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Main Authors: Bandeira, Afonso S., Mixon, Dustin G., Steinerberger, Stefan
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2405.06154
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author Bandeira, Afonso S.
Mixon, Dustin G.
Steinerberger, Stefan
author_facet Bandeira, Afonso S.
Mixon, Dustin G.
Steinerberger, Stefan
contents We prove the existence of a positive semidefinite matrix $A \in \mathbb{R}^{n \times n}$ such that any decomposition into rank-1 matrices has to have factors with a large $\ell^1-$norm, more precisely $$ \sum_{k} x_k x_k^*=A \quad \implies \quad \sum_k \|x_k\|^2_{1} \geq c \sqrt{n} \|A\|_{1},$$ where $c$ is independent of $n$. This provides a lower bound for the Balan--Jiang matrix problem. The construction is probabilistic.
format Preprint
id arxiv_https___arxiv_org_abs_2405_06154
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A lower bound for the Balan--Jiang matrix problem
Bandeira, Afonso S.
Mixon, Dustin G.
Steinerberger, Stefan
Functional Analysis
We prove the existence of a positive semidefinite matrix $A \in \mathbb{R}^{n \times n}$ such that any decomposition into rank-1 matrices has to have factors with a large $\ell^1-$norm, more precisely $$ \sum_{k} x_k x_k^*=A \quad \implies \quad \sum_k \|x_k\|^2_{1} \geq c \sqrt{n} \|A\|_{1},$$ where $c$ is independent of $n$. This provides a lower bound for the Balan--Jiang matrix problem. The construction is probabilistic.
title A lower bound for the Balan--Jiang matrix problem
topic Functional Analysis
url https://arxiv.org/abs/2405.06154