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2 results

  • 14 - ★ Functions of Eigenvalues of Symmetric Matrices

  • from Part III - Convex Functions
  • Fatma Kılınç-Karzan, Carnegie Mellon University, Pennsylvania, Arkadi Nemirovski, Georgia Institute of Technology
  • Book:
    Essential Mathematics for Convex Optimization
    Published online:
    22 October 2025
    Print publication:
    26 June 2025, pp 212-217

  • Summary

    In this chapter, we demonstrate that (a) substituting the vector of eigenvalues of a symmetric n x n matrix into a convex permutation symmetric function of n real variables results in a convex function of the matrix, and (b) that if g is a convex function on the real axis, and G is the set of symmetric matrices of a given size with spectrum in the domain of g, then G is a convex set, and when X is a matrix from G, the trace of the matrix g(X), is a convex function of X; here g(X) is the matrix acting at a spectral subspace of X associated with eigenvalue v as multiplication by g(v); both these facts will be heavily used when speaking about cone-convexity is chapter 21.