(\tfrac{\pi}{2} |x|^2)\int_0^{\infty} \frac{-\pi^2 t^2\psi_S(it)+\varphi(it)}{\Delta^{l/2}(it)}e^{ -\pi t |x|^2}\mathrm{d} t, \end{align*} $$
that hold for 
 $|x|^2>l$
. This shows that
$|x|^2>l$
. This shows that 
 $$ \begin{align*}H(x)=\widehat H(x)=0 \text{ for } |x|^2 \in \{l+2,l+4,\ldots \}. \end{align*} $$
$$ \begin{align*}H(x)=\widehat H(x)=0 \text{ for } |x|^2 \in \{l+2,l+4,\ldots \}. \end{align*} $$
However, if we let 
 $g=-\Delta ^{-l/2} w^2 \psi _S$
 and
$g=-\Delta ^{-l/2} w^2 \psi _S$
 and 
 $f=\Delta ^{-l/2} \varphi $
, then, by construction, the
$f=\Delta ^{-l/2} \varphi $
, then, by construction, the 
 $r^j$
-coefficient of
$r^j$
-coefficient of 
 $g-f$
 is a rational number for
$g-f$
 is a rational number for 
 $j=-l,\ldots ,-a$
. Similarly, by construction, the
$j=-l,\ldots ,-a$
. Similarly, by construction, the 
 $r^j$
-coefficient of
$r^j$
-coefficient of 
 $g+f$
 vanishes for
$g+f$
 vanishes for 
 $j=-l,\ldots ,-a$
. A straightforward computation shows also that
$j=-l,\ldots ,-a$
. A straightforward computation shows also that 
 $H(x)=\widehat H(x)=0$
 for
$H(x)=\widehat H(x)=0$
 for 
 $|x|^2\in \{a,a+2,\ldots \}$
, and the integral representation of
$|x|^2\in \{a,a+2,\ldots \}$
, and the integral representation of 
 $\widehat H(x)$
 above converges for
$\widehat H(x)$
 above converges for 
 $|x|^2>a-2$
.
$|x|^2>a-2$
.
 
Step 5. From now on, we assume that  . We claim that
. We claim that 
- 
(i)  $|\pi ^2 \psi (it)|< -\varphi _S(it)$
 for $|\pi ^2 \psi (it)|< -\varphi _S(it)$
 for $t\geq 1$
; $t\geq 1$
;
- 
(ii)  $|\pi ^2 t^2\psi _S(it)| < \varphi (it)$
 for $|\pi ^2 t^2\psi _S(it)| < \varphi (it)$
 for $t\geq 1$
. $t\geq 1$
.
Notice that for 
 $|x|^2>a-2$
, we have
$|x|^2>a-2$
, we have 
 $$ \begin{align*} \frac{\widehat H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)} & = \int_1^{\infty } \frac{-\pi^2 t^2\psi_S(it)+\varphi(it)}{\Delta^{l/2}(it)}e^{- \pi t |x|^2}\mathrm{d} t + \int_1^{\infty } \frac{-\pi^2\psi(it)-\varphi_S(it)}{\Delta^{l/2}(it)}e^{- \pi |x|^2/t} \frac{\mathrm{d} t}{t^{d/2}}> 0, \end{align*} $$
$$ \begin{align*} \frac{\widehat H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)} & = \int_1^{\infty } \frac{-\pi^2 t^2\psi_S(it)+\varphi(it)}{\Delta^{l/2}(it)}e^{- \pi t |x|^2}\mathrm{d} t + \int_1^{\infty } \frac{-\pi^2\psi(it)-\varphi_S(it)}{\Delta^{l/2}(it)}e^{- \pi |x|^2/t} \frac{\mathrm{d} t}{t^{d/2}}> 0, \end{align*} $$
by conditions (i) and (ii). This implies that 
 $\widehat H(x) \geq 0$
 for
$\widehat H(x) \geq 0$
 for 
 $|x|^2>a-2$
 and vanishes exactly at
$|x|^2>a-2$
 and vanishes exactly at 
 $|x|^2 \in \{a,a+2,a+4,\ldots \}$
 if
$|x|^2 \in \{a,a+2,a+4,\ldots \}$
 if 
 $|x|^2>a-2$
. Similarly, for
$|x|^2>a-2$
. Similarly, for 
 $|x|^2>l$
, we have
$|x|^2>l$
, we have 
 $$ \begin{align*} \frac{H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)} & = \int_1^{\infty } \frac{-\pi^2 t^2\psi_S(it)-\varphi(it)}{\Delta^{l/2}(it)}e^{- \pi t |x|^2}\mathrm{d} t + \int_1^{\infty } \frac{-\pi^2\psi(it)+\varphi_S(it)}{\Delta^{l/2}(it)}e^{- \pi |x|^2/t} \frac{\mathrm{d} t}{t^{d/2}} < 0, \end{align*} $$
$$ \begin{align*} \frac{H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)} & = \int_1^{\infty } \frac{-\pi^2 t^2\psi_S(it)-\varphi(it)}{\Delta^{l/2}(it)}e^{- \pi t |x|^2}\mathrm{d} t + \int_1^{\infty } \frac{-\pi^2\psi(it)+\varphi_S(it)}{\Delta^{l/2}(it)}e^{- \pi |x|^2/t} \frac{\mathrm{d} t}{t^{d/2}} < 0, \end{align*} $$
and so 
 $H(x) \leq 0$
 for
$H(x) \leq 0$
 for 
 $|x|^2>l$
 and vanishes exactly at
$|x|^2>l$
 and vanishes exactly at 
 $|x|^2 \in \{l,l+2,l+4,\ldots \}$
 if
$|x|^2 \in \{l,l+2,l+4,\ldots \}$
 if 
 $|x|^2>l-\varepsilon $
, for some small
$|x|^2>l-\varepsilon $
, for some small 
 $\varepsilon>0$
.
