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Related papers: Shape, Scale, and Minimality of Matrix Ranges

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For finite-dimensional operator systems $\mathcal{S}_{\mathsf T}$, ${\mathsf T} \in B({\mathcal H})^d$, we show that the local lifting property and $1$-exactness of $\mathcal{S}_{\mathsf T}$ may be characterized by measurements of the…

Functional Analysis · Mathematics 2021-06-09 Benjamin Passer , Vern I. Paulsen

This article shows the existence of a class of closed bounded matrix convex sets which do not have absolute extreme points. The sets we consider are noncommutative sets, $K_X$, formed by taking matrix convex combinations of a single tuple…

Operator Algebras · Mathematics 2022-02-24 Eric Evert

We study the matrix range of a tuple of compact operators on a Hilbert space and examine the notions of minimal, nonsingular, and fully compressed tuples. In this pursuit, we refine previous results by characterizing nonsingular compact…

Operator Algebras · Mathematics 2019-06-21 Benjamin Passer , Orr Moshe Shalit

We define the (convex) joint numerical range for an infinite family of compact operators in a Hilbert space H. We use this set to determine whether a self-adjoint compact operator A with {||A||, -||A||} in its spectrum is minimal respect to…

Functional Analysis · Mathematics 2023-03-08 Tamara Bottazzi , Alejandro Varela

We investigate $(0,1)$-matrices that are {\em convex}, which means that the ones are consecutive in every row and column. These matrices occur in discrete tomography. The notion of ranked essential sets, known for permutation matrices, is…

Combinatorics · Mathematics 2021-01-13 Richard A. Brualdi , Geir Dahl

A convex envelope for the problem of finding the best approximation to a given matrix with a prescribed rank is constructed. This convex envelope allows the usage of traditional optimization techniques when additional constraints are added…

Functional Analysis · Mathematics 2016-08-30 Fredrik Andersson , Marcus Carlsson , Carl Olsson

A matrix convex set is a set of the form $\mathcal{S} = \cup_{n\geq 1}\mathcal{S}_n$ (where each $\mathcal{S}_n$ is a set of $d$-tuples of $n \times n$ matrices) that is invariant under UCP maps from $M_n$ to $M_k$ and under formation of…

Operator Algebras · Mathematics 2025-04-15 Kenneth R. Davidson , Adam Dor-On , Orr Shalit , Baruch Solel

This note treats a simple minded question: what does a typical random matrix range look like? We study the relationship between various modes of convergence for tuples of operators, on the one hand, and continuity of matrix ranges with…

Operator Algebras · Mathematics 2023-05-10 Malte Gerhold , Orr Shalit

To every convex body $K \subseteq \mathbb{R}^d$, one may associate a minimal matrix convex set $\mathcal{W}^{\textrm{min}}(K)$, and a maximal matrix convex set $\mathcal{W}^{\textrm{max}}(K)$, which have $K$ as their ground level. The main…

Operator Algebras · Mathematics 2019-07-04 Benjamin Passer , Orr Shalit , Baruch Solel

We develop tractable convex relaxations for rank-constrained quadratic optimization problems over $n \times m$ matrices, a setting for which tractable relaxations are typically only available when the objective or constraints admit spectral…

Optimization and Control · Mathematics 2026-05-22 Ryan Cory-Wright , Jean Pauphilet

We study the problem of determining whether a given frame is scalable, and when it is, understanding the set of all possible scalings. We show that for most frames this is a relatively simple task in that the frame is either not scalable or…

Functional Analysis · Mathematics 2013-01-31 Jameson Cahill , Xuemei Chen

We continue the analysis in [3] of matrix convex functions of a fixed order defined in a real interval by differential methods as opposed to the characterization in terms of divided differences given by Kraus [5]. We amend and improve some…

Operator Algebras · Mathematics 2007-05-23 Frank Hansen , Jun Tomiyama

A new class of affine scaling matrices for the interior point Newton-type methods is considered to solve the nonlinear systems with simple bounds. We review the essential properties of a scaling matrix and consider several well-known…

Optimization and Control · Mathematics 2019-04-22 Aydin Ayanzadeh , Shokoufeh Yazdanian , Ehsan Shahamatnia

Concatenating matrices is a common technique for uncovering shared structures in data through singular value decomposition (SVD) and low-rank approximations. The fundamental question arises: How does the singular value spectrum of the…

Machine Learning · Computer Science 2025-07-01 Maksym Shamrai

A planar point set is in convex position precisely when it has a convex polygonization, that is, a polygonization with maximum interior angle measure at most \pi. We can thus talk about the convexity of a set of points in terms of the…

Computational Geometry · Computer Science 2014-09-16 Danny Rorabaugh

Results on matrix canonical forms are used to give a complete description of the higher rank numerical range of matrices arising from the study of quantum error correction. It is shown that the set can be obtained as the intersection of…

Functional Analysis · Mathematics 2011-02-10 Chi-Kwong Li , Nung-Sing Sze

We analyze matrix convex functions of a fixed order defined on a real interval by differential methods as opposed to the characterization in terms of divided differences given by Kraus. We obtain for each order conditions for matrix…

Operator Algebras · Mathematics 2007-05-23 Frank Hansen , Jun Tomiyama

We consider inhomogeneous matrix products over max-plus algebra, where the matrices in the product satisfy certain assumptions under which the matrix products of sufficient length be rank-one, as it was shown in [6][L. Shue, B.D.O.…

Rings and Algebras · Mathematics 2019-04-15 Arthur Kennedy Cochran Patrick , Sergei Sergeev , Štefan Berežný

The local boundedness of classes of operators is analyzed on different subsets directly related to their Fitzpatrick functions and characterizations of the topological vector spaces for which that local boundedness holds is given in terms…

Functional Analysis · Mathematics 2012-07-13 M. D. Voisei

This paper deals with the problem of robust matrix completion -- retrieving a low-rank matrix and a sparse matrix from the compressed counterpart of their superposition. Though seemingly not an unresolved issue, we point out that the…

Information Theory · Computer Science 2024-10-10 Yinjian Wang
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