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1. Verfasser: Chen, Xin
Format: Preprint
Veröffentlicht: 2026
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Online-Zugang:https://arxiv.org/abs/2605.18620
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author Chen, Xin
author_facet Chen, Xin
contents We study the standard quadratic optimization problem over the simplex when the objective matrix is drawn from the Gaussian Orthogonal Ensemble (GOE). Let \(κ_n\) denote the support size of the almost surely unique global optimizer. We prove \[ \Prob(κ_n>1)\sim 2\sqrt{2π}\,\frac{\sqrt{\log n}}{n}. \] The proof combines an exact two-coordinate condition for edge improvement with a product formula obtained by conditioning on the diagonal order statistics. Boundary-layer estimates identify the leading contribution and show that supports of size at least three are negligible. Consequently, the minimum-diagonal vertex is globally optimal with probability tending to one, with an explicit first-order correction.
format Preprint
id arxiv_https___arxiv_org_abs_2605_18620
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Singleton Optimality in Standard Quadratic Programs with the GOE
Chen, Xin
Optimization and Control
We study the standard quadratic optimization problem over the simplex when the objective matrix is drawn from the Gaussian Orthogonal Ensemble (GOE). Let \(κ_n\) denote the support size of the almost surely unique global optimizer. We prove \[ \Prob(κ_n>1)\sim 2\sqrt{2π}\,\frac{\sqrt{\log n}}{n}. \] The proof combines an exact two-coordinate condition for edge improvement with a product formula obtained by conditioning on the diagonal order statistics. Boundary-layer estimates identify the leading contribution and show that supports of size at least three are negligible. Consequently, the minimum-diagonal vertex is globally optimal with probability tending to one, with an explicit first-order correction.
title Singleton Optimality in Standard Quadratic Programs with the GOE
topic Optimization and Control
url https://arxiv.org/abs/2605.18620