Two results on the size of spectrahedral descriptions

preprint2015arXivOpen access

Abstract

A spectrahedron is a set defined by a linear matrix inequality. Given a spectrahedron we are interested in the question of the smallest possible size rr of the matrices in the description by linear matrix inequalities. We show that for the nn-dimensional unit ball rr is at least n2\frac{n}{2}. If n=2k+1n=2^k+1, then we actually have r=nr=n. The same holds true for any compact convex set in Rn\mathbb{R}^n defined by a quadratic polynomial. Furthermore, we show that for a convex region in R3\mathbb{R}^3 whose algebraic boundary is smooth and defined by a cubic polynomial we have that rr is at least five. More precisely, we show that if A,B,CA,B,C are real symmetric matrices such that f(x,y,z)=det⁡(I+Ax+By+Cz)f(x,y,z)=\det(I+A x+B y+C z) is a cubic polynomial, the surface in complex projective three-space with affine equation f(x,y,z)=0f(x,y,z)=0 is singular.

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