The classical limit of Quantum Max-Cut
Abstract: It is well-known in physics that the limit of large quantum spin $S$ should be understood as a semiclassical limit. This raises the question of whether such emergent classicality facilitates the approximation of computationally hard quantum optimization problems, such as the local Hamiltonian problem. We demonstrate this explicitly for spin-$S$ generalizations of Quantum Max-Cut ($\mathrm{QMaxCut}S$), equivalent to the problem of finding the ground state energy of an arbitrary spin-$S$ quantum Heisenberg antiferromagnet ($\mathrm{QHA}_S$). We prove that approximating the value of $\mathrm{QHA}_S$ to inverse polynomial accuracy is QMA-complete for all $S$, extending previous results for $S=1/2$. We also present two distinct families of classical approximation algorithms for $\mathrm{QMaxCut}_S$ based on rounding the output of a semidefinite program to a product of Bloch coherent states. The approximation ratios for both our proposed algorithms strictly increase with $S$ and converge to the Bri\"et-Oliveira-Vallentin approximation ratio $\alpha{\mathrm{BOV}} \approx 0.956$ from below as $S \to \infty$.
- R. M. Karp, Reducibility among combinatorial problems (Springer, 2010).
- J. Håstad, Journal of the ACM (JACM) 48, 798 (2001).
- M. X. Goemans and D. P. Williamson, Journal of the ACM (JACM) 42, 1115 (1995).
- P. Raghavendra, in Proceedings of the fortieth annual ACM symposium on Theory of computing (2008) pp. 245–254.
- D. Aharonov, I. Arad, and T. Vidick, The Quantum PCP Conjecture (2013), arXiv:1309.7495 [quant-ph] .
- N. Bansal, S. Bravyi, and B. M. Terhal, Classical approximation schemes for the ground-state energy of quantum and classical Ising spin Hamiltonians on planar graphs (2008), arXiv:0705.1115 [quant-ph] .
- S. Gharibian and J. Kempe, SIAM Journal on Computing 41, 1028 (2012).
- S. Gharibian and O. Parekh (Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2019).
- O. Parekh and K. Thompson, arXiv preprint arXiv:2206.08342 (2022).
- R. King, An Improved Approximation Algorithm for Quantum Max-Cut (2022), arXiv:2209.02589 [quant-ph] .
- E. Lee, Optimizing quantum circuit parameters via SDP (2022), arXiv:2209.00789 [quant-ph] .
- E. Lee, An improved Quantum Max Cut approximation via matching (2024), arXiv:2401.03616 [quant-ph] .
- S. Piddock and A. Montanaro, The complexity of antiferromagnetic interactions and 2D lattices (2015), arXiv:1506.04014 [quant-ph] .
- H. Bethe, Zeitschrift für Physik 71, 205 (1931).
- M. Gaudin, Journal de Physique 37, 1087 (1976).
- F. Haldane, Physical review letters 60, 635 (1988).
- B. S. Shastry, Phys. Rev. Lett. 60, 639 (1988).
- C. Dasgupta and S. Ma, Phys. Rev. B 22, 1305 (1980).
- R. Bhatt and P. Lee, Physical Review Letters 48, 344 (1982).
- D. A. Huse and V. Elser, Phys. Rev. Lett. 60, 2531 (1988).
- S. Piddock and A. Montanaro, Communications in Mathematical Physics 382, 721 (2021).
- E. H. Lieb, Communications in Mathematical Physics 31, 327 (1973).
- S. Weinberg, Lectures on quantum mechanics (Cambridge University Press, 2015).
- R. Delbourgo and J. Fox, Journal of Physics A: Mathematical and General 10, L233 (1977).
- F. A. Berezin, Communications in Mathematical Physics 40, 153 (1975).
- R. O’Donnell and Y. Wu, in Proceedings of the fortieth annual ACM symposium on Theory of computing (2008) pp. 335–344.
- T. S. Cubitt, A. Montanaro, and S. Piddock, Proceedings of the National Academy of Sciences 115, 9497 (2018).
- R. Oliveira and B. M. Terhal, The complexity of quantum spin systems on a two-dimensional square lattice (2008), arXiv:quant-ph/0504050 [quant-ph] .
- A. Anshu, D. Gosset, and K. Morenz (Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020).
- S. Bravyi and M. Hastings, Communications in Mathematical Physics 349, 1 (2017).
- S. Bravyi, D. P. DiVincenzo, and D. Loss, Annals of physics 326, 2793 (2011).
- For a Hamiltonian with eigen-decomposition H^=\sum@\slimits@λλ|ψλ⟩⟨ψλ|^𝐻\sum@subscript\slimits@𝜆𝜆ketsubscript𝜓𝜆brasubscript𝜓𝜆\hat{H}=\sum@\slimits@_{\lambda}\lambda\ket{\psi_{\lambda}}\bra{\psi_{\lambda}}over^ start_ARG italic_H end_ARG = start_POSTSUBSCRIPT italic_λ end_POSTSUBSCRIPT italic_λ | start_ARG italic_ψ start_POSTSUBSCRIPT italic_λ end_POSTSUBSCRIPT end_ARG ⟩ ⟨ start_ARG italic_ψ start_POSTSUBSCRIPT italic_λ end_POSTSUBSCRIPT end_ARG |, the pseudo-inverse is H^0−1=\sum@\slimits@λ≠01λ|ψλ⟩⟨ψλ|superscriptsubscript^𝐻01\sum@subscript\slimits@𝜆01𝜆ketsubscript𝜓𝜆brasubscript𝜓𝜆\hat{H}_{0}^{-1}=\sum@\slimits@_{\lambda\neq 0}\frac{1}{\lambda}\ket{\psi_{% \lambda}}\bra{\psi_{\lambda}}over^ start_ARG italic_H end_ARG start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT start_POSTSUPERSCRIPT - 1 end_POSTSUPERSCRIPT = start_POSTSUBSCRIPT italic_λ ≠ 0 end_POSTSUBSCRIPT divide start_ARG 1 end_ARG start_ARG italic_λ end_ARG | start_ARG italic_ψ start_POSTSUBSCRIPT italic_λ end_POSTSUBSCRIPT end_ARG ⟩ ⟨ start_ARG italic_ψ start_POSTSUBSCRIPT italic_λ end_POSTSUBSCRIPT end_ARG |.
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