$\varepsilon>0$
.
 
Step 6. To prove the claims (i) and (ii) in Step 5, we introduce the following notation: For a given 
 $u=\sum _{n\geq 0} a_n(w) r^n$
, we write
$u=\sum _{n\geq 0} a_n(w) r^n$
, we write 
 $$ \begin{align*}{(u)^{\mathrm{trunc}}} = \sum_{n= 0}^N a_n(w) r^n + r^{l+10} \ \text{ and } \ {(u)_{\mathrm{trunc}}} = \sum_{n= 0}^N a_n(w) r^n - r^{l+10}. \end{align*} $$
$$ \begin{align*}{(u)^{\mathrm{trunc}}} = \sum_{n= 0}^N a_n(w) r^n + r^{l+10} \ \text{ and } \ {(u)_{\mathrm{trunc}}} = \sum_{n= 0}^N a_n(w) r^n - r^{l+10}. \end{align*} $$
Recall from Lemma 19 that 
 $R_N$
 and
$R_N$
 and 
 $S_{N/2}$
 are the corresponding tail sums. We will choose
$S_{N/2}$
 are the corresponding tail sums. We will choose 
 $N \geq l+10n$
, with
$N \geq l+10n$
, with 
 $n\geq 1$
, to be the first integer such that the quantity
$n\geq 1$
, to be the first integer such that the quantity 
 $$ \begin{align*}\max\bigg\{\mathrm{abs}(C_\varphi)\mathbf{\Theta}^\top|_{r=0}R_N((3k-2)/2,l+10), 13\mathrm{abs}(C_\psi )\mathbf{ E}^\top|_{q=0}S_{N/2}((5k+10)/4,l/2+5)\bigg\} \end{align*} $$
$$ \begin{align*}\max\bigg\{\mathrm{abs}(C_\varphi)\mathbf{\Theta}^\top|_{r=0}R_N((3k-2)/2,l+10), 13\mathrm{abs}(C_\psi )\mathbf{ E}^\top|_{q=0}S_{N/2}((5k+10)/4,l/2+5)\bigg\} \end{align*} $$
is less than 
 $1$
. Above,
$1$
. Above, 
 $\mathrm {abs}(v)$
, for a vector v, is simply the same vector with each coordinate replaced by its absolute value. By Lemma 19, this guarantees that
$\mathrm {abs}(v)$
, for a vector v, is simply the same vector with each coordinate replaced by its absolute value. By Lemma 19, this guarantees that 
 $$ \begin{align*} {(\varphi)_{\mathrm{trunc}}} &\leq \varphi \leq {(\varphi)^{\mathrm{trunc}}}, \quad \quad \quad \, {(\varphi_S)_{\mathrm{trunc}}} \leq \varphi_S \leq {(\varphi_S)^{\mathrm{trunc}}},\\ {(\psi)_{\mathrm{trunc}}} &\leq \psi \leq {(\psi)^{\mathrm{trunc}}}, \quad \quad {(w^2\psi_S)_{\mathrm{trunc}}} \leq w^2\psi_S \leq {(w^2\psi_S)^{\mathrm{trunc}}}, \end{align*} $$
$$ \begin{align*} {(\varphi)_{\mathrm{trunc}}} &\leq \varphi \leq {(\varphi)^{\mathrm{trunc}}}, \quad \quad \quad \, {(\varphi_S)_{\mathrm{trunc}}} \leq \varphi_S \leq {(\varphi_S)^{\mathrm{trunc}}},\\ {(\psi)_{\mathrm{trunc}}} &\leq \psi \leq {(\psi)^{\mathrm{trunc}}}, \quad \quad {(w^2\psi_S)_{\mathrm{trunc}}} \leq w^2\psi_S \leq {(w^2\psi_S)^{\mathrm{trunc}}}, \end{align*} $$
for 
 $z=it$
,
$z=it$
, 
 $w=\pi t$
 and
$w=\pi t$
 and 
 $t\geq 1$
. A list of all N’s for each dimension d can be found on the ancillary files in the arXiv version of this paper (a file named Nnumbers). For instance, for
$t\geq 1$
. A list of all N’s for each dimension d can be found on the ancillary files in the arXiv version of this paper (a file named Nnumbers). For instance, for 
 $d=48$
, we have
$d=48$
, we have 
 $N=130$
.
