A spectrahedral representation of the first derivative relaxation of the positive semidefinite cone
Abstract
If $X$ is an $n\times n$ symmetric matrix, then the directional derivative of $X \mapsto \det(X)$ in the direction $I$ is the elementary symmetric polynomial of degree $n-1$ in the eigenvalues of $X$. This is a polynomial in the entries of $X$ with the property that it is hyperbolic with respect to the direction $I$. The corresponding hyperbolicity cone is a relaxation of the positive semidefinite (PSD) cone known as the first derivative relaxation (or Renegar derivative) of the PSD cone. A spectrahedal cone is a convex cone that has a representation as the intersection of a subspace with the cone of PSD matrices in some dimension. We show that the first derivative relaxation of the PSD cone is a spectrahedral cone, and give an explicit spectrahedral description of size $\binom{n+1}{2}-1$. The construction provides a new explicit example of a hyperbolicity cone that is also a spectrahedron. This is consistent with the generalized Lax conjecture, which conjectures that every hyperbolicity cone is a spectrahedron.
- Publication:
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arXiv e-prints
- Pub Date:
- July 2017
- DOI:
- arXiv:
- arXiv:1707.09150
- Bibcode:
- 2017arXiv170709150S
- Keywords:
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- Mathematics - Optimization and Control
- E-Print:
- 10 pages, fixed typos, more direct proof of Lemma 4