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Related papers: $k$-Positive Maps: New Characterizations and a Gen…

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This paper investigates the properties of Choi polynomials and their fundamental role in the theory of positive linear maps between matrix algebras. By focusing on Hermitian symmetric biquadratic forms, we establish a connection between the…

Quantum Physics · Physics 2026-05-01 Minh Toan Ho , Thanh Hieu Le , Cong Trinh Le , Hiroyuki Osaka

We use a new idea that emerged in the examination of exposed positive maps between matrix algebras to investigate in more detail the difference between positive maps on $M_2(C)$ and $M_3(C)$. Our main tool stems from classical Grothendieck…

Mathematical Physics · Physics 2016-04-08 Wladyslaw A. Majewski , Tomasz I. Tylec

We study factorization and dilation properties of Markov maps between von Neumann algebras equipped with normal faithful states, i.e., completely positive unital maps which preserve the given states and also intertwine their automorphism…

Operator Algebras · Mathematics 2015-05-19 Uffe Haagerup , Magdalena Musat

An alternative, geometrical proof of a known theorem concerning the decomposition of positive maps of the matrix algebra $M_{2}(\mathbb{C})$ has been presented. The premise of the proof is the identification of positive maps with operators…

Mathematical Physics · Physics 2015-06-04 Marek Miller , Robert Olkiewicz

Using pure entangled Schmidt states, we show that m-positivity of a map is bounded by the ranks of its negative Kraus matrices. We also give an algebraic condition for a map to be m-positive. We interpret these results in the context of…

Quantum Physics · Physics 2007-05-23 Aik-meng Kuah , E. C. G. Sudarshan

The problem of decomposing a given covariance matrix as the sum of a positive semi-definite matrix of given rank and a positive semi-definite diagonal matrix, is considered. We present a projection-type algorithm to address this problem.…

Optimization and Control · Mathematics 2018-06-13 Valentina Ciccone , Augusto Ferrante , Mattia Zorzi

A theoretical framework for non-negative matrix factorization based on generalized dual Kullback-Leibler divergence, which includes members of the exponential family of models, is proposed. A family of algorithms is developed using this…

Machine Learning · Statistics 2019-05-20 Karthik Devarajan

This paper establishes new Positivstellens\"atze for polynomials that are positive on sets defined by polynomial matrix inequalities (PMIs). We extend the classical Handelman and Krivine-Stengle theorems from the scalar inequality setting…

Optimization and Control · Mathematics 2025-09-03 Feng Guo

We study several variants of decomposing a symmetric matrix into a sum of a low-rank positive semidefinite matrix and a diagonal matrix. Such decompositions have applications in factor analysis and they have been studied for many decades.…

Optimization and Control · Mathematics 2023-10-02 Levent Tunçel , Stephen A. Vavasis , Jingye Xu

This paper studies the problem of decomposing a low-rank positive-semidefinite matrix into symmetric factors with binary entries, either $\{\pm 1\}$ or $\{0,1\}$. This research answers fundamental questions about the existence and…

Data Structures and Algorithms · Computer Science 2019-08-01 Richard Kueng , Joel A. Tropp

Exposed positive maps in matrix algebras define a dense subset of extremal maps. We provide a class of indecomposable positive maps in the algebra of 2n x 2n complex matrices with n>1. It is shown that these maps are exposed and hence…

Quantum Physics · Physics 2012-12-11 Gniewomir Sarbicki , Dariusz Chruściński

This article introduces PnCP, a MATLAB toolbox for constructing positive maps which are not completely positive. We survey optimization and sum of squares relaxation techniques to find the most numerically efficient methods for this…

Optimization and Control · Mathematics 2020-01-07 Abhishek Bhardwaj

We study the problem of testing $k$-block-positivity via symmetric $N$-extendibility by taking the tensor product with a $k$-dimensional maximally entangled state. We exploit the unitary symmetry of the maximally entangled state to reduce…

Quantum Physics · Physics 2026-01-27 Qian Chen , Benoît Collins , Omar Fawzi

It is proven that a certain class of positive maps in the matrix algebra $M_n$ consists of optimal maps, i.e. maps from which one cannot subtract any completely positive map without loosing positivity. This class provides a generalization…

Quantum Physics · Physics 2023-04-12 Anindita Bera , Gniewomir Sarbicki , Dariusz Chruściński

We review the basic theory of More Sums Than Differences (MSTD) sets, specifically their existence, simple constructions of infinite families, the proof that a positive percentage of sets under the uniform binomial model are MSTD but not if…

Number Theory · Mathematics 2011-07-15 Geoffrey Iyer , Oleg Lazarev , Steven J. Miller , Liyang Zhang

Let $K=\mathbb Q(\sqrt D)$ be a real quadratic field. We consider the additive semigroup $\mathcal O_K^+(+)$ of totally positive integers in $K$ and determine its generators (indecomposable integers) and relations; they can be nicely…

Number Theory · Mathematics 2020-08-11 Tomáš Hejda , Vítězslav Kala

This paper considers the problem of positive semidefinite factorization (PSD factorization), a generalization of exact nonnegative matrix factorization. Given an $m$-by-$n$ nonnegative matrix $X$ and an integer $k$, the PSD factorization…

Optimization and Control · Mathematics 2018-08-29 Arnaud Vandaele , François Glineur , Nicolas Gillis

We study copositive matrices which admit a decomposition into a sum of a positive semidefinite matrix and a matrix with nonnegative entries. Our main result shows that if the off-diagonal entries of a copositive matrix are nondecreasing in…

Optimization and Control · Mathematics 2026-05-18 Grigoriy Blekherman , Santanu S. Dey , Alex Dunbar , Burak Kocuk

The paper introduces k-bounded MAP inference, a parameterization of MAP inference in Markov logic networks. k-Bounded MAP states are MAP states with at most k active ground atoms of hidden (non-evidence) predicates. We present a novel…

Artificial Intelligence · Computer Science 2012-03-19 Mathias Niepert

The nonnegative matrix factorization is a widely used, flexible matrix decomposition, finding applications in biology, image and signal processing and information retrieval, among other areas. Here we present a related matrix factorization.…

Machine Learning · Statistics 2017-12-12 David W Dreisigmeyer
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