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Two Results on the Size of Spectrahedral Descriptions

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2016

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SIAM Journal on Optimization. 2016, 26(1), pp. 589-601. ISSN 1052-6234. eISSN 1095-7189. Available under: doi: 10.1137/15M1030789

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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 $r$ of the matrices in the description by linear matrix inequalities. We show that for the $n$-dimensional unit ball $r$ is at least $\frac{n}{2}$. If $n=2^k+1$, then we actually have $r=n$. The same holds true for any compact convex set in $\mathbb{R}^n$ defined by a quadratic polynomial. Furthermore, we show that for a convex region in $\mathbb{R}^3$ whose algebraic boundary is smooth and defined by a cubic polynomial, we have that $r$ is at least five. More precisely, we show that if $A,B,C \in {Sym}_r(\mathbb{R})$ are real symmetric matrices such that $f(x,y,z)=\det(I_r+A x+B y+C z)$ is a cubic polynomial, then the surface in complex projective three-space with affine equation $f(x,y,z)=0$ is singular.

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510 Mathematik

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ISO 690KUMMER, Mario, 2016. Two Results on the Size of Spectrahedral Descriptions. In: SIAM Journal on Optimization. 2016, 26(1), pp. 589-601. ISSN 1052-6234. eISSN 1095-7189. Available under: doi: 10.1137/15M1030789
BibTex
@article{Kummer2016-02-25Resul-34059,
  year={2016},
  doi={10.1137/15M1030789},
  title={Two Results on the Size of Spectrahedral Descriptions},
  number={1},
  volume={26},
  issn={1052-6234},
  journal={SIAM Journal on Optimization},
  pages={589--601},
  author={Kummer, Mario}
}
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