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          <dc:title>Quantum Query-To-Communication Simulation Needs a Logarithmic Overhead</dc:title>
          <dc:creator>Chakraborty, Sourav</dc:creator>
          <dc:creator>Chattopadhyay, Arkadev</dc:creator>
          <dc:creator>Mande, Nikhil S.</dc:creator>
          <dc:creator>Paraashar, Manaswi</dc:creator>
          <dc:subject>Quantum query complexity</dc:subject>
          <dc:subject>quantum communication complexity</dc:subject>
          <dc:subject>approximate degree</dc:subject>
          <dc:subject>approximate spectral norm</dc:subject>
          <dc:description>Buhrman, Cleve and Wigderson (STOC'98) observed that for every Boolean function f:{-1,1}ⁿ → {-1,1} and •:{-1,1}² → {-1,1} the two-party bounded-error quantum communication complexity of (f ∘ •) is O(Q(f) log n), where Q(f) is the bounded-error quantum query complexity of f. Note that the bounded-error randomized communication complexity of (f ∘ •) is bounded by O(R(f)), where R(f) denotes the bounded-error randomized query complexity of f. Thus, the BCW simulation has an extra O(log n) factor appearing that is absent in classical simulation. A natural question is if this factor can be avoided. Razborov (IZV MATH'03) showed that the bounded-error quantum communication complexity of Set-Disjointness is Ω(√n). The BCW simulation yields an upper bound of O(√n log n). Høyer and de Wolf (STACS'02) showed that this can be reduced to c^(log^* n) for some constant c, and subsequently Aaronson and Ambainis (FOCS'03) showed that this factor can be made a constant. That is, the quantum communication complexity of the Set-Disjointness function (which is NOR_n ∘ ∧) is O(Q(NOR_n)).&#13;
Perhaps somewhat surprisingly, we show that when • = ⊕, then the extra log n factor in the BCW simulation is unavoidable. In other words, we exhibit a total function F:{-1,1}ⁿ → {-1,1} such that Q^{cc}(F ∘ ⊕) = Θ(Q(F) log n).&#13;
To the best of our knowledge, it was not even known prior to this work whether there existed a total function F and 2-bit function •, such that Q^{cc}(F ∘ •) = ω(Q(F)).</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Sourav Chakraborty and Arkadev Chattopadhyay and Nikhil S. Mande and Manaswi Paraashar</dc:contributor>
          <dc:date>2020</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 169, 35th Computational Complexity Conference (CCC 2020)</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.2020.32</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-125842</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2020.32</dc:identifier>
          <dc:language>eng</dc:language>
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