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Fine-Grained Reductions and Quantum Speedups for Dynamic Programming

Author Amir Abboud

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Amir Abboud
  • IBM Almaden Research Center, San Jose, California, USA


We thank Karl Bringmann and the anonymous reviewers for helpful feedback.

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Amir Abboud. Fine-Grained Reductions and Quantum Speedups for Dynamic Programming. In 46th International Colloquium on Automata, Languages, and Programming (ICALP 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 132, pp. 8:1-8:13, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2019)


This paper points at a connection between certain (classical) fine-grained reductions and the question: Do quantum algorithms offer an advantage for problems whose (classical) best solution is via dynamic programming? A remarkable recent result of Ambainis et al. [SODA 2019] indicates that the answer is positive for some fundamental problems such as Set-Cover and Travelling Salesman. They design a quantum O^*(1.728^n) time algorithm whereas the dynamic programming O^*(2^n) time algorithms are conjectured to be classically optimal. In this paper, fine-grained reductions are extracted from their algorithms giving the first lower bounds for problems in P that are based on the intriguing Set-Cover Conjecture (SeCoCo) of Cygan et al. [CCC 2010]. In particular, the SeCoCo implies: - a super-linear Omega(n^{1.08}) lower bound for 3-SUM on n integers, - an Omega(n^{k/(c_k)-epsilon}) lower bound for k-SUM on n integers and k-Clique on n-node graphs, for any integer k >= 3, where c_k <= log_2{k}+1.4427. While far from being tight, these lower bounds are significantly stronger than what is known to follow from the Strong Exponential Time Hypothesis (SETH); the well-known n^{Omega(k)} ETH-based lower bounds for k-Clique and k-SUM are vacuous when k is constant. Going in the opposite direction, this paper observes that some "sequential" problems with previously known fine-grained reductions to a "parallelizable" core also enjoy quantum speedups over their classical dynamic programming solutions. Examples include RNA Folding and Least-Weight Subsequence.

Subject Classification

ACM Subject Classification
  • Theory of computation → Problems, reductions and completeness
  • Fine-Grained Complexity
  • Set-Cover
  • 3-SUM
  • k-Clique
  • k-SUM
  • Dynamic Programming
  • Quantum Algorithms


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