Complexity Classification of Product State Problems for Local Hamiltonians

Authors John Kallaugher, Ojas Parekh , Kevin Thompson, Yipu Wang, Justin Yirka



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John Kallaugher
  • Sandia National Laboratories, Albuquerque, NM, USA
Ojas Parekh
  • Sandia National Laboratories, Albuquerque, NM, USA
Kevin Thompson
  • Sandia National Laboratories, Albuquerque, NM, USA
Yipu Wang
  • Sandia National Laboratories, Albuquerque, NM, USA
Justin Yirka
  • Sandia National Laboratories, Albuquerque, NM, USA
  • The University of Texas at Austin, TX, USA

Acknowledgements

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. This written work is authored by an employee of NTESS. The employee, not NTESS, owns the right, title and interest in and to the written work and is responsible for its contents. Any subjective views or opinions that might be expressed in the written work do not necessarily represent the views of the U.S. Government. The publisher acknowledges that the U.S. Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this written work or allow others to do so, for U.S. Government purposes. The DOE will provide public access to results of federally sponsored research in accordance with the DOE Public Access Plan.

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John Kallaugher, Ojas Parekh, Kevin Thompson, Yipu Wang, and Justin Yirka. Complexity Classification of Product State Problems for Local Hamiltonians. In 16th Innovations in Theoretical Computer Science Conference (ITCS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 325, pp. 63:1-63:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.ITCS.2025.63

Abstract

Product states, unentangled tensor products of single qubits, are a ubiquitous ansatz in quantum computation, including for state-of-the-art Hamiltonian approximation algorithms. A natural question is whether we should expect to efficiently solve product state problems on any interesting families of Hamiltonians.
We completely classify the complexity of finding minimum-energy product states for Hamiltonians defined by any fixed set of allowed 2-qubit interactions. Our results follow a line of work classifying the complexity of solving Hamiltonian problems and classical constraint satisfaction problems based on the allowed constraints. We prove that estimating the minimum energy of a product state is in 𝖯 if and only if all allowed interactions are 1-local, and NP-complete otherwise. Equivalently, any family of non-trivial two-body interactions generates Hamiltonians with NP-complete product-state problems. Our hardness constructions only require coupling strengths of constant magnitude.
A crucial component of our proofs is a collection of hardness results for a new variant of the Vector Max-Cut problem, which should be of independent interest. Our definition involves sums of distances rather than squared distances and allows linear stretches.
We similarly give a proof that the original Vector Max-Cut problem is NP-complete in 3 dimensions. This implies hardness of optimizing product states for Quantum Max-Cut (the quantum Heisenberg model) is NP-complete, even when every term is guaranteed to have positive unit weight.

Subject Classification

ACM Subject Classification
  • Theory of computation → Quantum complexity theory
Keywords
  • quantum complexity
  • quantum algorithms
  • local hamiltonians