$N=130$
.
To prove that condition (i) is satisfied, first we verify thatFootnote 5
- 
(I)  $ C_\varphi \geq 0$
, $ C_\varphi \geq 0$
,
since it directly shows that 
 $\varphi (it)>0$
 for
$\varphi (it)>0$
 for 
 $t>0$
, which implies that (since
$t>0$
, which implies that (since 
 $k/2$
 is odd)
$k/2$
 is odd) 
 $\varphi _S(it)<0$
 for
$\varphi _S(it)<0$
 for 
 $t>0$
. Next, we show thatFootnote 
6
$t>0$
. Next, we show thatFootnote 
6
 
- 
(II)  ${(\psi )_{\mathrm {trunc}}}$
 has only nonnegative coefficents in its q-expansion, ${(\psi )_{\mathrm {trunc}}}$
 has only nonnegative coefficents in its q-expansion,
which proves that 
 $\psi (it)>0$
 for
$\psi (it)>0$
 for 
 $t\geq 1$
 and that
$t\geq 1$
 and that 
 $-\pi ^2 \psi (it)<-\varphi _S(it)$
 for
$-\pi ^2 \psi (it)<-\varphi _S(it)$
 for 
 $t\geq 1$
. Next, we use Sturm’s method (which can be done via exact rational arithmetic evaluations) on the variable r to show that the polynomial
$t\geq 1$
. Next, we use Sturm’s method (which can be done via exact rational arithmetic evaluations) on the variable r to show that the polynomial 
- 
(III)  $- \pi _2^2 {(\psi )^{\mathrm {trunc}}} - {(\varphi _S)^{\mathrm {trunc}}}> 0$
 for $- \pi _2^2 {(\psi )^{\mathrm {trunc}}} - {(\varphi _S)^{\mathrm {trunc}}}> 0$
 for $0 < r< \gamma _2$
, $0 < r< \gamma _2$
,
where we use 
 $\pi _2 = \lceil \pi 10^{m}\rceil 10^{-m}$
 for
$\pi _2 = \lceil \pi 10^{m}\rceil 10^{-m}$
 for 
 $m=20,40,\ldots ,100$
 and
$m=20,40,\ldots ,100$
 and 
 $\gamma _2=\lceil e^{-\pi } 10^{m'}\rceil 10^{-m'}$
 for
$\gamma _2=\lceil e^{-\pi } 10^{m'}\rceil 10^{-m'}$
 for 
 $m'=2,5,8,11$
, where we select
$m'=2,5,8,11$
, where we select 
 $(m,m')$
 according to necessity (for large dimensions, more precision is sometimes required). From now on, whenever we apply Sturm’s method in the range
$(m,m')$
 according to necessity (for large dimensions, more precision is sometimes required). From now on, whenever we apply Sturm’s method in the range 
 $0 < r< \gamma _2$
, we will select
$0 < r< \gamma _2$
, we will select 
 $\gamma _2$
 as before. This shows that
$\gamma _2$
 as before. This shows that 
 $\pi ^2 \psi (it) <- {\varphi _S}(it)$
 for
$\pi ^2 \psi (it) <- {\varphi _S}(it)$
 for 
 $t\geq 1$
, and proves that condition (i) holds.
$t\geq 1$
, and proves that condition (i) holds.
