Two Combinatorial MA-Complete Problems

Authors Dorit Aharonov, Alex B. Grilo



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Dorit Aharonov
  • Hebrew University of Jerusalem, Israel
Alex B. Grilo
  • Sorbonne Université, CNRS, LIP6, Paris, France

Acknowledgements

We notice that the ACAC problem did not appear in the first version of the this work and we thank an anonymous reviewer who pushed us to define more natural problems. We are grateful to Umesh Vazirani for asking the right question that led to this note. Most of this work was done while A.G. was affiliated to CWI and QuSoft, and part of it was done while A.G. was visiting the Simons Institute for the Theory of Computing.

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Dorit Aharonov and Alex B. Grilo. Two Combinatorial MA-Complete Problems. In 12th Innovations in Theoretical Computer Science Conference (ITCS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 185, pp. 36:1-36:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/LIPIcs.ITCS.2021.36

Abstract

Despite the interest in the complexity class MA, the randomized analog of NP, there are just a few known natural (promise-)MA-complete problems. The first such problem was found by Bravyi and Terhal (SIAM Journal of Computing 2009); this result was then followed by Crosson, Bacon and Brown (PRE 2010) and then by Bravyi (Quantum Information and Computation 2015). Surprisingly, each of these problems is either from or inspired by quantum computation. This fact makes it hard for classical complexity theorists to study these problems, and prevents potential progress, e.g., on the important question of derandomizing MA. 
In this note we define two new natural combinatorial problems and we prove their MA-completeness. The first problem, that we call approximately-clean approximate-connected-component (ACAC), gets as input a succinctly described graph, some of whose vertices are marked. The problem is to decide whether there is a connected component whose vertices are all unmarked, or the graph is far from having this property. The second problem, called SetCSP, generalizes in a novel way the standard constraint satisfaction problem (CSP) into constraints involving sets of strings.
Technically, our proof that SetCSP is MA-complete is a fleshing out of an observation made in (Aharonov and Grilo, FOCS 2019), where it was noted that a restricted case of Bravyi and Terhal’s MA complete problem (namely, the uniform case) is already MA complete; and, moreover, that this restricted case can be stated using classical, combinatorial language. The fact that the first, arguably more natural, problem of ACAC is MA-hard follows quite naturally from this proof as well; while containment of ACAC in MA is simple, based on the theory of random walks. 
We notice that this work, along with a translation of the main result of Aharonov and Grilo to the SetCSP problem, implies that finding a gap-amplification procedure for SetCSP (in the spirit of the gap-amplification procedure introduced in Dinur’s PCP proof) would imply MA=NP. In fact, the problem of finding gap-amplification for SetCSP is equivalent to the MA=NP problem. This provides an alternative new path towards the major problem of derandomizing MA. Deriving a similar statement regarding gap amplification of a natural restriction of $ACAC$ remains an open question.

Subject Classification

ACM Subject Classification
  • Theory of computation → Complexity classes
Keywords
  • Merlin-Arthur proof systems
  • Constraint sastifation problem
  • Random walks

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References

  1. Dorit Aharonov and Alex B. Grilo. Stoquastic PCP vs. Randomness. In FOCS 2019, 2019. URL: http://arxiv.org/abs/1901.05270.
  2. Dorit Aharonov and Alex B. Grilo. Two combinatorial MA-complete problems. arXiv preprint, 2020. URL: http://arxiv.org/abs/2003.13065.
  3. Dorit Aharonov, Wim van Dam, Julia Kempe, Zeph Landau, Seth Lloyd, and Oded Regev. Adiabatic quantum computation is equivalent to standard quantum computation. SIAM Review, 50(4):755-787, 2008. Google Scholar
  4. László Babai. Trading group theory for randomness. In Proceedings of the 17th Annual ACM Symposium on Theory of Computing, pages 421-429, 1985. Google Scholar
  5. László Babai, Lance Fortnow, Noam Nisan, and Avi Wigderson. Bpp has subexponential time simulations unless exptime has publishable proofs. Comput. Complex., 3(4):307-318, October 1993. URL: https://doi.org/10.1007/BF01275486.
  6. Sergey Bravyi. Monte Carlo simulation of stoquastic Hamiltonians. arXiv preprint, 2014. URL: http://arxiv.org/abs/1402.2295.
  7. Sergey Bravyi, Arvid J. Bessen, and Barbara M. Terhal. Merlin-arthur games and stoquastic complexity. arXiv preprint, 2006. URL: http://arxiv.org/abs/quant-ph/0611021.
  8. Sergey Bravyi and Barbara M. Terhal. Complexity of stoquastic frustration-free hamiltonians. SIAM J. Comput., 39(4):1462-1485, 2009. Google Scholar
  9. Elizabeth Crosson, Dave Bacon, and Kenneth R. Brown. Making classical ground-state spin computing fault-tolerant. Phys. Rev. E, 82:031106, September 2010. Google Scholar
  10. Irit Dinur. The PCP Theorem by Gap Amplification. Journal of the ACM, 54(3), 2007. Google Scholar
  11. Andrew Drucker. A pcp characterization of am. In Proceedings of the 38th International Colloquim Conference on Automata, Languages and Programming - Volume Part I, ICALP'11, 2011. Google Scholar
  12. Oded Goldreich and David Zuckerman. Another proof that BPP ⊆ PH (and more). In Studies in Complexity and Cryptography, pages 40-53. Springer-Verlag, 2011. Google Scholar
  13. Johan Håstad, Russell Impagliazzo, Leonid A. Levin, and Michael Luby. A pseudorandom generator from any one-way function. SIAM J. Comput., 28(4), March 1999. Google Scholar
  14. Russell Impagliazzo, Valentine Kabanets, and Avi Wigderson. In search of an easy witness: exponential time vs. probabilistic polynomial time. J. Comput. Syst. Sci., 65(4):672-694, 2002. Google Scholar
  15. Russell Impagliazzo and Avi Wigderson. P = bpp if e requires exponential circuits: Derandomizing the xor lemma. In Proceedings of the Twenty-ninth Annual ACM Symposium on Theory of Computing, STOC '97, pages 220-229. ACM, 1997. URL: https://doi.org/10.1145/258533.258590.
  16. Valentine Kabanets and Russell Impagliazzo. Derandomizing polynomial identity tests means proving circuit lower bounds. Computational Complexity, 13(1):1-46, December 2004. Google Scholar
  17. Alexei Kitaev, A Shen, and M N Vyalyi. Classical and quantum computation. Graduate studies in mathematics. American mathematical society, Providence (R.I.), 2002. URL: http://opac.inria.fr/record=b1100148.
  18. Noam Nisan and Avi Wigderson. Hardness vs randomness. J. Comput. Syst. Sci., 49(2):149-167, 1994. Google Scholar
  19. Peter Shor and Ryan Williams. Mathoverflow: Complete problems for randomized complexity classes. URL: https://mathoverflow.net/questions/34469/complete-problems-for-randomized-complexity-classes. Accessed: 2019-01-14.
  20. Madhu Sudan, Luca Trevisan, and Salil Vadhan. Pseudorandom generators without the xor lemma. Journal of Computer and System Sciences, 62(2):236-266, 2001. Google Scholar
  21. Stathis Zachos and Martin Furer. Probabilistic quantifiers vs. distrustful adversaries. In Seventh Conference on Foundations of Software Technology and Theoretical Computer Science, pages 443-455, 1987. Google Scholar
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