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        <identifier>oai:drops-oai.dagstuhl.de:18299</identifier>
        <datestamp>2024-03-06T11:01:33Z</datestamp>
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          <dc:title>Constant-Depth Circuits vs. Monotone Circuits</dc:title>
          <dc:creator>Cavalar, Bruno P.</dc:creator>
          <dc:creator>Oliveira, Igor C.</dc:creator>
          <dc:subject>circuit complexity</dc:subject>
          <dc:subject>monotone circuit complexity</dc:subject>
          <dc:subject>bounded-depth circuis</dc:subject>
          <dc:subject>constraint-satisfaction problems</dc:subject>
          <dc:description>We establish new separations between the power of monotone and general (non-monotone) Boolean circuits:  &#13;
- For every k ≥ 1, there is a monotone function in AC⁰ (constant-depth poly-size circuits) that requires monotone circuits of depth Ω(log^k n). This significantly extends a classical result of Okol'nishnikova [Okol'nishnikova, 1982] and Ajtai and Gurevich [Ajtai and Gurevich, 1987]. In addition, our separation holds for a monotone graph property, which was unknown even in the context of AC⁰ versus mAC⁰. &#13;
- For every k ≥ 1, there is a monotone function in AC⁰[⊕] (constant-depth poly-size circuits extended with parity gates) that requires monotone circuits of size exp(Ω(log^k n)). This makes progress towards a question posed by Grigni and Sipser [Grigni and Sipser, 1992].  These results show that constant-depth circuits can be more efficient than monotone formulas and monotone circuits when computing monotone functions.&#13;
In the opposite direction, we observe that non-trivial simulations are possible in the absence of parity gates: every monotone function computed by an AC⁰ circuit of size s and depth d can be computed by a monotone circuit of size 2^{n - n/O(log s)^{d-1}}. We show that the existence of significantly faster monotone simulations would lead to breakthrough circuit lower bounds. In particular, if every monotone function in AC⁰ admits a polynomial size monotone circuit, then NC² is not contained in NC¹.&#13;
Finally, we revisit our separation result against monotone circuit size and investigate the limits of our approach, which is based on a monotone lower bound for constraint satisfaction problems (CSPs) established by Göös, Kamath, Robere and Sokolov [Göös et al., 2019] via lifting techniques. Adapting results of Schaefer [Thomas J. Schaefer, 1978] and Allender, Bauland, Immerman, Schnoor and Vollmer [Eric Allender et al., 2009], we obtain an unconditional classification of the monotone circuit complexity of Boolean-valued CSPs via their polymorphisms. This result and the consequences we derive from it might be of independent interest.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Bruno P. Cavalar and Igor C. Oliveira</dc:contributor>
          <dc:date>2023</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 264, 38th Computational Complexity Conference (CCC 2023)</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.2023.29</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-182998</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2023.29</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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