## Abstract

The Minimum Circuit Size Problem (MCSP ) has been the focus of intense study recently; MCSP is hard for SZK under rather powerful reductions [4], and is provably not hard under “local” reductions computable in TIME(n^{0.49}) [22]. The question of whether MCSP is NP -hard (or indeed, hard even for small subclasses of P ) under some of the more familiar notions of reducibility (such as many-one or Turing reductions computable in polynomial time or in AC^{0} ) is closely related to many of the longstanding open questions in complexity theory [7, 8, 16–18, 20, 22]. All prior hardness results for MCSP hold also for computing somewhat weak approximations to the circuit complexity of a function [3, 4, 9, 16, 21, 27]. (Subsequent to our work, a new hardness result has been announced [19] that relies on more exact size computations.) Some of these results were proved by exploiting a connection to a notion of time-bounded Kolmogorov complexity (KT ) and the corresponding decision problem (MKTP ). More recently, a new approach for proving improved hardness results for MKTP was developed [5, 7], but this approach establishes only hardness of extremely good approximations of the form 1 + o(1 ), and these improved hardness results are not yet known to hold for MCSP. In particular, it is known that MKTP is hard for the complexity class DET under nonuniform (formula presented) reductions, implying MKTP is not in AC^{0}[ p] for any prime p [7]. It was still open if similar circuit lower bounds hold for MCSP. (But see [13, 19].) One possible avenue for proving a similar hardness result for MCSP would be to improve the hardness of approximation for MKTP beyond 1 + o(1 ) to ω(1 ), as KT -complexity and circuit size are polynomially-related. In this paper, we show that this approach cannot succeed. More specifically, we prove that PARITY does not reduce to the problem of computing superlinear approximations to KT -complexity or circuit size via AC^{0} -Turing reductions that make O(1) queries. This is significant, since approximating any set in P/ poly AC^{0} -reduces to just one query of a much worse approximation of circuit size or KT -complexity [24]. For weaker approximations, we also prove non-hardness under more powerful reductions. Our non-hardness results are unconditional, in contrast to conditional results presented in [7] (for more powerful reductions, but for much worse approximations). This highlights obstacles that would have to be overcome by any proof that MKTP or MCSP is hard for NP under AC^{0} reductions. It may also be a step toward confirming a conjecture of Murray and Williams, that MCSP is not NP -complete under logtime-uniform (formula presented) reductions [22].

Original language | English (US) |
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Title of host publication | Computer Science – Theory and Applications - 14th International Computer Science Symposium in Russia, CSR 2019, Proceedings |

Editors | René van Bevern, Gregory Kucherov |

Publisher | Springer Verlag |

Pages | 13-24 |

Number of pages | 12 |

ISBN (Print) | 9783030199548 |

DOIs | |

State | Published - 2019 |

Event | 14th International Computer Science Symposium in Russia, CSR 2019 - Novosibirsk, Russian Federation Duration: Jul 1 2019 → Jul 5 2019 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11532 LNCS |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

### Conference

Conference | 14th International Computer Science Symposium in Russia, CSR 2019 |
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Country/Territory | Russian Federation |

City | Novosibirsk |

Period | 7/1/19 → 7/5/19 |

## All Science Journal Classification (ASJC) codes

- Theoretical Computer Science
- Computer Science(all)

## Keywords

- Minimum Circuit Size Problem
- NP-completeness
- Reductions
- Time-bounded Kolmogorov complexity