Step 7. For condition (ii), we write
 $$ \begin{align*} {(w^2 \psi_S)_{\mathrm{trunc}}}+{(\varphi)_{\mathrm{trunc}}} & = [1,w,w^2][P_0(e^{-w}),P_1(e^{-w}),P_2(e^{-w})]^\top\\ -{(w^2 \psi_S)^{\mathrm{trunc}}}+{(\varphi)_{\mathrm{trunc}}} & = [1,w,w^2][Q_0(e^{-w}),Q_1(e^{-w}),Q_2(e^{-w})]^\top, \end{align*} $$
$$ \begin{align*} {(w^2 \psi_S)_{\mathrm{trunc}}}+{(\varphi)_{\mathrm{trunc}}} & = [1,w,w^2][P_0(e^{-w}),P_1(e^{-w}),P_2(e^{-w})]^\top\\ -{(w^2 \psi_S)^{\mathrm{trunc}}}+{(\varphi)_{\mathrm{trunc}}} & = [1,w,w^2][Q_0(e^{-w}),Q_1(e^{-w}),Q_2(e^{-w})]^\top, \end{align*} $$
where the 
 $P_i$
’s and
$P_i$
’s and 
 $Q_i$
’s are polynomials with integer coefficients and degree at most N. Note that
$Q_i$
’s are polynomials with integer coefficients and degree at most N. Note that 
 $P_2(e^{-w})={(\psi )_{\mathrm {trunc}}} (it)$
 and
$P_2(e^{-w})={(\psi )_{\mathrm {trunc}}} (it)$
 and 
 $Q_2(e^{-w})=-{(\psi )_{\mathrm {trunc}}} (it)-e^{-w(l+10)}$
, so
$Q_2(e^{-w})=-{(\psi )_{\mathrm {trunc}}} (it)-e^{-w(l+10)}$
, so 
 $-Q_2$
 and
$-Q_2$
 and 
 $P_2$
 have only positive coefficients. We then set
$P_2$
 have only positive coefficients. We then set 
 $x=e^{-w}$
 and
$x=e^{-w}$
 and 
 $$ \begin{align*} w_1(x) =\sum_{n=1}^N \frac{(1-x)^n}{n} \text{ and } w_2(x) = \sum_{n=1}^N \frac{(1-x)^n}{n}+\frac{(1-x)^{N+1}}{(N+1)x}, \end{align*} $$
$$ \begin{align*} w_1(x) =\sum_{n=1}^N \frac{(1-x)^n}{n} \text{ and } w_2(x) = \sum_{n=1}^N \frac{(1-x)^n}{n}+\frac{(1-x)^{N+1}}{(N+1)x}, \end{align*} $$
and note that 
 $w_1(x)<w < w_2(x)$
 for
$w_1(x)<w < w_2(x)$
 for 
 $0<x<1$
. We then conclude that condition (ii) is implied by the two conditions below:
$0<x<1$
. We then conclude that condition (ii) is implied by the two conditions below: 
- 
(IV)  $[1,w_{j}(x),w_{1}(x)^2][P_0(x),P_1(x),P_2(x)]^\top>0$
 for all $[1,w_{j}(x),w_{1}(x)^2][P_0(x),P_1(x),P_2(x)]^\top>0$
 for all $ j\in \{1,2\}$
 and $ j\in \{1,2\}$
 and $0<x<\gamma _2$
; $0<x<\gamma _2$
;
- 
(V)  $[1,w_{j}(x),w_{2}(x)^2][Q_0(x),Q_1(x),Q_2(x)]^\top>0$
 for all $[1,w_{j}(x),w_{2}(x)^2][Q_0(x),Q_1(x),Q_2(x)]^\top>0$
 for all $ j\in \{1,2\}$
 and $ j\in \{1,2\}$
 and $0<x<\gamma _2$
. $0<x<\gamma _2$
.
Both can now be verified using Sturm’s method.
 
Step 8. The proof that 
 $\widehat H(x)>0$
 for
$\widehat H(x)>0$
 for 
 $c<|x|^2 < a-2$
 is more involved. Let
$c<|x|^2 < a-2$
 is more involved. Let 
 $v(w) = -{w^2 \psi _S}+\varphi $
 and
$v(w) = -{w^2 \psi _S}+\varphi $
 and 
 $\Delta ^{-l/2}=\sum _{n\geq -l} \delta _{l,n} r^n$
. For
$\Delta ^{-l/2}=\sum _{n\geq -l} \delta _{l,n} r^n$
. For 
 $s=|x|^2>a-2$
, we have
$s=|x|^2>a-2$
, we have 
 $$ \begin{align*} \frac{\widehat H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)} & = \int_1^{\infty } \frac{v(\pi t)}{\Delta^{l/2}(it)}e^{- \pi t s}\mathrm{d} t + \int_1^{\infty } \frac{-\pi^2\psi(it)-\varphi_S(it)}{\Delta^{l/2}(it)}e^{- \pi |x|^2/t} t^{-d/2}\mathrm{d} t \\ & = \int_1^{\infty } v(\pi t)\bigg(\sum_{n=-l}^{N} \delta_{l,n} e^{-n\pi t}\bigg)e^{- \pi t s}\mathrm{d} t + \int_1^{\infty } v(\pi t)\bigg(\sum_{n>N} \delta_{l,n} e^{-n\pi t}\bigg)e^{- \pi t s}\mathrm{d} t \\ & \quad + \int_1^{\infty } \frac{-\pi^2\psi(it)-\varphi_S(it)}{\Delta^{l/2}(it)}e^{- \pi s/t} t^{-d/2}\mathrm{d} t. \end{align*} $$
