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        <identifier>oai:drops-oai.dagstuhl.de:10149</identifier>
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          <dc:title>Quadratic Time-Space Lower Bounds for Computing Natural Functions with a Random Oracle</dc:title>
          <dc:creator>McKay, Dylan M.</dc:creator>
          <dc:creator>Williams, Richard Ryan</dc:creator>
          <dc:subject>branching programs</dc:subject>
          <dc:subject>random oracles</dc:subject>
          <dc:subject>time-space tradeoffs</dc:subject>
          <dc:subject>lower bounds</dc:subject>
          <dc:subject>SAT</dc:subject>
          <dc:subject>counting complexity</dc:subject>
          <dc:description>We define a model of size-S R-way branching programs with oracles that can make up to S distinct oracle queries over all of their possible inputs, and generalize a lower bound proof strategy of Beame [SICOMP 1991] to apply in the case of random oracles. Through a series of succinct reductions, we prove that the following problems require randomized algorithms where the product of running time and space usage must be Omega(n^2/poly(log n)) to obtain correct answers with constant nonzero probability, even for algorithms with constant-time access to a uniform random oracle (i.e., a uniform random hash function): 
- Given an unordered list L of n elements from [n] (possibly with repeated elements), output [n]-L. 
- Counting satisfying assignments to a given 2CNF, and printing any satisfying assignment to a given 3CNF. Note it is a major open problem to prove a time-space product lower bound of n^{2-o(1)} for the decision version of SAT, or even for the decision problem Majority-SAT. 
- Printing the truth table of a given CNF formula F with k inputs and n=O(2^k) clauses, with values printed in lexicographical order (i.e., F(0^k), F(0^{k-1}1), ..., F(1^k)). Thus we have a 4^k/poly(k) lower bound in this case. 
- Evaluating a circuit with n inputs and O(n) outputs. 
 As our lower bounds are based on R-way branching programs, they hold for any reasonable model of computation (e.g. log-word RAMs and multitape Turing machines).</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Dylan M. McKay and Richard Ryan Williams</dc:contributor>
          <dc:date>2019</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 124, 10th Innovations in Theoretical Computer Science Conference (ITCS 2019)</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.ITCS.2019.56</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-101493</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2019.56</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/3.0/legalcode</dc:rights>
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