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Positive semidefinite Hermitian matrices that are not fully specified can be completed provided their underlying graph is chordal. If the matrix is positive definite the completion can be uniquely characterized as the matrix that maximizes…

Rings and Algebras · Mathematics 2021-12-08 Olaf Dreyer

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

Structured canonical forms under unitary and suitable structure-preserving similarity transformations for normal and (skew-)Hamiltonian as well as normal and per(skew)-Hermitian matrices are proposed. Moreover, an algorithm for computing…

Numerical Analysis · Mathematics 2024-03-19 Erna Begovic , Heike Fassbender , Philip Saltenberger

We study the computational complexity of the problem SFT (Sum-free Formula partial Trace): given a tensor formula F over a subsemiring of the complex field (C,+,.) plus a positive integer k, under the restrictions that all inputs are column…

Quantum Physics · Physics 2016-09-08 Martin Beaudry , Jose M. Fernandez , Markus Holzer

We show how the separability problem is dual to that of decomposing any given matrix into a conic combination of rank-one partial isometries, thus offering a duality approach different to the positive maps characterization problem. Several…

Quantum Physics · Physics 2007-05-23 D. Salgado , J. L. Sanchez-Gomez , M. Ferrero

Inspired by some problems in Quantum Information Theory, we present some results concerning decompositions of positive operators acting on finite dimensional Hilbert spaces. We focus on decompositions by families having geometrical symmetry…

Functional Analysis · Mathematics 2017-03-23 Maria Anastasia Jivulescu , Ion Nechita , Pasc Gavruta

The partly symmetric real Ginibre ensemble consists of matrices formed as linear combinations of real symmetric and real anti-symmetric Gaussian random matrices. Such matrices typically have both real and complex eigenvalues. For a fixed…

Mathematical Physics · Physics 2015-08-27 Peter J. Forrester , Taro Nagao

The trace regression model, a direct extension of the well-studied linear regression model, allows one to map matrices to real-valued outputs. We here introduce an even more general model, namely the partial-trace regression model, a family…

Machine Learning · Computer Science 2020-08-26 Hachem Kadri , Stéphane Ayache , Riikka Huusari , Alain Rakotomamonjy , Liva Ralaivola

Let $A$ be a $m\times m$ complex matrix with zero trace. Then there are $m\times m$ matrices $B$ and $C$ such that $A=[B,C]$ and $\|B\|\|C\|_2\le (\log m+O(1))^{1/2}\|A\|_2$ where $\|D\|$ is the norm of $D$ as an operator on $\ell_2^m$ and…

Functional Analysis · Mathematics 2017-05-17 Omer Angel , Gideon Schechtman

Minimum error state discrimination between two mixed states \rho and \sigma can be aided by the receipt of "classical side information" specifying which states from some convex decompositions of \rho and \sigma apply in each run. We…

Quantum Physics · Physics 2012-10-22 Matthew F. Pusey , Terry Rudolph

We propose a quantum walk defined by digraphs (mixed graphs). This is like Grover walk that is perturbed by a certain complex-valued function defined by digraphs. The discriminant of this quantum walk is a matrix that is a certain…

Combinatorics · Mathematics 2021-03-10 Sho Kubota , Etsuo Segawa , Tetsuji Taniguchi

Taking partial traces for computing reduced density matrices, or related functions, is a ubiquitous procedure in the quantum mechanics of composite systems. In this article, we present a thorough description of this function and analyze the…

Quantum Physics · Physics 2016-08-25 Jonas Maziero

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

Symplectic eigenvalues are conventionally defined for symmetric positive-definite matrices via Williamson's diagonal form. Many properties of standard eigenvalues, including the trace minimization theorem, are extended to the case of…

Optimization and Control · Mathematics 2022-10-11 Nguyen Thanh Son , Tatjana Stykel

Patterns on numerical semigroups are multivariate linear polynomials, and they are said to be admissible if there exists a numerical semigroup such that evaluated at any nonincreasing sequence of elements of the semigroup gives integers…

Number Theory · Mathematics 2012-11-06 Maria Bras-Amorós , Pedro A. García-Sánchez , Albert Vico-Oton

A hermitian matrix can be parametrized by a set consisting of its determinant and the eigenvalues of its submatrices. We established a group of equations which connect these variables with the mixing parameters of diagonalization. These…

High Energy Physics - Phenomenology · Physics 2024-10-03 S. H. Chiu , T. K. Kuo

Changes of some unitarily invariant norms and anti-norms under the operation of partial trace are examined. The norms considered form a two-parametric family, including both the Ky Fan and Schatten norms as particular cases. The obtained…

Quantum Physics · Physics 2012-11-02 Alexey E. Rastegin

The product of a Hermitian matrix and a positive semidefinite matrix has only real eigenvalues. We present bounds for sums of eigenvalues of such a product.

Functional Analysis · Mathematics 2019-05-13 Bo-Yan Xi , Fuzhen Zhang

To develop a unitary quantum theory with probabilistic description for pseudo- Hermitian systems one needs to consider the theories in a different Hilbert space endowed with a positive definite metric operator. There are different…

Quantum Physics · Physics 2013-05-10 Ananya Ghatak , Bhabani Prasad Mandal

A sequence of approximations for the determinant and its logarithm of a complex matrixis derived, along with relative error bounds. The determinant approximations are derived from expansions of det(X)=exp(trace(log(X))), and they apply to…

Numerical Analysis · Mathematics 2011-05-04 Ilse C. F. Ipsen , Dean J. Lee