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A degenerate string is a sequence of sets of characters. A generalized degenerate (GD) string extends this notion to the sequence of sets of strings, where strings of the same set are of equal length. Finding an exact match for a pattern…

Quantum Physics · Physics 2026-03-18 Massimo Equi , Md Rabiul Islam Khan , Veli Mäkinen

Given an $n*n$ sparse symmetric matrix with $m$ nonzero entries, performing Gaussian elimination may turn some zeroes into nonzero values. To maintain the matrix sparse, we would like to minimize the number $k$ of these changes, hence…

Computational Complexity · Computer Science 2016-06-28 Yixin Cao , R. B. Sandeep

This study aims to publish a novel similarity metric to increase the speed of comparison operations. Also the new metric is suitable for distance-based operations among strings. Most of the simple calculation methods, such as string length…

Data Structures and Algorithms · Computer Science 2014-01-28 Sadi Evren Seker , Oguz Altun , Uğur Ayan , Cihan Mert

A fundamental problem in shape matching and geometric similarity is computing the maximum area overlap between two polygons under translation. For general simple polygons, the best-known algorithm runs in $O((nm)^2 \log(nm))$ time [Mount,…

Computational Geometry · Computer Science 2025-11-07 Mikkel Abrahamsen , Sujoy Bhore , Maike Buchin , Jacobus Conradi , Ce Jin , André Nusser , Carolin Rehs

We give the first input-sparsity time algorithms for the rank-$k$ low rank approximation problem in every Schatten norm. Specifically, for a given $n\times n$ matrix $A$, our algorithm computes $Y,Z\in \mathbb{R}^{n\times k}$, which, with…

Data Structures and Algorithms · Computer Science 2020-07-01 Yi Li , David Woodruff

A distance matrix $A \in \mathbb R^{n \times m}$ represents all pairwise distances, $A_{ij}=\mathrm{d}(x_i,y_j)$, between two point sets $x_1,...,x_n$ and $y_1,...,y_m$ in an arbitrary metric space $(\mathcal Z, \mathrm{d})$. Such matrices…

Data Structures and Algorithms · Computer Science 2019-06-05 Piotr Indyk , Ali Vakilian , Tal Wagner , David Woodruff

We study the problem of $k$-means clustering in the space of straight-line segments in $\mathbb{R}^{2}$ under the Hausdorff distance. For this problem, we give a $(1+\epsilon)$-approximation algorithm that, for an input of $n$ segments, for…

Computational Geometry · Computer Science 2023-05-19 Sergio Cabello , Panos Giannopoulos

In the Pattern Masking for Dictionary Matching (PMDM) problem, we are given a dictionary $\mathcal{D}$ of $d$ strings, each of length $\ell$, a query string $q$ of length $\ell$, and a positive integer $z$, and we are asked to compute a…

Data Structures and Algorithms · Computer Science 2024-03-11 Panagiotis Charalampopoulos , Huiping Chen , Peter Christen , Grigorios Loukides , Nadia Pisanti , Solon P. Pissis , Jakub Radoszewski

String attractors [STOC 2018] are combinatorial objects recently introduced to unify all known dictionary compression techniques in a single theory. A set $\Gamma\subseteq [1..n]$ is a $k$-attractor for a string $S\in[1..\sigma]^n$ if and…

Data Structures and Algorithms · Computer Science 2020-12-09 Dominik Kempa , Alberto Policriti , Nicola Prezza , Eva Rotenberg

The quantum query complexity of subgraph-containment problems, which ask whether a given subgraph $H$ is present in an input graph $G$, has been the subject of considerable study. However, even for relatively simple subgraphs, such as paths…

Quantum Physics · Physics 2026-05-12 Arjan Cornelissen , Amin Shiraz Gilani , Subhasree Patro

A quantum algorithm is known that solves an unstructured search problem in a number of iterations of order $\sqrt{d}$, where $d$ is the dimension of the search space, whereas any classical algorithm necessarily scales as $O(d)$. It is shown…

Quantum Physics · Physics 2009-10-31 N. J. Cerf , L. K. Grover , C. P. Williams

For any $\varepsilon > 0$, we prove that $k$-Dimensional Matching is hard to approximate within a factor of $k/(12 + \varepsilon)$ for large $k$ unless $\textsf{NP} \subseteq \textsf{BPP}$. Listed in Karp's 21 $\textsf{NP}$-complete…

Computational Complexity · Computer Science 2024-09-27 Euiwoong Lee , Ola Svensson , Theophile Thiery

We give a quantum reduction from finding short codewords in a random linear code to decoding for the Hamming metric. This is the first time such a reduction (classical or quantum) has been obtained. Our reduction adapts to linear codes…

Cryptography and Security · Computer Science 2023-06-06 Thomas Debris-Alazard , Maxime Remaud , Jean-Pierre Tillich

Motivated by the imminent growth of massive, highly redundant genomic databases, we study the problem of compressing a string database while simultaneously supporting fast random access, substring extraction and pattern matching to the…

Data Structures and Algorithms · Computer Science 2012-11-01 Travis Gagie , Paweł Gawrychowski , Christopher Hoobin , Simon J. Puglisi

The quantum k-Local Hamiltonian problem is a natural generalization of classical constraint satisfaction problems (k-CSP) and is complete for QMA, a quantum analog of NP. Although the complexity of k-Local Hamiltonian problems has been well…

Quantum Physics · Physics 2021-11-16 Ojas Parekh , Kevin Thompson

Symmetries in a Hamiltonian play an important role in quantum physics because they correspond directly with conserved quantities of the related system. In this paper, we propose quantum algorithms capable of testing whether a Hamiltonian…

Quantum Physics · Physics 2023-12-29 Margarite L. LaBorde , Mark M. Wilde

Alice and Bob want to know if two strings of length n are almost equal. That is, do they differ on \textit{at most} a bits? Let 0\leq a\leq n-1. We show that any deterministic protocol, as well as any error-free quantum protocol (C*…

Computational Complexity · Computer Science 2015-01-13 Andris Ambainis , William Gasarch , Aravind Srinavasan , Andrey Utis

Complexity of a quantum analogue of the satisfiability problem is studied. Quantum k-SAT is a problem of verifying whether there exists n-qubit pure state such that its k-qubit reduced density matrices have support on prescribed subspaces.…

Quantum Physics · Physics 2007-05-23 Sergey Bravyi

We develop a randomized approximation algorithm for the classical maximum coverage problem, which given a list of sets $A_1,A_2,\cdots, A_m$ and integer parameter $k$, select $k$ sets $A_{i_1}, A_{i_2},\cdots, A_{i_k}$ for maximum union…

Data Structures and Algorithms · Computer Science 2016-07-21 Bin Fu

Finding a high (or low) energy state of a given quantum Hamiltonian is a potential area to gain a provable and practical quantum advantage. A line of recent studies focuses on Quantum Max Cut, where one is asked to find a high energy state…

Quantum Physics · Physics 2026-02-17 Eunou Lee , Ojas Parekh
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