Skip to main navigation Skip to search Skip to main content

Integer multiplication is at least as hard as matrix transposition

  • School of Mathematics and Statistics
  • University of New South Wales

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Working in the multitape Turing model, we show how to reduce the problem of matrix transposition to the problem of integer multiplication. If transposing an n × n binary matrix requires Ω(n2 log n) steps on a Turing machine, then our reduction implies that multiplying n-bit integers requires Ω(n log n) steps. In other words, if matrix transposition is as hard as expected, then integer multiplication is also as hard as expected.

Original languageEnglish
Title of host publicationProceedings - 2025 IEEE 66th Annual Symposium on Foundations of Computer Science, FOCS 2025
PublisherIEEE Computer Society
Pages1366-1381
Number of pages16
ISBN (Electronic)9798331571320
DOIs
Publication statusPublished - 1 Jan 2025
Event66th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2025 - Sydney, Australia
Duration: 14 Dec 2025 → 17 Dec 2025

Publication series

NameProceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS
ISSN (Print)0272-5428

Conference

Conference66th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2025
Country/TerritoryAustralia
CitySydney
Period14/12/25 → 17/12/25

Keywords

  • integer multiplication
  • lower bounds
  • matrix transposition

Fingerprint

Dive into the research topics of 'Integer multiplication is at least as hard as matrix transposition'. Together they form a unique fingerprint.

Cite this