Saved in:
Bibliographic Details
Main Authors: Lohrey, Markus, Lück, Lukas, Thumm, Alexander, Xochitemol, Julio
Format: Preprint
Published: 2022
Subjects:
Online Access:https://arxiv.org/abs/2202.04060
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866913054036328448
author Lohrey, Markus
Lück, Lukas
Thumm, Alexander
Xochitemol, Julio
author_facet Lohrey, Markus
Lück, Lukas
Thumm, Alexander
Xochitemol, Julio
contents We investigate deterministic and randomized streaming algorithms for word problems in finitely generated groups and semigroups. For this we introduce the notion of a distinguisher: a randomized streaming algorithm that processes two input words in parallel and, with high probability, reaches identical memory states if the words represent the same element, and distinct states otherwise. We construct such distinguishers with low error probability using logarithmic, and in some cases doubly logarithmic, space. For example, our results apply to linear semigroups and to semigroups obtained (under suitable restrictions) via standard constructions such as graph products, wreath products, and semilattice decompositions. In case of commutative semigroups and cancellative nilpotent semigroups, we achieve space complexity $\mathcal{O}(\log \log n)$. We complement these upper bounds with lower bounds demonstrating that certain well-known semigroups do not admit sublinear-space distinguishers. This includes, for example, free inverse monoids of rank at least two and Thompson's group $F$. Finally, we study randomized streaming algorithms for subgroup membership problems in free groups and their direct products.
format Preprint
id arxiv_https___arxiv_org_abs_2202_04060
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Streaming algorithms for groups and semigroups
Lohrey, Markus
Lück, Lukas
Thumm, Alexander
Xochitemol, Julio
Group Theory
Data Structures and Algorithms
20F10, 68W27
We investigate deterministic and randomized streaming algorithms for word problems in finitely generated groups and semigroups. For this we introduce the notion of a distinguisher: a randomized streaming algorithm that processes two input words in parallel and, with high probability, reaches identical memory states if the words represent the same element, and distinct states otherwise. We construct such distinguishers with low error probability using logarithmic, and in some cases doubly logarithmic, space. For example, our results apply to linear semigroups and to semigroups obtained (under suitable restrictions) via standard constructions such as graph products, wreath products, and semilattice decompositions. In case of commutative semigroups and cancellative nilpotent semigroups, we achieve space complexity $\mathcal{O}(\log \log n)$. We complement these upper bounds with lower bounds demonstrating that certain well-known semigroups do not admit sublinear-space distinguishers. This includes, for example, free inverse monoids of rank at least two and Thompson's group $F$. Finally, we study randomized streaming algorithms for subgroup membership problems in free groups and their direct products.
title Streaming algorithms for groups and semigroups
topic Group Theory
Data Structures and Algorithms
20F10, 68W27
url https://arxiv.org/abs/2202.04060