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We address the question: for which collections of finite simple groups does there exist an algorithm that determines the images of an arbitrary finitely presented group that lie in the collection? We prove both positive and negative…

Group Theory · Mathematics 2017-10-20 Martin R. Bridson , David M. Evans , Martin W. Liebeck , Dan Segal

We give an new arithmetic algorithm to compute the generalized Discrete Fourier Transform (DFT) over finite groups $G$. The new algorithm uses $O(|G|^{\omega/2 + o(1)})$ operations to compute the generalized DFT over finite groups of Lie…

Data Structures and Algorithms · Computer Science 2018-04-02 Chloe Ching-Yun Hsu , Chris Umans

Many exponential speedups that have been achieved in quantum computing are obtained via hidden subgroup problems (HSPs). We show that the HSP over Weyl-Heisenberg groups can be solved efficiently on a quantum computer. These groups are…

Quantum Physics · Physics 2013-12-05 Hari Krovi , Martin Roetteler

This paper studies the quantum computational complexity of the discrete logarithm (DL) and related group-theoretic problems in the context of generic algorithms -- that is, algorithms that do not exploit any properties of the group…

Quantum Physics · Physics 2024-10-23 Minki Hhan , Takashi Yamakawa , Aaram Yun

Extraspecial groups form a remarkable subclass of p-groups. They are also present in quantum information theory, in particular in quantum error correction. We give here a polynomial time quantum algorithm for finding hidden subgroups in…

Quantum Physics · Physics 2007-05-23 Gábor Ivanyos , Luc Sanselme , Miklos Santha

We study feature selection for $k$-means clustering. Although the literature contains many methods with good empirical performance, algorithms with provable theoretical behavior have only recently been developed. Unfortunately, these…

Machine Learning · Computer Science 2016-11-17 Christos Boutsidis , Malik Magdon-Ismail

Network decomposition is a central tool in distributed graph algorithms. We present two improvements on the state of the art for network decomposition, which thus lead to improvements in the (deterministic and randomized) complexity of…

Data Structures and Algorithms · Computer Science 2020-07-17 Mohsen Ghaffari , Christoph Grunau , Václav Rozhoň

Given a polygon $H$ in the plane, the art gallery problem calls for fining the smallest set of points in $H$ from which every other point in $H$ is seen. We give a deterministic algorithm that, given any polygon $H$ with $h$ holes, $n$…

Computational Geometry · Computer Science 2026-04-16 Khaled Elbassioni

In theoretical computer science, it is a common practice to show existential lower bounds for problems, meaning there is a family of pathological inputs on which no algorithm can do better. However, most inputs of interest can be solved…

Data Structures and Algorithms · Computer Science 2023-04-14 Yi-Jun Chang , Oren Hecht , Dean Leitersdorf

For every Turing machine, we construct an automaton group that simulates it. Precisely, starting from an initial configuration of the Turing machine, we explicitly construct an element of the group such that the Turing machine stops if, and…

Group Theory · Mathematics 2017-11-30 Pierre Gillibert

Constraint satisfaction problems (CSPs) consist of a set of variables taking values from some finite domain and a set of local constraints on these variables. The objective is to find an assignment to the variables that maximizes the…

Computational Complexity · Computer Science 2026-05-12 Amey Bhangale , Yezhou Zhang

Subexponential parameterized algorithms are known for a wide range of natural problems on planar graphs, but the techniques are usually highly problem specific. The goal of this paper is to introduce a framework for obtaining…

Data Structures and Algorithms · Computer Science 2021-10-29 Dániel Marx , Pranabendu Misra , Daniel Neuen , Prafullkumar Tale

In this note we prove the following results: $\bullet$ If a finitely presented group $G$ admits a strongly aperiodic SFT, then $G$ has decidable word problem. More generally, for f.g. groups that are not recursively presented, there exists…

Group Theory · Mathematics 2015-07-07 Emmanuel Jeandel

Let $F$ be a free group of arbitrary rank and let $H$ be a finitely generated subgroup of $F$. Given a pseudovariety $\mathbf{V}$ of finite groups, i.e. a class of finite groups closed under taking subgroups, quotients and finitary direct…

Group Theory · Mathematics 2023-05-30 Claude Marion , Pedro V. Silva , Gareth Tracey

Let $G$ be a group. A subset $D$ of $G$ is a determining set of $G$, if every automorphism of $G$ is uniquely determined by its action on $D$. The determining number of $G$, denoted by $\alpha(G)$, is the cardinality of a smallest…

Group Theory · Mathematics 2018-01-26 Dengyin Wang , Shikun Ou , Haipeng Qu

This work establishes a new probabilistic bound on the number of elements to generate finite nilpotent groups. Let $\varphi_k(G)$ denote the probability that $k$ random elements generate a finite nilpotent group $G$. For any $0 < \epsilon <…

Quantum Physics · Physics 2025-11-26 Ziyuan Dong , Xiang Fan , Tengxun Zhong , Daowen Qiu

We prove that there is no algorithm that can determine whether or not a finitely presented group has a non-trivial finite quotient; indeed, this remains undecidable among the fundamental groups of compact, non-positively curved square…

Group Theory · Mathematics 2023-07-19 Martin R. Bridson , Henry Wilton

Given two graphs $H$ and $G$, the Subgraph Isomorphism problem asks if $H$ is isomorphic to a subgraph of $G$. While NP-hard in general, algorithms exist for various parameterized versions of the problem: for example, the problem can be…

Data Structures and Algorithms · Computer Science 2013-08-27 Dániel Marx , Michał Pilipczuk

In this work we revisit the arithmetic and bit complexity of Hermitian eigenproblems. Recently, [BGVKS, FOCS 2020] proved that a (non-Hermitian) matrix can be diagonalized with a randomized algorithm in $O(n^{\omega}\log^2(n/\epsilon))$…

Data Structures and Algorithms · Computer Science 2025-04-29 Aleksandros Sobczyk

First-order stochastic methods for solving large-scale non-convex optimization problems are widely used in many big-data applications, e.g. training deep neural networks as well as other complex and potentially non-convex machine learning…

Machine Learning · Computer Science 2020-11-23 Matilde Gargiani , Andrea Zanelli , Quoc Tran-Dinh , Moritz Diehl , Frank Hutter