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References

  1. Sanjeev Arora and Boaz Barak. Computational complexity: a modern approach. Cambridge University Press, 2009. Google Scholar
  2. Afonso S. Bandeira, Christopher Kennedy, and Amit Singer. Approximating the little Grothendieck problem over the orthogonal and unitary groups. Mathematical programming, 160:433-475, 2016. URL: https://doi.org/10.1007/s10107-016-0993-7.
  3. Alexander I. Barvinok. Problems of distance geometry and convex properties of quadratic maps. Discrete & Computational Geometry, 13:189-202, 1995. URL: https://doi.org/10.1007/BF02574037.
  4. Fernando G.S.L. Brandão and Aram W. Harrow. Product-state approximations to quantum states. Commun. Math. Phys., 342:47-80, 2016. URL: https://doi.org/10.1007/s00220-016-2575-1.
  5. Sergey Bravyi, David Gosset, Robert König, and Kristan Temme. Approximation algorithms for quantum many-body problems. Journal of Mathematical Physics, 60(3):032203, 2019. URL: https://doi.org/10.1063/1.5085428.
  6. Sergey Bravyi and Matthew Hastings. On complexity of the quantum Ising model. Communications in Mathematical Physics, 349(1):1-45, 2017. URL: https://doi.org/10.1007/s00220-016-2787-4.
  7. Jop Briët, Harry Buhrman, and Ben Toner. A generalized Grothendieck inequality and nonlocal correlations that require high entanglement. Communications in mathematical physics, 305(3):827-843, 2011. URL: https://doi.org/10.1007/s00220-011-1280-3.
  8. Jop Briët, Fernando Mário de Oliveira Filho, and Frank Vallentin. The positive semidefinite Grothendieck problem with rank constraint. In International Colloquium on Automata, Languages, and Programming, pages 31-42. Springer, 2010. URL: https://doi.org/10.1007/978-3-642-14165-2_4.
  9. Jop Briët, Oded Regev, and Rishi Saket. Tight hardness of the non-commutative Grothendieck problem. Theory of Computing, 13(15):1-24, 2017. URL: https://doi.org/10.4086/toc.2017.v013a015.
  10. Anne Broadbent and Alex Bredariol Grilo. QMA-hardness of consistency of local density matrices with applications to quantum zero-knowledge. SIAM Journal on Computing, 51(4):1400-1450, 2022. URL: https://doi.org/10.1137/21M140729X.
  11. Samuel Burer and Renato D.C. Monteiro. A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization. Mathematical programming, 95(2):329-357, 2003. URL: https://doi.org/10.1007/s10107-002-0352-8.
  12. Nadia Creignou. A dichotomy theorem for maximum generalized satisfiability problems. Journal of Computer and System Sciences, 51(3):511-522, 1995. URL: https://doi.org/10.1006/jcss.1995.1087.
  13. Nadia Creignou, Sanjeev Khanna, and Madhu Sudan. Complexity classifications of Boolean constraint satisfaction problems. SIAM, 2001. Google Scholar
  14. Toby Cubitt and Ashley Montanaro. Complexity classification of local Hamiltonian problems. SIAM Journal on Computing, 45(2):268-316, 2016. URL: https://doi.org/10.1137/140998287.
  15. Toby S. Cubitt, Ashley Montanaro, and Stephen Piddock. Universal quantum Hamiltonians. Proceedings of the National Academy of Sciences, 115(38):9497-9502, August 2018. URL: https://doi.org/10.1073/pnas.1804949115.
  16. Sevag Gharibian, Yichen Huang, Zeph Landau, Seung Woo Shin, et al. Quantum Hamiltonian complexity. Foundations and Trends in Theoretical Computer Science, 10(3):159-282, 2015. URL: https://doi.org/10.1561/0400000066.
  17. Sevag Gharibian and Julia Kempe. Approximation algorithms for QMA-complete problems. SIAM Journal on Computing, 41(4):1028-1050, 2012. URL: https://doi.org/10.1137/110842272.
  18. Sevag Gharibian and Ojas Parekh. Almost Optimal Classical Approximation Algorithms for a Quantum Generalization of Max-Cut. In Approximation, Randomization, and Combinatorial Optimization (APPROX/RANDOM 2019), volume 145 of Leibniz International Proceedings in Informatics (LIPIcs), pages 31:1-31:17. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019. URL: https://doi.org/10.4230/LIPIcs.APPROX-RANDOM.2019.31.
  19. Michel X. Goemans and David P Williamson. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming. J. ACM, 42(6):1115-1145, 1995. URL: https://doi.org/10.1145/227683.227684.
