License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CCC.2022.26
URN: urn:nbn:de:0030-drops-165880
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/16588/
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Hirahara, Shuichi

Symmetry of Information from Meta-Complexity

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LIPIcs-CCC-2022-26.pdf (1 MB)

Abstract

Symmetry of information for time-bounded Kolmogorov complexity is a hypothetical inequality that relates time-bounded Kolmogorov complexity and its conditional analogue. In 1992, Longpré and Watanabe showed that symmetry of information holds if NP is easy in the worst case, which has been the state of the art over the last three decades. In this paper, we significantly improve this result by showing that symmetry of information holds under the weaker assumption that NP is easy on average. In fact, our proof techniques are applicable to any resource-bounded Kolmogorov complexity and enable proving symmetry of information from an efficient algorithm that computes resource-bounded Kolmogorov complexity.
We demonstrate the significance of our proof techniques by presenting two applications. First, using that symmetry of information does not hold for Levin’s Kt-complexity, we prove that randomized Kt-complexity cannot be computed in time 2^o(n) on inputs of length n, which improves the previous quasi-polynomial lower bound of Oliveira (ICALP 2019). Our proof implements Kolmogorov’s insightful approach to the P versus NP problem in the case of randomized Kt-complexity. Second, we consider the question of excluding Heuristica, i.e., a world in which NP is easy on average but NP ≠ P, from Impagliazzo’s five worlds: Using symmetry of information, we prove that Heuristica is excluded if the problem of approximating time-bounded conditional Kolmogorov complexity K^t(x∣y) up to some additive error is NP-hard for t ≫ |y|. We complement this result by proving NP-hardness of approximating sublinear-time-bounded conditional Kolmogorov complexity up to a multiplicative factor of |x|^{1/(log log |x|)^O(1)} for t ≪ |y|. Our NP-hardness proof presents a new connection between sublinear-time-bounded conditional Kolmogorov complexity and a secret sharing scheme.

BibTeX - Entry

@InProceedings{hirahara:LIPIcs.CCC.2022.26,
  author =	{Hirahara, Shuichi},
  title =	{{Symmetry of Information from Meta-Complexity}},
  booktitle =	{37th Computational Complexity Conference (CCC 2022)},
  pages =	{26:1--26:41},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-241-9},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{234},
  editor =	{Lovett, Shachar},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/16588},
  URN =		{urn:nbn:de:0030-drops-165880},
  doi =		{10.4230/LIPIcs.CCC.2022.26},
  annote =	{Keywords: resource-bounded Kolmogorov complexity, average-case complexity, pseudorandomness, hardness of approximation, unconditional lower bound}
}

Keywords: resource-bounded Kolmogorov complexity, average-case complexity, pseudorandomness, hardness of approximation, unconditional lower bound
Collection: 37th Computational Complexity Conference (CCC 2022)
Issue Date: 2022
Date of publication: 11.07.2022

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