Some trade-off results for polynomial calculus

Chris Beck, Jakob Nordström, Bangsheng Tang

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

We present size-space trade-offs for the polynomial calculus (PC) and polynomial calculus resolution (PCR) proof systems. These are the first true size-space trade-offs in any algebraic proof system, showing that size and space cannot be simultaneously optimized in these models. We achieve this by extending essentially all known size-space trade-offs for resolution to PC and PCR. As such, our results cover space complexity from constant all the way up to exponential and yield mostly superpolynomial or even exponential size blow-ups. Since the upper bounds in our trade-offs hold for resolution, our work shows that there are formulas for which adding algebraic reasoning on top of resolution does not improve the trade-off properties in any significant way. As byproducts of our analysis, we also obtain trade-offs between space and degree in PC and PCR exactly matching analogous results for space versus width in resolution, and strengthen the resolution trade-offs in [Beame, Beck, and Impagliazzo '12] to apply also to k-CNF formulas.

Original languageEnglish
Title of host publicationSTOC 2013 - Proceedings of the 2013 ACM Symposium on Theory of Computing
PublisherAssociation for Computing Machinery (ACM)
Pages813-822
Number of pages10
ISBN (Print)9781450320290
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event45th Annual ACM Symposium on Theory of Computing, STOC 2013 - Palo Alto, CA, United States
Duration: 2013 Jun 12013 Jun 4

Publication series

NameProceedings of the Annual ACM Symposium on Theory of Computing
PublisherACM
ISSN (Print)0737-8017

Conference

Conference45th Annual ACM Symposium on Theory of Computing, STOC 2013
Country/TerritoryUnited States
CityPalo Alto, CA
Period2013/06/012013/06/04

Subject classification (UKÄ)

  • Computer Science

Free keywords

  • Degree
  • PCR
  • Pebble games
  • Pebbling formulas
  • Polynomial calculus
  • Proof complexity
  • Resolution
  • Size
  • Space
  • Trade-offs
  • Tseitin formulas

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