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Gauge-invariant quantum minimally entangled typical thermal states algorithm with mutually unbiased physical bases for Z2 lattice gauge theories at finite temperature and density

Reita Maeno*

  • *Contact author: maeno-reita916@g.ecc.u-tokyo.ac.jp

Phys. Rev. Research 8, 033306 – Published 14 September, 2026

DOI: https://doi.org/10.1103/qyj2-97tw

Abstract

In quantum computations of gauge theories at finite temperature and finite density, enforcing Gauss's law for all states contributing to the thermal ensemble is a nontrivial challenge. In this work, we adapt the quantum minimally entangled typical thermal states (QMETTS) algorithm to Z2 gauge-constrained systems and propose a method for computing finite-temperature and finite-density expectation values without eliminating redundant gauge-field degrees of freedom. In QMETTS, the thermal ensemble is sampled via a Markov chain of pure states generated by imaginary-time evolution and projective measurements. To preserve gauge invariance while maintaining efficient sampling, we introduce measurement bases that are gauge invariant and mutually unbiased within the physical subspace. We show that such measurement bases can be constructed efficiently for Z2 lattice gauge theories in arbitrary spatial dimensions and arbitrary boundary conditions by exploiting the correspondence between Z2 lattice gauge theories and the stabilizer formalism. Furthermore, since expectation-value estimation on quantum hardware is inherently affected by shot noise, we explicitly incorporate shot noise into the analysis. By formulating a finite-shot version of QMETTS, we show that the resulting estimator remains unbiased and that using one observable-measurement shot per sampled state is nearly optimal in terms of variance when the total number of circuit executions used to generate the Markov chain and measure observables is fixed. This result indicates that it is often more efficient to generate more QMETTS samples than to accurately estimate the expectation value for each individual pure state. We validate the proposed method numerically in a (1+1)-dimensional Z2 lattice gauge theory coupled to staggered fermions. Our results provide a gauge-invariant sampling framework for finite-temperature and finite-density quantum algorithms for lattice gauge theories.

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References (61)