$$ \begin{align*} \frac{\widehat H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)} & = \int_1^{\infty } \frac{v(\pi t)}{\Delta^{l/2}(it)}e^{- \pi t s}\mathrm{d} t + \int_1^{\infty } \frac{-\pi^2\psi(it)-\varphi_S(it)}{\Delta^{l/2}(it)}e^{- \pi |x|^2/t} t^{-d/2}\mathrm{d} t \\ & = \int_1^{\infty } v(\pi t)\bigg(\sum_{n=-l}^{N} \delta_{l,n} e^{-n\pi t}\bigg)e^{- \pi t s}\mathrm{d} t + \int_1^{\infty } v(\pi t)\bigg(\sum_{n>N} \delta_{l,n} e^{-n\pi t}\bigg)e^{- \pi t s}\mathrm{d} t \\ & \quad + \int_1^{\infty } \frac{-\pi^2\psi(it)-\varphi_S(it)}{\Delta^{l/2}(it)}e^{- \pi s/t} t^{-d/2}\mathrm{d} t. \end{align*} $$
In this way, the last two integrals above converge absolutely for 
 $s=|x|^2>0$
, while the first integral extends to a meromorphic function of
$s=|x|^2>0$
, while the first integral extends to a meromorphic function of 
 $s\in \mathbb {C}$
 with possible poles
$s\in \mathbb {C}$
 with possible poles 
 $s=a-2,a-4,\ldots ,2,0$
. Since
$s=a-2,a-4,\ldots ,2,0$
. Since 
 $\widehat H(x)$
 is entire in the variable s, the above representation now holds in the region
$\widehat H(x)$
 is entire in the variable s, the above representation now holds in the region 
 $\Re s \in (0,\infty )\setminus \{2,4,\ldots ,,a-2\}$
. In particular, since
$\Re s \in (0,\infty )\setminus \{2,4,\ldots ,,a-2\}$
. In particular, since 
 $\delta _{l,n}\geq 0$
,
$\delta _{l,n}\geq 0$
, 
 $v(\pi t)>0$
 and
$v(\pi t)>0$
 and 
 $-\pi ^2\psi (it)-\varphi _S(it)>0$
 for
$-\pi ^2\psi (it)-\varphi _S(it)>0$
 for 
 $t\geq 1$
, we obtain the following inequality in the range
$t\geq 1$
, we obtain the following inequality in the range 
 $s>0$
:
$s>0$
: 
 $$ \begin{align*}\frac{\widehat H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)}> \widetilde{ \int}_{1}^\infty {v(\pi t)}\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t , \end{align*} $$
$$ \begin{align*}\frac{\widehat H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)}> \widetilde{ \int}_{1}^\infty {v(\pi t)}\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t , \end{align*} $$
where by 
 $ \widetilde { \int }$
 we mean the meromorphic extension of the function defined by this integral. Now let
$ \widetilde { \int }$
 we mean the meromorphic extension of the function defined by this integral. Now let 
 $A(w)$
 be such that
$A(w)$
 be such that 
 $v(w)-A(w)=O(r^l)$
. Then the right-hand side above is
$v(w)-A(w)=O(r^l)$
. Then the right-hand side above is 
 $$ \begin{align*} & \widetilde{ \int}_{1}^\infty A(\pi t)\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t + { \int}_{1}^\infty (v(\pi t)-A(\pi t))\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t \\ &> \widetilde{ \int}_{1}^\infty A(\pi t)\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t \\ & \quad \quad + { \int}_{1}^\infty (-{(w^2 \psi_S)^{\mathrm{trunc}}}(it)+{(\varphi)_{\mathrm{trunc}}}(it)-A(\pi t ))\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t \\ & = \widetilde{ \int}_{1}^\infty (-{(w^2 \psi_S)^{\mathrm{trunc}}}(it)+{(\varphi)_{\mathrm{trunc}}}(it))\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t, \end{align*} $$
$$ \begin{align*} & \widetilde{ \int}_{1}^\infty A(\pi t)\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t + { \int}_{1}^\infty (v(\pi t)-A(\pi t))\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t \\ &> \widetilde{ \int}_{1}^\infty A(\pi t)\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t \\ & \quad \quad + { \int}_{1}^\infty (-{(w^2 \psi_S)^{\mathrm{trunc}}}(it)+{(\varphi)_{\mathrm{trunc}}}(it)-A(\pi t ))\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t \\ & = \widetilde{ \int}_{1}^\infty (-{(w^2 \psi_S)^{\mathrm{trunc}}}(it)+{(\varphi)_{\mathrm{trunc}}}(it))\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) e^{-\pi t s} \mathrm{d} t, \end{align*} $$
