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Related papers: On orthogonal matrices maximizing the 1-norm

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We introduce the concept of n-OU and n-OO matrix sets, a collection of n mutually-orthogonal unitary and real orthogonal matrices under Hilbert-Schmidt inner product. We give a detailed characterization of order-three n-OO matrix sets under…

Quantum Physics · Physics 2025-10-28 Zhiwei Song , Lin Chen , Saiqi Liu

In this paper, we consider the following $k$-dispersion problem. Given a set $S$ of $n$ points placed in the plane in a convex position, and an integer $k$ ($0<k<n$), the objective is to compute a subset $S'\subset S$ such that $|S'|=k$ and…

Computational Geometry · Computer Science 2022-05-05 Vishwanath R. Singireddy , Manjanna Basappa

We show the optimal coherence of $2d$ lines in $\mathbb{C}^{d}$ is given by the Welch bound whenever a skew Hadamard of order $d+1$ exists. Our proof uses a variant of Hadamard doubling that converts any equiangular tight frame of size…

Metric Geometry · Mathematics 2023-12-18 Kean Fallon , Joseph W. Iverson

In the Determinant Maximization problem, given an $n\times n$ positive semi-definite matrix $\bf{A}$ in $\mathbb{Q}^{n\times n}$ and an integer $k$, we are required to find a $k\times k$ principal submatrix of $\bf{A}$ having the maximum…

Data Structures and Algorithms · Computer Science 2024-02-20 Naoto Ohsaka

The orthogonality dimension of a graph $G$ over $\mathbb{R}$ is the smallest integer $k$ for which one can assign a nonzero $k$-dimensional real vector to each vertex of $G$, such that every two adjacent vertices receive orthogonal vectors.…

Computational Complexity · Computer Science 2023-11-16 Dror Chawin , Ishay Haviv

We introduce a randomized algorithm for computing the minimal-norm solution to an underdetermined system of linear equations. Given an arbitrary full-rank m x n matrix A with m<n, any m x 1 vector b, and any positive real number epsilon…

Numerical Analysis · Computer Science 2009-09-08 Mark Tygert

The problem of an optimal mapping between Hilbert spaces $IN$ of $\left|\psi\right\rangle$ and $OUT$ of $\left|\phi\right\rangle$ based on a set of wavefunction measurements (within a phase) $\psi_l \to \phi_l$, $l=1\dots M$, is formulated…

Machine Learning · Computer Science 2024-11-20 Mikhail Gennadievich Belov , Vladislav Gennadievich Malyshkin

We study the minimization of fixed-degree polynomials over the simplex. This problem is well-known to be NP-hard, as it contains the maximum stable set problem in graph theory as a special case. In this paper, we consider a rational…

Optimization and Control · Mathematics 2014-07-09 Etienne de Klerk , Monique Laurent , Zhao Sun

Writing for a general mathematical audience, we provide elementary upper and lower bounds on the growth (as a function of N) of the sum \sum_{n=1}^N (-1)^{\floor{n x}} for various fixed x. For example, if x is a quadratic irrational, then…

Number Theory · Mathematics 2007-05-23 Kevin O'Bryant , Bruce Reznick , Monika Serbinowska

Very recently, Bai [Linear Algebra Appl., 681:150-186, 2024 \& Appl. Math. Lett., 166:109510, 2025] studied some concrete structures, and obtained essential algebraic and computational properties of the one-dimensional, two-dimensional and…

Rings and Algebras · Mathematics 2025-06-19 Aaisha Be , Nachiketa Mishra , Debasisha Mishra

In this paper, an effective method with time complexity of $\mathcal{O}(K^{3/2}N^2\log \frac{K}{\epsilon_0})$ is introduced to find an approximation of the convex hull for $N$ points in dimension $n$, where $K$ is close to the number of…

Computational Geometry · Computer Science 2016-03-15 Hossein Sartipizadeh , Tyrone L. Vincent

Many applications, including rank aggregation and crowd-labeling, can be modeled in terms of a bivariate isotonic matrix with unknown permutations acting on its rows and columns. We consider the problem of estimating such a matrix based on…

Machine Learning · Statistics 2018-06-06 Cheng Mao , Ashwin Pananjady , Martin J. Wainwright

Let $A$ be an $n\times n$ random matrix whose entries are i.i.d. with mean $0$ and variance $1$. We present a deterministic polynomial time algorithm which, with probability at least $1-2\exp(-\Omega(\epsilon n))$ in the choice of $A$,…

Probability · Mathematics 2020-12-02 Vishesh Jain , Ashwin Sah , Mehtaab Sawhney

This paper initiates the study of quantum algorithms for matroid property problems. It is shown that quadratic quantum speedup is possible for the calculation problem of finding the girth or the number of circuits (bases, flats,…

Quantum Physics · Physics 2022-03-28 Xiaowei Huang , Jingquan Luo , Lvzhou Li

We describe a new approximation algorithm for Max Cut. Our algorithm runs in $\tilde O(n^2)$ time, where $n$ is the number of vertices, and achieves an approximation ratio of $.531$. On instances in which an optimal solution cuts a…

Data Structures and Algorithms · Computer Science 2008-12-08 Luca Trevisan

We study the classic NP-Hard problem of finding the maximum $k$-set coverage in the data stream model: given a set system of $m$ sets that are subsets of a universe $\{1,\ldots,n \}$, find the $k$ sets that cover the most number of distinct…

Data Structures and Algorithms · Computer Science 2018-05-11 Andrew McGregor , Hoa T. Vu

Matrix scaling and matrix balancing are two basic linear-algebraic problems with a wide variety of applications, such as approximating the permanent, and pre-conditioning linear systems to make them more numerically stable. We study the…

We show new algorithms and constructions over linear delta-matroids. We observe an alternative representation for linear delta-matroids, as a contraction representation over a skew-symmetric matrix. This is equivalent to the more standard…

Data Structures and Algorithms · Computer Science 2024-02-20 Tomohiro Koana , Magnus Wahlström

Let $f$ be a symmetric norm on ${\mathbb R}^n$ and let ${\mathcal B}({\mathcal H})$ be the set of all bounded linear operators on a Hilbert space ${\mathcal H}$ of dimension at least $n$. Define a norm on ${\mathcal B}({\mathcal H})$ by…

Functional Analysis · Mathematics 2022-02-11 Jor-Ting Chan , Chi-Kwong Li

A runtime analysis of the Univariate Marginal Distribution Algorithm (UMDA) is presented on the OneMax function for wide ranges of its parameters $\mu$ and $\lambda$. If $\mu\ge c\log n$ for some constant $c>0$ and…

Neural and Evolutionary Computing · Computer Science 2018-06-08 Carsten Witt