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          <dc:title>More on AC^0[oplus] and Variants of the Majority Function</dc:title>
          <dc:creator>Limaye, Nutan</dc:creator>
          <dc:creator>Srinivasan, Srikanth</dc:creator>
          <dc:creator>Tripathi, Utkarsh</dc:creator>
          <dc:subject>AC^0[oplus]</dc:subject>
          <dc:subject>Coin Problem</dc:subject>
          <dc:subject>Promise Majority</dc:subject>
          <dc:description>In this paper we prove two results about AC^0[oplus] circuits.&#13;
(1) We show that for d(N) = o(sqrt(log N/log log N)) and N &lt;= s(N) &lt;= 2^(dN^(1/4d^2)) there is an explicit family of functions {f_N:{0,1}^N - &gt; {0,1}} such that &#13;
- f_N has uniform AC^0 formulas of depth d and size at most s; &#13;
- f_N does not have AC^0[oplus] formulas of depth d and size s^epsilon, where epsilon is a fixed absolute constant. &#13;
 This gives a quantitative improvement on the recent result of Limaye, Srinivasan, Sreenivasaiah, Tripathi, and Venkitesh, (STOC, 2019), which proved a similar Fixed-Depth Size-Hierarchy theorem but for d &lt;&lt; log log N and s &lt;&lt; exp(N^(1/2^Omega(d))). &#13;
As in the previous result, we use the Coin Problem to prove our hierarchy theorem. Our main technical result is the construction of uniform size-optimal formulas for solving the coin problem with improved sample complexity (1/delta)^O(d) (down from (1/delta)^(2^O(d)) in the previous result).&#13;
(2) In our second result, we show that randomness buys depth in the AC^0[oplus] setting. Formally, we show that for any fixed constant d &gt;= 2, there is a family of Boolean functions that has polynomial-sized randomized uniform AC^0 circuits of depth d but no polynomial-sized (deterministic) AC^0[oplus] circuits of depth d.&#13;
Previously Viola (Computational Complexity, 2014) showed that an increase in depth (by at least 2) is essential to avoid superpolynomial blow-up while derandomizing randomized AC^0 circuits. We show that an increase in depth (by at least 1) is essential even for AC^0[oplus]. &#13;
As in Viola’s result, the separating examples are promise variants of the Majority function on N inputs that accept inputs of weight at least N/2 + N/(log N)^(d-1) and reject inputs of weight at most N/2 - N/(log N)^(d-1).</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Nutan Limaye and Srikanth Srinivasan and Utkarsh Tripathi</dc:contributor>
          <dc:date>2019</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 150, 39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:type>publishedVersion</dc:type>
          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/LIPIcs.FSTTCS.2019.22</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-115844</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2019.22</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/3.0/legalcode</dc:rights>
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