for 
 $s>0$
. After a change of variables
$s>0$
. After a change of variables 
 $w=\pi t$
, we conclude that
$w=\pi t$
, we conclude that 
 $$ \begin{align*} \frac{\pi \widehat H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)}> \widetilde{\int}_{\pi}^\infty \bigg( \sum_{m=-a+2}^{2N-l-2} p_m(w)e^{-mw} \bigg) e^{-w s}\mathrm{d} w \end{align*} $$
$$ \begin{align*} \frac{\pi \widehat H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)}> \widetilde{\int}_{\pi}^\infty \bigg( \sum_{m=-a+2}^{2N-l-2} p_m(w)e^{-mw} \bigg) e^{-w s}\mathrm{d} w \end{align*} $$
for 
 $s>0$
, where
$s>0$
, where 
 $$ \begin{align*}(-{(w^2 \psi_S)^{\mathrm{trunc}}}(it)+{(\varphi)_{\mathrm{trunc}}}(it))\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) =: \sum_{m=-a+2}^{2N-l-2} p_m(w)e^{-mw}. \end{align*} $$
$$ \begin{align*}(-{(w^2 \psi_S)^{\mathrm{trunc}}}(it)+{(\varphi)_{\mathrm{trunc}}}(it))\bigg(\sum_{n= -l}^{N-l-2} \delta_{l,n} e^{-n\pi t} \bigg) =: \sum_{m=-a+2}^{2N-l-2} p_m(w)e^{-mw}. \end{align*} $$
Let now 
 $M=\lfloor (2N-l-2)/2^{m}\rfloor $
 with
$M=\lfloor (2N-l-2)/2^{m}\rfloor $
 with 
 $m=4,3,2,1,0$
 (depending on precision). Let
$m=4,3,2,1,0$
 (depending on precision). Let 
 $$ \begin{align*} A_1(w)&=\sum_{m=-a+2}^{M-1} p_m(w)e^{-mw} + e^{-Mw}w^2[w^2](p_M(w)) \\ A_2(w)&=-A_1(w)+\sum_{m=-a+2}^{2N-l-2} p_m(w)e^{-mw}. \end{align*} $$
$$ \begin{align*} A_1(w)&=\sum_{m=-a+2}^{M-1} p_m(w)e^{-mw} + e^{-Mw}w^2[w^2](p_M(w)) \\ A_2(w)&=-A_1(w)+\sum_{m=-a+2}^{2N-l-2} p_m(w)e^{-mw}. \end{align*} $$
Let 
 $x=e^{-w}$
. We then show that
$x=e^{-w}$
. We then show that 
- 
(VI)  $[1,w_{j}(x),w_{2}(x)^2][[w^0]A_2,[w^1]A_2,[w^2]A_2]^\top>0$
 for all $[1,w_{j}(x),w_{2}(x)^2][[w^0]A_2,[w^1]A_2,[w^2]A_2]^\top>0$
 for all $ j\in \{1,2\}$
 and $ j\in \{1,2\}$
 and $0<x<\gamma _2$
. $0<x<\gamma _2$
.
This proves that
 $$ \begin{align} \frac{\pi \widehat H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)}> \widetilde{\int}_{\pi}^\infty A_1(w) e^{-w s}\mathrm{d} w. \end{align} $$
$$ \begin{align} \frac{\pi \widehat H(x)}{\sin^2(\tfrac{\pi}{2} |x|^2)}> \widetilde{\int}_{\pi}^\infty A_1(w) e^{-w s}\mathrm{d} w. \end{align} $$
Let now 
 $\mathcal {R}$
 be the following ‘rationalization’ operator
$\mathcal {R}$
 be the following ‘rationalization’ operator 
 $$ \begin{align*}P(s)=\sum c_{i,j,n} \pi^i e^{-\pi j} s^n \mapsto \mathcal{R}(P)(s):= \sum \widetilde c_{i,j,n} s^n, \end{align*} $$
$$ \begin{align*}P(s)=\sum c_{i,j,n} \pi^i e^{-\pi j} s^n \mapsto \mathcal{R}(P)(s):= \sum \widetilde c_{i,j,n} s^n, \end{align*} $$
where 
 $\widetilde c_{i,j,n}=\min _{\alpha ,\beta \in \{1,2\}}\{c_{i,j,n} \pi _\alpha ^i \gamma _\beta ^j\}$
 and
$\widetilde c_{i,j,n}=\min _{\alpha ,\beta \in \{1,2\}}\{c_{i,j,n} \pi _\alpha ^i \gamma _\beta ^j\}$
 and 
 $\pi _1,\pi _2,\gamma _1,\gamma _2$
 are rational approximations of
$\pi _1,\pi _2,\gamma _1,\gamma _2$
 are rational approximations of 
 $\pi $
 and
$\pi $
 and 
 $\gamma =e^{-\pi }$
 such that
$\gamma =e^{-\pi }$
 such that 
 $$ \begin{align*}\pi_1 < \pi < \pi_2 \quad \text{and} \quad \gamma_1 < \gamma<\gamma_2. \end{align*} $$
