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          <dc:title>Quantum Lower and Upper Bounds for 2D-Grid and Dyck Language</dc:title>
          <dc:creator>Ambainis, Andris</dc:creator>
          <dc:creator>Balodis, Kaspars</dc:creator>
          <dc:creator>Iraids, Jānis</dc:creator>
          <dc:creator>Khadiev, Kamil</dc:creator>
          <dc:creator>Kļevickis, Vladislavs</dc:creator>
          <dc:creator>Prūsis, Krišjānis</dc:creator>
          <dc:creator>Shen, Yixin</dc:creator>
          <dc:creator>Smotrovs, Juris</dc:creator>
          <dc:creator>Vihrovs, Jevgēnijs</dc:creator>
          <dc:subject>Quantum query complexity</dc:subject>
          <dc:subject>Quantum algorithms</dc:subject>
          <dc:subject>Dyck language</dc:subject>
          <dc:subject>Grid path</dc:subject>
          <dc:description>We study the quantum query complexity of two problems.&#13;
First, we consider the problem of determining if a sequence of parentheses is a properly balanced one (a Dyck word), with a depth of at most k. We call this the Dyck_{k,n} problem. We prove a lower bound of Ω(c^k √n), showing that the complexity of this problem increases exponentially in k. Here n is the length of the word. When k is a constant, this is interesting as a representative example of star-free languages for which a surprising Õ(√n) query quantum algorithm was recently constructed by Aaronson et al. [Scott Aaronson et al., 2018]. Their proof does not give rise to a general algorithm. When k is not a constant, Dyck_{k,n} is not context-free. We give an algorithm with O(√n(log n)^{0.5k}) quantum queries for Dyck_{k,n} for all k. This is better than the trival upper bound n for k = o({log(n)}/{log log n}). &#13;
Second, we consider connectivity problems on grid graphs in 2 dimensions, if some of the edges of the grid may be missing. By embedding the "balanced parentheses" problem into the grid, we show a lower bound of Ω(n^{1.5-ε}) for the directed 2D grid and Ω(n^{2-ε}) for the undirected 2D grid. The directed problem is interesting as a black-box model for a class of classical dynamic programming strategies including the one that is usually used for the well-known edit distance problem. We also show a generalization of this result to more than 2 dimensions.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Andris Ambainis and Kaspars Balodis and Jānis Iraids and Kamil Khadiev and Vladislavs Kļevickis and Krišjānis Prūsis and Yixin Shen and Juris Smotrovs and Jevgēnijs Vihrovs</dc:contributor>
          <dc:date>2020</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 170, 45th International Symposium on Mathematical Foundations of Computer Science (MFCS 2020)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
          <dc:type>publishedVersion</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.MFCS.2020.8</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-126774</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2020.8</dc:identifier>
          <dc:language>eng</dc:language>
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