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        <datestamp>2024-03-06T10:37:10Z</datestamp>
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          <dc:title>Limits of Minimum Circuit Size Problem as Oracle</dc:title>
          <dc:creator>Hirahara, Shuichi</dc:creator>
          <dc:creator>Watanabe, Osamu</dc:creator>
          <dc:subject>minimum circuit size problem</dc:subject>
          <dc:subject>NP-completeness</dc:subject>
          <dc:subject>randomized reductions</dc:subject>
          <dc:subject>resource-bounded Kolmogorov complexity</dc:subject>
          <dc:subject>Turing reductions</dc:subject>
          <dc:description>The Minimum Circuit Size Problem (MCSP) is known to be hard for statistical zero knowledge via a BPP-Turing reduction (Allender and Das, 2014), whereas establishing NP-hardness of MCSP via a polynomial-time many-one reduction is difficult (Murray and Williams, 2015) in the sense that it implies ZPP != EXP, which is a major open problem in computational complexity.  &#13;
&#13;
In this paper, we provide strong evidence that current techniques cannot establish NP-hardness of MCSP, even under polynomial-time Turing reductions or randomized reductions: Specifically, we introduce the notion of oracle-independent reduction to MCSP, which captures all the currently known reductions.  We say that a reduction to MCSP is oracle-independent if the reduction can be generalized to a reduction to MCSP^A for any oracle A, where MCSP^A denotes an oracle version of MCSP. We prove that no language outside P is reducible to MCSP via an oracle-independent polynomial-time Turing reduction. We also show that the class of languages reducible to MCSP via an oracle-independent randomized reduction that makes at most one query is contained in AM intersect coAM. Thus, NP-hardness of MCSP cannot be established via such oracle-independent reductions unless the polynomial hierarchy collapses.  &#13;
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We also extend the previous results to the case of more general reductions: We prove that establishing NP-hardness of MCSP via a polynomial-time nonadaptive reduction implies ZPP != EXP, and that establishing NP-hardness of approximating circuit complexity via a polynomial-time Turing reduction also implies ZPP != EXP. Along the way, we prove that approximating Levin's Kolmogorov complexity is provably not EXP-hard under polynomial-time Turing reductions, which is of independent interest.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Shuichi Hirahara and Osamu Watanabe</dc:contributor>
          <dc:date>2016</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 50, 31st Conference on Computational Complexity (CCC 2016)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.CCC.2016.18</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-58426</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2016.18</dc:identifier>
          <dc:language>eng</dc:language>
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