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          <dc:title>Fourier Growth of Structured 𝔽₂-Polynomials and Applications</dc:title>
          <dc:creator>Błasiok, Jarosław</dc:creator>
          <dc:creator>Ivanov, Peter</dc:creator>
          <dc:creator>Jin, Yaonan</dc:creator>
          <dc:creator>Lee, Chin Ho</dc:creator>
          <dc:creator>Servedio, Rocco A.</dc:creator>
          <dc:creator>Viola, Emanuele</dc:creator>
          <dc:subject>Fourier analysis</dc:subject>
          <dc:subject>Pseudorandomness</dc:subject>
          <dc:subject>Fourier growth</dc:subject>
          <dc:description>We analyze the Fourier growth, i.e. the L₁ Fourier weight at level k (denoted L_{1,k}), of various well-studied classes of "structured" m F₂-polynomials. This study is motivated by applications in pseudorandomness, in particular recent results and conjectures due to [Chattopadhyay et al., 2019; Chattopadhyay et al., 2019; Eshan Chattopadhyay et al., 2020] which show that upper bounds on Fourier growth (even at level k = 2) give unconditional pseudorandom generators. &#13;
Our main structural results on Fourier growth are as follows:  &#13;
- We show that any symmetric degree-d m F₂-polynomial p has L_{1,k}(p) ≤ Pr [p = 1] ⋅ O(d)^k. This quadratically strengthens an earlier bound that was implicit in [Omer Reingold et al., 2013].&#13;
- We show that any read-Δ degree-d m F₂-polynomial p has L_{1,k}(p) ≤ Pr [p = 1] ⋅ (k Δ d)^{O(k)}.&#13;
- We establish a composition theorem which gives L_{1,k} bounds on disjoint compositions of functions that are closed under restrictions and admit L_{1,k} bounds. &#13;
Finally, we apply the above structural results to obtain new unconditional pseudorandom generators and new correlation bounds for various classes of m F₂-polynomials.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Jarosław Błasiok and Peter Ivanov and Yaonan Jin and Chin Ho Lee and Rocco A. Servedio and Emanuele Viola</dc:contributor>
          <dc:date>2021</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 207, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2021)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.APPROX/RANDOM.2021.53</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-147462</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2021.53</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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