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        <identifier>oai:drops-oai.dagstuhl.de:24432</identifier>
        <datestamp>2025-12-12T15:01:49Z</datestamp>
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          <dc:title>Testing Isomorphism of Boolean Functions over Finite Abelian Groups</dc:title>
          <dc:creator>Datta, Swarnalipa</dc:creator>
          <dc:creator>Ghosh, Arijit</dc:creator>
          <dc:creator>Kayal, Chandrima</dc:creator>
          <dc:creator>Paraashar, Manaswi</dc:creator>
          <dc:creator>Roy, Manmatha</dc:creator>
          <dc:subject>Analysis of Boolean functions</dc:subject>
          <dc:subject>Abelian groups</dc:subject>
          <dc:subject>Automorphism group</dc:subject>
          <dc:subject>Function isomorphism</dc:subject>
          <dc:subject>Spectral norm</dc:subject>
          <dc:description>Let f and g be Boolean functions over a finite Abelian group 𝒢, where g is fully known and f is accessible via queries; that is, given any x ∈ 𝒢, we can obtain the value f(x). We study the problem of tolerant isomorphism testing: given parameters ε ≥ 0 and τ &gt; 0, the goal is to determine, using as few queries as possible, whether there exists an automorphism σ of 𝒢 such that the fractional Hamming distance between f∘σ and g is at most ε, or whether for every automorphism σ, the distance is at least ε + τ.&#13;
We design an efficient tolerant property testing algorithm for this problem over finite Abelian groups with constant exponent. The exponent of a finite group refers to the largest order of any element in the group. The query complexity of our algorithm is polynomial in s and 1/τ, where s bounds the spectral norm of the function g, and τ is the tolerance parameter. In addition, we present an improved algorithm in the case where g is Fourier sparse, meaning that its Fourier expansion contains only a small number of nonzero coefficients.&#13;
Our approach draws on key ideas from Abelian group theory and Fourier analysis, including the annihilator of a subgroup, Pontryagin duality, and a pseudo inner product defined over finite Abelian groups. We believe that these techniques will be useful more broadly in the design of property testing algorithms.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Swarnalipa Datta and Arijit Ghosh and Chandrima Kayal and Manaswi Paraashar and Manmatha Roy</dc:contributor>
          <dc:date>2025</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 353, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.APPROX/RANDOM.2025.66</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-244328</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2025.66</dc:identifier>
          <dc:language>eng</dc:language>
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