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The family of $(k,\ell)$-sparse graphs, introduced by Lorea, plays a central role in combinatorial optimization and has a wide range of applications, particularly in rigidity theory. A key algorithmic problem is to decide whether a given…

Data Structures and Algorithms · Computer Science 2026-04-15 Bence Deák , Péter Madarasi

We present substantially generalized and improved quantum algorithms over prior work for inhomogeneous linear and nonlinear ordinary differential equations (ODE). Specifically, we show how the norm of the matrix exponential characterizes…

Quantum Physics · Physics 2025-12-15 Hari Krovi

Graph sparsification underlies a large number of algorithms, ranging from approximation algorithms for cut problems to solvers for linear systems in the graph Laplacian. In its strongest form, "spectral sparsification" reduces the number of…

Quantum Physics · Physics 2023-05-09 Simon Apers , Ronald de Wolf

A new method for solving Laplacian linear systems proposed by Kelner et al. involves the random sampling and update of fundamental cycles in a graph. Kelner et al. proved asymptotic bounds on the complexity of this method but did not report…

Data Structures and Algorithms · Computer Science 2015-10-07 Erik G. Boman , Kevin Deweese , John R. Gilbert

We provide linear-time algorithms for geometric graphs with sublinearly many crossings. That is, we provide algorithms running in O(n) time on connected geometric graphs having n vertices and k crossings, where k is smaller than n by an…

Computational Geometry · Computer Science 2010-12-16 David Eppstein , Michael T. Goodrich , Darren Strash

Nonlinear differential equations model diverse phenomena but are notoriously difficult to solve. While there has been extensive previous work on efficient quantum algorithms for linear differential equations, the linearity of quantum…

Quantum computers have the potential to efficiently solve a system of nonlinear ordinary differential equations (ODEs), which play a crucial role in various industries and scientific fields. However, it remains unclear which system of…

Quantum Physics · Physics 2025-04-07 Yu Tanaka , Keisuke Fujii

We study linear equations in combinatorial Laplacians of $k$-dimensional simplicial complexes ($k$-complexes), a natural generalization of graph Laplacians. Combinatorial Laplacians play a crucial role in homology and are a central tool in…

Computational Complexity · Computer Science 2022-02-11 Ming Ding , Rasmus Kyng , Maximilian Probst Gutenberg , Peng Zhang

We present a quantum algorithm solving the $k$-distinctness problem in $O(n^{1-2^{k-2}/(2^k-1)})$ queries with a bounded error. This improves the previous $O(n^{k/(k+1)})$-query algorithm by Ambainis. The construction uses a modified…

Quantum Physics · Physics 2012-08-10 Aleksandrs Belovs

Integer Linear Programming with $n$ binary variables and $m$ many $0/1$-constraints can be solved in time $2^{\tilde O(m^2)} \text{poly}(n)$ and it is open whether the dependence on $m$ is optimal. Several seemingly unrelated problems,…

Data Structures and Algorithms · Computer Science 2024-09-06 Lars Rohwedder , Karol Węgrzycki

We present an improved algorithm for solving symmetrically diagonally dominant linear systems. On input of an $n\times n$ symmetric diagonally dominant matrix $A$ with $m$ non-zero entries and a vector $b$ such that $A\bar{x} = b$ for some…

Data Structures and Algorithms · Computer Science 2011-08-22 Ioannis Koutis , Gary Miller , Richard Peng

We present new quantum algorithms for Triangle Finding improving its best previously known quantum query complexities for both dense and spare instances.For dense graphs on $n$ vertices, we get a query complexity of $O(n^{5/4})$ without any…

Quantum Physics · Physics 2016-10-13 Titouan Carette , Mathieu Laurière , Frédéric Magniez

We present an efficient quantum algorithm to simulate nonlinear differential equations with polynomial vector fields of arbitrary degree on quantum platforms. Models of physical systems that are governed by ordinary differential equations…

Dynamical Systems · Mathematics 2023-02-08 Amit Surana , Abeynaya Gnanasekaran , Tuhin Sahai

We study dynamic $(1+\epsilon)$-approximation algorithms for the all-pairs shortest paths problem in unweighted undirected $n$-node $m$-edge graphs under edge deletions. The fastest algorithm for this problem is a randomized algorithm with…

Data Structures and Algorithms · Computer Science 2018-03-02 Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

In this paper we present an efficiently scaling quantum algorithm which finds the size of the maximum common edge subgraph for a pair of arbitrary graphs and thus provides a meaningful measure of graph similarity. The algorithm makes use of…

Quantum Physics · Physics 2018-10-04 M. Chiew , K. de Lacy , C. H. Yu , S. Marsh , J. B. Wang

In this paper, we prove that, given a clique-width $k$-expression of an $n$-vertex graph, \textsc{Hamiltonian Cycle} can be solved in time $n^{\mathcal{O}(k)}$. This improves the naive algorithm that runs in time $n^{\mathcal{O}(k^2)}$ by…

Data Structures and Algorithms · Computer Science 2019-06-11 Benjamin Bergougnoux , Mamadou Moustapha Kanté , O-joung Kwon

We consider the problem of approximating the girth, $g$, of an unweighted and undirected graph $G=(V,E)$ with $n$ nodes and $m$ edges. A seminal result of Itai and Rodeh [SICOMP'78] gave an additive $1$-approximation in $O(n^2)$ time, and…

Data Structures and Algorithms · Computer Science 2017-04-10 Søren Dahlgaard , Mathias Bæk Tejs Knudsen , Morten Stöckel

The girth of a graph, i.e. the length of its shortest cycle, is a fundamental graph parameter. Unfortunately all known algorithms for computing, even approximately, the girth and girth-related structures in directed weighted $m$-edge and…

Data Structures and Algorithms · Computer Science 2018-08-14 Jakub Pachocki , Liam Roditty , Aaron Sidford , Roei Tov , Virginia Vassilevska Williams

Computing the diameter, and more generally, all eccentricities of an undirected graph is an important problem in algorithmic graph theory and the challenge is to identify graph classes for which their computation can be achieved in…

Data Structures and Algorithms · Computer Science 2024-10-15 Pierre Bergé , Guillaume Ducoffe , Michel Habib

We present an algorithm that given a linear program with $n$ variables, $m$ constraints, and constraint matrix $A$, computes an $\epsilon$-approximate solution in $\tilde{O}(\sqrt{rank(A)}\log(1/\epsilon))$ iterations with high probability.…

Data Structures and Algorithms · Computer Science 2020-09-02 Yin Tat Lee , Aaron Sidford