  1. M. A. Stephanov, QCD phase diagram: An overview, PoS LAT 2006, 024 (2006).
  2. K. Fukushima and T. Hatsuda, The phase diagram of dense QCD, Rep. Prog. Phys. 74, 014001 (2011).
  3. E. V. Shuryak, Quantum chromodynamics and the theory of superdense matter, Phys. Rep. 61, 71 (1980).
  4. K. G. Wilson, Confinement of quarks, Phys. Rev. D 10, 2445 (1974).
  5. J. B. Kogut and L. Susskind, Hamiltonian formulation of Wilson's lattice gauge theories, Phys. Rev. D 11, 395 (1975).
  6. S. Durr et al., Ab initio determination of light hadron masses, Science 322, 1224 (2008).
  7. K. Nagata, Finite-density lattice QCD and sign problem: Current status and open problems, Prog. Part. Nucl. Phys. 127, 103991 (2022).
  8. C.-F. Chen, M. J. Kastoryano, F. G. S. L. Brandão, and A. Gilyén, Efficient quantum thermal simulation, Nature (London) 646, 561 (2025).
  9. C.-F. Chen, M. J. Kastoryano, and A. Gilyén, An efficient and exact noncommutative quantum Gibbs sampler, arXiv:2311.09207.
  10. M. Consiglio, J. Settino, A. Giordano, C. Mastroianni, F. Plastina, S. Lorenzo, S. Maniscalco, J. Goold, and T. J. G. Apollaro, Variational Gibbs state preparation on noisy intermediate-scale quantum devices, Phys. Rev. A 110, 012445 (2024).
  11. T. J. Sewell, C. D. White, and B. Swingle, Thermal multi-scale entanglement renormalization ansatz for variational Gibbs state preparation, arXiv:2210.16419.
  12. M. Motta, C. Sun, A. T. K. Tan, M. J. O. Rourke, E. Ye, A. J. Minnich, F. G. S. L. Brandão, and G. K.- L. Chan, Determining eigenstates and thermal states on a quantum computer using quantum imaginary time evolution, Nat. Phys. 16, 205 (2020).
  13. I.-C. Chen, J. C. Getelina, K. Pollock, A. Khindanov, S. Sen, Y.-X. Yao, and T. Iadecola, Classical and quantum simulations of 1 + 1-dimensional Z2 gauge theory at finite temperature and density, Commun. Phys. 8, 375 (2025).
  14. A. Tomiya, Schwinger model at finite temperature and density with beta VQE, arXiv:2205.08860.
  15. F. Turro, A. Ciavarella, and X. Yao, Classical and quantum computing of shear viscosity for (2 + 1)D SU(2) gauge theory, Phys. Rev. D 109, 114511 (2024).
  16. F. Turro and X. Yao, Emergent hydrodynamic mode on SU(2) plaquette chains and quantum simulation, Phys. Rev. D 111, 094502 (2025).
  17. A. T. Than et al., The phase diagram of quantum chromodynamics in one dimension on a quantum computer, Nat. Commun. 16, 10288 (2025).
  18. T. Schmale and H. Weimer, Stabilizing quantum simulations of lattice gauge theories by dissipation, Phys. Rev. Res. 6, 033306 (2024).
  19. E. Ballini, J. Mildenberger, M. M. Wauters, and P. Hauke, Symmetry verification for noisy quantum simulations of non-Abelian lattice gauge theories, Quantum 9, 1802 (2025).
  20. A. Rajput, A. Roggero, and N. Wiebe, Quantum error correction with gauge symmetries, npj Quantum Inf. 9, 41 (2023).
  21. M. Carena, H. Lamm, Y.-Y. Li, and W. Liu, Quantum error thresholds for gauge-redundant digitizations of lattice field theories, Phys. Rev. D 110, 054516 (2024).
  22. L. Spagnoli, A. Roggero, and N. Wiebe, Fault-tolerant simulation of lattice gauge theories with gauge covariant codes, Quantum 10, 1968 (2026).
  23. Z. Davoudi, N. Mueller, and C. Powers, Towards quantum computing phase diagrams of gauge theories with thermal pure quantum states, Phys. Rev. Lett. 131, 081901 (2023).
  24. M. Fromm, O. Philipsen, M. Spannowsky, and C. Winterowd, Simulating Z2 lattice gauge theory with the variational quantum thermalizer, EPJ Quantum Technol. 11, 20 (2024).
  25. E. Ballini, G. Clemente, M. D'Elia, L. Maio, and K. Zambello, Quantum computation of thermal averages for a non-Abelian D4 lattice gauge theory via quantum Metropolis sampling, Phys. Rev. D 109, 034510 (2024).
  26. M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information (Cambridge University Press, Cambridge, 2010).
  27. D. Gottesman, Stabilizer codes and quantum error correction, Caltech, Ph.D. thesis, 1997.
  28. M. Binder and T. Barthel, Symmetric minimally entangled typical thermal states for canonical and grand-canonical ensembles, Phys. Rev. B 95, 195148 (2017).
  29. S. Goto and I. Danshita, Quasiexact Kondo dynamics of fermionic alkaline-earth-like atoms at finite temperatures, Phys. Rev. Lett. 123, 143002 (2019).
  30. D. Horn, M. Weinstein, and S. Yankielowicz, Hamiltonian approach to Z(N) lattice gauge theories, Phys. Rev. D 19, 3715 (1979).
  31. J. Mildenberger, W. Mruczkiewicz, J. C. Halimeh, Z. Jiang, and P. Hauke, Confinement in a Z2 lattice gauge theory on a quantum computer, Nat. Phys. 21, 312 (2025).
  32. T. Hayata, K. Seki, and A. Yamamoto, Floquet prethermalization of Z2 lattice gauge theory on superconducting qubits, Phys. Rev. D 110, 114503 (2024).