$$ \begin{align*}\pi_1 < \pi < \pi_2 \quad \text{and} \quad \gamma_1 < \gamma<\gamma_2. \end{align*} $$
Usually these rational approximations are taken to be m-digit truncations (in base 
 $10$
) from below and above, with
$10$
) from below and above, with 
 $m\in \{10,15,20,\ldots ,50\}$
 depending on the required precision. Observe now that if
$m\in \{10,15,20,\ldots ,50\}$
 depending on the required precision. Observe now that if 
 $p(w)$
 is a quadratic polynomial with coefficients in
$p(w)$
 is a quadratic polynomial with coefficients in 
 $\mathbb {Q}[\pi ]$
, then we obtain that
$\mathbb {Q}[\pi ]$
, then we obtain that 
 $$ \begin{align*} & e^{\pi s} \int_\pi^\infty p(w)e^{-mw}e^{-sw} \mathrm{d} w \\ & = e^{-\pi m}\int_0^\infty p(w+\pi)e^{-(s+m)w} \mathrm{d} w \\ & = e^{-\pi m} \sum_{j=0}^2 \frac{j)}{(s+m)^{j+1}} \\ & = e^{-\pi m} \frac{(s+m)^3[w^0](p(w+\pi))+(s+m)^2[w^1](p(w+\pi))+2(s+m)[w^2](p(w+\pi))}{(s+m)^4} \\ & \geq \frac{\mathcal{R}(e^{-\pi m}(s+m)[w^0](p(w+\pi)))}{(s+m)^2}+\frac{\mathcal{R}(e^{-\pi m}[w^1](p(w+\pi)))}{(s+m)^2}\\ &\quad +\frac{\mathcal{R}(2e^{-\pi m}(s+m)[w^2](p(w+\pi)))}{(s+m)^4}\\ & =: {B_m[p](s)}. \end{align*} $$
$$ \begin{align*} & e^{\pi s} \int_\pi^\infty p(w)e^{-mw}e^{-sw} \mathrm{d} w \\ & = e^{-\pi m}\int_0^\infty p(w+\pi)e^{-(s+m)w} \mathrm{d} w \\ & = e^{-\pi m} \sum_{j=0}^2 \frac{j)}{(s+m)^{j+1}} \\ & = e^{-\pi m} \frac{(s+m)^3[w^0](p(w+\pi))+(s+m)^2[w^1](p(w+\pi))+2(s+m)[w^2](p(w+\pi))}{(s+m)^4} \\ & \geq \frac{\mathcal{R}(e^{-\pi m}(s+m)[w^0](p(w+\pi)))}{(s+m)^2}+\frac{\mathcal{R}(e^{-\pi m}[w^1](p(w+\pi)))}{(s+m)^2}\\ &\quad +\frac{\mathcal{R}(2e^{-\pi m}(s+m)[w^2](p(w+\pi)))}{(s+m)^4}\\ & =: {B_m[p](s)}. \end{align*} $$
We deduce that (4) is bounded from below by
 $$ \begin{align*} e^{-\pi s}\bigg(\sum_{m=-a+2}^{M-1} B_m(p_m)(s) + B_M(w^2[w^2](p_M(w))) \bigg) =: e^{-\pi s}Q(s), \end{align*} $$
$$ \begin{align*} e^{-\pi s}\bigg(\sum_{m=-a+2}^{M-1} B_m(p_m)(s) + B_M(w^2[w^2](p_M(w))) \bigg) =: e^{-\pi s}Q(s), \end{align*} $$
where 
 $Q(s)$
 is a rational function with rational coefficients. Finally, we write
$Q(s)$
 is a rational function with rational coefficients. Finally, we write 
 $Q=Q_{num}/Q_{den}$
, for polynomials
$Q=Q_{num}/Q_{den}$
, for polynomials 
 $Q_{num}$
 and
$Q_{num}$
 and 
 $Q_{den}$
 and obtain that
$Q_{den}$
 and obtain that 
 $\widehat H(x)>0$
 for
$\widehat H(x)>0$
 for 
 $c<|x|^2 < a-2$
 holds true if the following condition is satisfied
$c<|x|^2 < a-2$
 holds true if the following condition is satisfied 
- 
(VII)  $Q_{den}(s) \prod _{j=0}^{a/2-1} (s-2j)^{-2}$
 has only nonnegative coefficients and $Q_{den}(s) \prod _{j=0}^{a/2-1} (s-2j)^{-2}$
 has only nonnegative coefficients and $Q_{num}(s)>0$
 for $Q_{num}(s)>0$
 for $c<s<a-2$
. $c<s<a-2$
.
This can be checked by Sturm’s method again. Notice that since we have used only strict inequalities, this shows that 
 $\{|x|^2 : \widehat H(x)=0 \text { and } |x|>c_d\}=\{a_d,a_d+2,\ldots \}$
.
$\{|x|^2 : \widehat H(x)=0 \text { and } |x|>c_d\}=\{a_d,a_d+2,\ldots \}$
.
We then check that conditions (I), (II), (III), (IV), (V), (VI) and (VII) are satisfied using rational arithmetic only, producing in this way a mathematical proof. The necessary algorithm to check this positivity conditions can be found in the ancillary files in the arXiv submission of this paper (a file named Postest; please also read the file Readme).