  20. Sean Hallgren, Eunou Lee, and Ojas Parekh. An approximation algorithm for the max-2-local Hamiltonian problem. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020). Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. URL: https://doi.org/10.4230/LIPIcs.APPROX/RANDOM.2020.59.
  21. Ryszard Horodecki et al. Information-theoretic aspects of inseparability of mixed states. Phys. Rev. A, 54(3):1838-1843, 1996. URL: https://doi.org/10.1103/PhysRevA.54.1838.
  22. Yeongwoo Hwang, Joe Neeman, Ojas Parekh, Kevin Thompson, and John Wright. Unique games hardness of Quantum Max-Cut, and a conjectured vector-valued Borell’s inequality. In Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 1319-1384. SIAM, 2023. URL: https://doi.org/10.1137/1.9781611977554.ch48.
  23. Peter Jonsson. Boolean constraint satisfaction: complexity results for optimization problems with arbitrary weights. Theoretical Computer Science, 244(1-2):189-203, 2000. URL: https://doi.org/10.1016/S0304-3975(98)00343-0.
  24. Peter Jonsson, Mikael Klasson, and Andrei Krokhin. The approximability of three-valued Max CSP. SIAM Journal on Computing, 35(6):1329-1349, 2006. URL: https://doi.org/10.1137/S009753970444644X.
  25. Sanjeev Khanna, Madhu Sudan, and David P Williamson. A complete classification of the approximability of maximization problems derived from boolean constraint satisfaction. In Proceedings of the twenty-ninth annual ACM symposium on Theory of computing, pages 11-20, 1997. URL: https://doi.org/10.1145/258533.258538.
  26. Alexei Yu Kitaev, Alexander Shen, and Mikhail N Vyalyi. Classical and quantum computation. Number 47 in Graduate Studies in Mathematics. American Mathematical Soc., 2002. Google Scholar
  27. Yi-Kai Liu. Consistency of local density matrices is QMA-complete. In Josep Díaz, Klaus Jansen, José D. P. Rolim, and Uri Zwick, editors, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, pages 438-449, Berlin, Heidelberg, 2006. Springer Berlin Heidelberg. URL: https://doi.org/10.1007/11830924_40.
  28. L. Lovász. Semidefinite Programs and Combinatorial Optimization, pages 137-194. Springer New York, New York, NY, 2003. URL: https://doi.org/10.1007/0-387-22444-0_6.
  29. László Lovász. Graphs and geometry, volume 65. American Mathematical Soc., 2019. Google Scholar
  30. Hiroshi Maehara. On the total edge-length of a tetrahedron. The American Mathematical Monthly, 108(10):967-969, 2001. URL: http://www.jstor.org/stable/2695418.
  31. Ojas Parekh and Kevin Thompson. Beating random assignment for approximating quantum 2-local Hamiltonian problems. In 29th Annual European Symposium on Algorithms (ESA 2021), volume 204 of Leibniz International Proceedings in Informatics (LIPIcs), pages 74:1-74:18. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021. URL: https://doi.org/10.4230/LIPIcs.ESA.2021.74.
  32. Ojas Parekh and Kevin Thompson. An optimal product-state approximation for 2-local quantum Hamiltonians with positive terms, 2022. URL: https://arxiv.org/abs/2206.08342v1.
  33. Stephen Piddock and Ashley Montanaro. The complexity of antiferromagnetic interactions and 2D lattices. Quantum Info. Comput., 17(7-8):636-672, 2017. URL: https://doi.org/10.5555/3179553.3179559.
  34. Stephen Piddock and Ashley Montanaro. Universal qudit Hamiltonians, 2018. URL: https://arxiv.org/abs/1802.07130.
  35. Thomas J. Schaefer. The complexity of satisfiability problems. In Proceedings of the tenth annual ACM symposium on Theory of computing, pages 216-226, 1978. URL: https://doi.org/10.1145/800133.804350.
  36. Johan Thapper and Stanislav Živnỳ. The complexity of finite-valued CSPs. Journal of the ACM, 63(4):1-33, 2016. URL: https://doi.org/10.1145/2974019.
  37. G. Thompson. Normal forms for skew-symmetric matrices and Hamiltonian systems with first integrals linear in momenta. Proc. of the Amer. Math. Soc., 104(3):910-916, 1988. URL: https://doi.org/10.2307/2046815.
  38. John Watrous. The theory of quantum information. Cambridge university press, 2018. Google Scholar
  39. Pawel Wocjan and Thomas Beth. The 2-local Hamiltonian problem encompasses NP. International Journal of Quantum Information, 1(03):349-357, 2003. URL: https://doi.org/10.1142/S021974990300022X.
  40. John Wright. Personal communication, 2022. Google Scholar
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