  33. P. Jordan and E. P. Wigner, About the Pauli exclusion principle, Z. Phys. 47, 631 (1928).
  34. S. R. White and E. M. Stoudenmire, Minimally entangled typical thermal state algorithms, New J. Phys. 12, 023026 (2010).
  35. S. R. White, Minimally entangled typical quantum states at finite temperature, Phys. Rev. Lett. 102, 190601 (2009).
  36. N. Madras and A. D. Sokal, The pivot algorithm: A highly efficient Monte Carlo method for the self-avoiding walk, J. Stat. Phys. 50, 109 (1988).
  37. A. Sokal, Monte Carlo methods in statistical mechanics: Foundations and new algorithms, in Functional Integration: Basics and Applications (Springer, Berlin, 1997), pp. 131–192.
  38. U. Wolff (ALPHA Collaboration), Monte Carlo errors with less errors, Comput. Phys. Commun. 156, 143 (2004).
  39. B. Bruognolo, J. von Delft, and A. Weichselbaum, Symmetric minimally entangled typical thermal states, Phys. Rev. B 92, 115105 (2015).
  40. W. K. Wootters and B. D. Fields, Optimal state-determination by mutually unbiased measurements, Ann. Phys. 191, 363 (1989).
  41. S. Aaronson and D. Gottesman, Improved simulation of stabilizer circuits, Phys. Rev. A 70, 052328 (2004).
  42. In Figs. 7 and 8, no initial samples are discarded as burn-in, yet the QMETTS estimates for LKS=8 remain consistent with the exact results within statistical fluctuations. This provides additional evidence that burn-in effects are not practically significant for the chain lengths and parameter ranges considered here.
  43. The integrated autocorrelation time can become slightly negative due to statistical fluctuations for the short-chain case with Nchain=40. To avoid underestimating the statistical uncertainty, we conservatively replace estimates below unity by max(τ(Nshot),1).
  44. M. Kliesch, C. Gogolin, M. J. Kastoryano, A. Riera, and J. Eisert, Locality of temperature, Phys. Rev. X 4, 031019 (2014).
  45. D. Gottesman, Fault tolerant quantum computation with higher dimensional systems, Chaos, Solitons Fractals 10, 1749 (1999).
  46. V. Gheorghiu, Standard form of qudit stabilizer groups, Phys. Lett. A 378, 505 (2014).
  47. L. Spagnoli, A. Roggero, and N. Wiebe, Qudit stabiliser codes for ZN lattice gauge theories with matter, arXiv:2602.20661.
  48. M. Turco, L. Spagnoli, and A. Roggero, Binary Gauss stabilizers for Abelian lattice gauge theories, arXiv:2607.14861.
  49. J. R. Stryker, Oracles for Gauss's law on digital quantum computers, Phys. Rev. A 99, 042301 (2019).
  50. J. P. Lacambra, A. Chatwin-Davies, M. Honda, and P. A. Hoehn, Gauss law codes and vacuum codes from lattice gauge theories, arXiv:2604.06087.
  51. X. Yao, Quantum error correction codes for truncated SU(2) lattice gauge theories, Phys. Rev. D 113, 114512 (2026).
  52. M. Sekiyama and L. Nagano, Ground state preparation in two-dimensional pure Z2 lattice gauge theory via deterministic quantum imaginary time evolution, arXiv:2604.17874 [Phys. Rev. D (to be published)].
  53. T. Kosugi, Y. Nishiya, H. Nishi, and Y.-I. Matsushita, Imaginary-time evolution using forward and backward real-time evolution with a single ancilla: First-quantized eigensolver algorithm for quantum chemistry, Phys. Rev. Res. 4, 033121 (2022).
  54. F. Turro, A. Roggero, V. Amitrano, P. Luchi, K. A. Wendt, J. L. DuBois, S. Quaglioni, and F. Pederiva, Imaginary-time propagation on a quantum chip, Phys. Rev. A 105, 022440 (2022).
  55. A. Gilyén, Y. Su, G. H. Low, and N. Wiebe, Quantum singular value transformation and beyond: Exponential improvements for quantum matrix arithmetics, in 51st annual, ACM SIGACT Symp. Theory Comput. 6, 193 (2018).
  56. K. Hejazi, M. Motta, and G. K.-L. Chan, Adiabatic quantum imaginary time evolution, Phys. Rev. Res. 6, 033084 (2024).
  57. M. Gluza, J. Son, B. H. Tiang, R. Zander, R. Seidel, Y. Suzuki, Z. Holmes, and N. H. Y. Ng, Double-bracket quantum algorithms for quantum imaginary-time evolution, Phys. Rev. Lett. 136, 020601 (2026).
  58. N. Matsumoto, S. Tsutsui, Y. O. Nakagawa, Y. Hidaka, S. Kanasugi, K. Maruyama, H. Oshima, and S. Sato, Quantum many-body simulation of finite-temperature systems with sampling a series expansion of a quantum imaginary-time evolution, Phys. Rev. Res. 7, 013254 (2025).
  59. C. Moore and M. Nilsson, Parallel quantum computation and quantum codes, SIAM J. Comput. 31, 799 (2012).
  60. As follows from Theorem t5, the stabilizer generators corresponding to Gauss's law constraints are assumed to be independent. If the original set of Gauss's law operators contains redundant constraints, we first replace it with an independent generating subset.
  61. A. M. Childs, Y. Su, M. C. Tran, N. Wiebe, and S. Zhu, Theory of Trotter error with commutator scaling, Phys. Rev. X 11, 011020 (2021).

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