Second-order linear-time computability with applications to computable analysis

Akitoshi Kawamura, Florian Steinberg, Holger Thies

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work we put forward a complexity class of type-two linear-time. For such a definition to be meaningful, a detailed protocol for the cost of interactions with functional inputs has to be fixed. This includes some design decisions the defined class is sensible to and we carefully discuss our choices and their implications. We further discuss some properties and examples of operators that are and are not computable in linear-time and nearly linear-time and some applications to computable analysis.

Original languageEnglish
Title of host publicationTheory and Applications of Models of Computation - 15th Annual Conference, TAMC 2019, Proceedings
EditorsJunzo Watada, T. V. Gopal
PublisherSpringer Verlag
Pages337-358
Number of pages22
ISBN (Print)9783030148119
DOIs
Publication statusPublished - Jan 1 2019
Event15th Annual Conference on Theory and Applications of Models of Computation, TAMC 2019 - Kitakyushu, Japan
Duration: Apr 13 2019Apr 16 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11436 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Annual Conference on Theory and Applications of Models of Computation, TAMC 2019
CountryJapan
CityKitakyushu
Period4/13/194/16/19

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kawamura, A., Steinberg, F., & Thies, H. (2019). Second-order linear-time computability with applications to computable analysis. In J. Watada, & T. V. Gopal (Eds.), Theory and Applications of Models of Computation - 15th Annual Conference, TAMC 2019, Proceedings (pp. 337-358). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11436 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-14812-6_21