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In this paper, we present a low-diameter decomposition algorithm in the LOCAL model of distributed computing that succeeds with probability $1 - 1/poly(n)$. Specifically, we show how to compute an $\left(\epsilon, O\left(\frac{\log…

Data Structures and Algorithms · Computer Science 2023-07-25 Yi-Jun Chang , Zeyong Li

We construct fast, structure-preserving iterations for computing the sign decomposition of a unitary matrix $A$ with no eigenvalues equal to $\pm i$. This decomposition factorizes $A$ as the product of an involutory matrix $S =…

Numerical Analysis · Mathematics 2020-11-26 Evan S. Gawlik

We prove that given a discrete space with $n$ points which is either embedded in a system of $k$ trees, or the Cartesian product of $k$ trees, we can compute all eccentricities in ${\cal O}(2^{{\cal O}(k\log{k})}(N+n)^{1+o(1)})$ time, where…

Data Structures and Algorithms · Computer Science 2020-10-30 Guillaume Ducoffe

We present an efficient, nearly optimal quantum algorithm for solving linear matrix differential equations, with applications to the simulation of open quantum systems and beyond. For unitary or dissipative dynamics, the algorithm computes…

Quantum Physics · Physics 2026-05-18 Sophia Simon , Dominic W. Berry , Rolando D. Somma

Many real-world data sets are sparse or almost sparse. One method to measure this for a matrix $A\in \mathbb{R}^{n\times n}$ is the \emph{numerical sparsity}, denoted $\mathsf{ns}(A)$, defined as the minimum $k\geq 1$ such that…

Data Structures and Algorithms · Computer Science 2021-07-06 Vladimir Braverman , Robert Krauthgamer , Aditya Krishnan , Shay Sapir

We develop two fast algorithms for Hessenberg reduction of a structured matrix $A = D + UV^H$ where $D$ is a real or unitary $n \times n$ diagonal matrix and $U, V \in\mathbb{C}^{n \times k}$. The proposed algorithm for the real case…

Numerical Analysis · Mathematics 2016-12-14 Luca Gemignani , Leonardo Robol

We present improved algorithms for short cycle decomposition of a graph. Short cycle decompositions were introduced in the recent work of Chu et al, and were used to make progress on several questions in graph sparsification. For all…

Data Structures and Algorithms · Computer Science 2019-01-15 Yang P. Liu , Sushant Sachdeva , Zejun Yu

Semidefinite programming (SDP) is a central topic in mathematical optimization with extensive studies on its efficient solvers. In this paper, we present a proof-of-principle sublinear-time algorithm for solving SDPs with low-rank…

Data Structures and Algorithms · Computer Science 2020-08-07 Nai-Hui Chia , Tongyang Li , Han-Hsuan Lin , Chunhao Wang

We consider the problem of preprocessing an $n\times n$ matrix $\mathbf{M}$, and supporting queries that, for any vector $v$, returns the matrix-vector product $\mathbf{M} v$. This problem has been extensively studied in both theory and…

Data Structures and Algorithms · Computer Science 2026-02-10 Emile Anand , Jan van den Brand , Rose McCarty

Let $M=(m_{ij})$ be a symmetric matrix of order $n$ whose elements lie in an arbitrary field $\mathbb{F}$, and let $G$ be the graph with vertex set $\{1,\ldots,n\}$ such that distinct vertices $i$ and $j$ are adjacent if and only if $m_{ij}…

Data Structures and Algorithms · Computer Science 2021-10-28 Martin Fürer , Carlos Hoppen , Vilmar Trevisan

Randomized sampling has recently been proven a highly efficient technique for computing approximate factorizations of matrices that have low numerical rank. This paper describes an extension of such techniques to a wider class of matrices…

Numerical Analysis · Mathematics 2015-03-25 Per-Gunnar Martinsson

This article presents a strongly polynomial-time algorithm for the general linear programming problem. This algorithm is an implicit reduction procedure that works as follows. Primal and dual problems are combined into a special system of…

Optimization and Control · Mathematics 2026-03-24 Samuel Awoniyi

We present a prescription for forming matrices with specified eigenvalues and known eigenvectors. With this method, we can form Hermitian, anti-Hermitian, symmetric and general matrices with arbitrary eigenvalues. In addition we propose an…

Quantum Physics · Physics 2007-05-23 Habatwa V. Mweene

We consider the problem of low-rank rectangular matrix completion in the regime where the matrix $M$ of size $n\times m$ is ``long", i.e., the aspect ratio $m/n$ diverges to infinity. Such matrices are of particular interest in the study of…

Statistics Theory · Mathematics 2024-06-24 Ludovic Stephan , Yizhe Zhu

We show an algorithm for computing the permanent of a random matrix with vanishing mean in quasi-polynomial time. Among special cases are the Gaussian, and biased-Bernoulli random matrices with mean 1/lnln(n)^{1/8}. In addition, we can…

Data Structures and Algorithms · Computer Science 2018-10-11 Lior Eldar , Saeed Mehraban

In this review we focus on the almost diagonalization of pseudodifferential operators and highlight the advantages that time-frequency techniques provide here. In particular, we retrace the steps of an insightful paper by Gr\"ochenig, who…

Functional Analysis · Mathematics 2020-04-08 S. Ivan Trapasso

Vizing's theorem states that any $n$-vertex $m$-edge graph of maximum degree $\Delta$ can be edge colored using at most $\Delta + 1$ different colors. Vizing's original proof is easily translated into a deterministic $O(mn)$ time algorithm.…

Data Structures and Algorithms · Computer Science 2025-10-20 Sepehr Assadi , Soheil Behnezhad , Sayan Bhattacharya , Martín Costa , Shay Solomon , Tianyi Zhang

We provide novel deterministic distributed vertex coloring algorithms. As our main result, we give a deterministic distributed algorithm to compute a $(\Delta+1)$-coloring of an $n$-node graph with maximum degree $\Delta$ in…

Data Structures and Algorithms · Computer Science 2019-07-10 Fabian Kuhn

We consider the classical Minimum Crossing Number problem: given an $n$-vertex graph $G$, compute a drawing of $G$ in the plane, while minimizing the number of crossings between the images of its edges. This is a fundamental and extensively…

Data Structures and Algorithms · Computer Science 2022-02-15 Julia Chuzhoy , Zihan Tan

Given a nonsingular $n \times n$ matrix of univariate polynomials over a field $\mathbb{K}$, we give fast and deterministic algorithms to compute its determinant and its Hermite normal form. Our algorithms use…

Symbolic Computation · Computer Science 2017-03-31 George Labahn , Vincent Neiger , Wei Zhou