 
Step 9. Finally, for 
 $d=48$
, it remains to show the claim that
$d=48$
, it remains to show the claim that 
 $\{|x|^2:H(x)< 0\}\cap (0,10) = (6,8)$
. The method is exactly the same as the one employed on Step 8, except we start from
$\{|x|^2:H(x)< 0\}\cap (0,10) = (6,8)$
. The method is exactly the same as the one employed on Step 8, except we start from 
 $H(x)$
 and
$H(x)$
 and 
 $-{w^2 \psi _S}-\varphi $
 and show, after essentially the same procedure, that the resulting rational function
$-{w^2 \psi _S}-\varphi $
 and show, after essentially the same procedure, that the resulting rational function 
 $Q(s)$
 divided by
$Q(s)$
 divided by 
 $(s-6)(s-8)$
 is positive in the interval
$(s-6)(s-8)$
 is positive in the interval 
 $0<s<10$
.
$0<s<10$
.
This finishes the proof of Theorem 4.
9 Proof of Theorems 2 and 5
 Noting that 
 $A_d = (1,\sup (K_d)]\setminus K_d$
, we conclude that a packing P is K-admissible if and only if it avoids
$A_d = (1,\sup (K_d)]\setminus K_d$
, we conclude that a packing P is K-admissible if and only if it avoids 
 $A_d$
. Thus, Theorems 2 and 5 are equivalent. The proof of Theorem 5 follows directly from Theorem 4. Let
$A_d$
. Thus, Theorems 2 and 5 are equivalent. The proof of Theorem 5 follows directly from Theorem 4. Let 
 $P=\Lambda +Y+{\tfrac 12}B_d$
 be a
$P=\Lambda +Y+{\tfrac 12}B_d$
 be a 
 $K_d$
-admissible periodic sphere packing. Poisson summation over
$K_d$
-admissible periodic sphere packing. Poisson summation over 
 $\Lambda +Y-Y$
 with the function
$\Lambda +Y-Y$
 with the function 
 $F(x)=H(\sqrt {a_d}x)$
 and H as in Theorem 4 shows that
$F(x)=H(\sqrt {a_d}x)$
 and H as in Theorem 4 shows that 
 $$ \begin{align*}H(0)\#Y \geq \sum_{y,y'\in Y} \sum_{x\in L} F(x+y-y') = \frac{1}{\mathrm{vol}(\mathbb{R}^d/L)} \sum_{x^*\in L^*} \widehat F(x^*)\bigg|\sum_{y\in Y} e^{2\pi i y \cdot x^*}\bigg|^2 \geq \frac{\widehat H(0)a_d^{-d/2}(\#Y)^2}{\mathrm{vol}(\mathbb{R}^d/L)}; \end{align*} $$
$$ \begin{align*}H(0)\#Y \geq \sum_{y,y'\in Y} \sum_{x\in L} F(x+y-y') = \frac{1}{\mathrm{vol}(\mathbb{R}^d/L)} \sum_{x^*\in L^*} \widehat F(x^*)\bigg|\sum_{y\in Y} e^{2\pi i y \cdot x^*}\bigg|^2 \geq \frac{\widehat H(0)a_d^{-d/2}(\#Y)^2}{\mathrm{vol}(\mathbb{R}^d/L)}; \end{align*} $$
hence, 
 $\mathrm {dens}(P)\leq \mathrm {vol} \left ( B_d\right ) \left ( \frac {\sqrt {a_d}}{2}\right )^d$
, which is attained by any even unimodular extremal lattice. Poisson summation implies that equality is attained for a lattice packing (
$\mathrm {dens}(P)\leq \mathrm {vol} \left ( B_d\right ) \left ( \frac {\sqrt {a_d}}{2}\right )^d$
, which is attained by any even unimodular extremal lattice. Poisson summation implies that equality is attained for a lattice packing (
 $\#Y=1$
) if and only if for every
$\#Y=1$
) if and only if for every 
 $v\in \Lambda ^*$
, we have
$v\in \Lambda ^*$
, we have 
 $|v|^2\in \{a_d,a_d+2,\ldots \}$
. Then, as in the proof of Theorem 1, one shows that
$|v|^2\in \{a_d,a_d+2,\ldots \}$
. Then, as in the proof of Theorem 1, one shows that 
 $\sqrt {a_d}\Lambda $
 is an even unimodular extremal lattice.
$\sqrt {a_d}\Lambda $
 is an even unimodular extremal lattice.
Acknowledgements
The authors thank João P. Ramos, Henry Cohn and Danlyo Radchenko for fruitful discussions on the elaboration of this paper. The first author acknowledges support from the following funding agencies: The Office of Naval Research GRANT14201749 (award number N629092412126), The Serrapilheira Institute (Serra-2211-41824), FAPERJ \hbox{(E-26/200.209/2023)} and CNPq (309910/2023-4). The second author acknowledges the support of CNPq (141446/2023-4) and FAPERJ (E-26/202.492/2022) scholarships.
Competing interest
The authors have no competing interest to declare.
Data availability statement
Ancillary files with code and data are available in the arXiv submission of this paper: arXiv:2308.03925 [math.NT].
 
 









 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 




























