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Evaluating Many-Body Stabilizer Rényi Entropy by Sampling Reduced Pauli Strings: Singularities, Volume Law, and Nonlocal Magic

Yi-Ming Ding1,2,3,*, Zhe Wang2,3, and Zheng Yan2,3,†

  • 1State Key Laboratory of Surface Physics and Department of Physics, Fudan University, Shanghai 200438, China
  • 2Department of Physics, School of Science and Research Center for Industries of the Future, Westlake University, Hangzhou 310030, China
  • 3Institute of Natural Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, China

  • *Contact author: dingyiming@westlake.edu.cn
  • †Contact author: zhengyan@westlake.edu.cn

PRX Quantum 6, 030328 – Published 18 August, 2025

DOI: https://doi.org/10.1103/pyzr-jmvw

Abstract

We present a novel quantum Monte Carlo method for evaluating the α-stabilizer Rényi entropy (SRE) for any integer α≥2. By interpreting the α-SRE as partition-function ratios, we eliminate the sign problem in the imaginary-time path integral by sampling reduced Pauli strings within a reduced configuration space, which enables efficient classical computations of the α-SRE and its derivatives to explore magic in previously inaccessible two- or higher-dimensional systems. We first isolate the free-energy part in 2-SRE, which is a trivial term. Notably, at quantum critical points in one-dimensional or two-dimensional transverse-field Ising (TFI) models, we reveal nontrivial singularities associated with the characteristic function contribution, directly tied to magic. Their interplay leads to complicated behaviors of 2-SRE, avoiding extrema at critical points generally. In contrast, analyzing the volume-law correction to SRE reveals a discontinuity tied to criticalities, suggesting that it is more informative than the full-state magic. For conformal critical points, we claim that it could reflect nonlocal magic residing in correlations. Finally, we verify that 2-SRE fails to characterize magic in mixed states (e.g., Gibbs states), yielding nonphysical results. This work provides a powerful tool for exploring the roles of magic in large-scale many-body systems and reveals the intrinsic relation between magic and many-body physics.

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References (101)

  1. S. Sachdev, Quantum phase transitions, Physics World 12, 33 (1999).
  2. S. M. Girvin and K. Yang, Modern Condensed Matter Physics (Cambridge University Press, New York, 2019).
  3. E. Chitambar and G. Gour, Quantum resource theories, Rev. Mod. Phys. 91, 025001 (2019).
  4. L. Amico, R. Fazio, A. Osterloh, and V. Vedral, Entanglement in many-body systems, Rev. Mod. Phys. 80, 517 (2008).
  5. B. Zeng, X. Chen, D.-L. Zhou, and X.-G. Wen, in Quantum Information Meets Quantum Matter: From Quantum Entanglement to Topological Phases of Many-Body Systems (Springer New York, New York, 2019).
  6. N. Laflorencie, Quantum entanglement in condensed matter systems, Phys. Rep. 646, 1 (2016), quantum entanglement in condensed matter systems.
  7. A. Heimendahl, M. Heinrich, and D. Gross, The axiomatic and the operational approaches to resource theories of magic do not coincide, J. Math. Phys. 63, 112201 (2022).
  8. V. Veitch, S. A. H. Mousavian, D. Gottesman, and J. Emerson, The resource theory of stabilizer quantum computation, New J. Phys. 16, 013009 (2014).
  9. C. D. White, C. Cao, and B. Swingle, Conformal field theories are magical, Phys. Rev. B 103, 075145 (2021).
  10. Z.-W. Liu and A. Winter, Many-body quantum magic, PRX Quantum 3, 020333 (2022).
  11. P. S. Tarabunga, E. Tirrito, T. Chanda, and M. Dalmonte, Many-body magic via Pauli-Markov chains—from criticality to gauge theories, PRX Quantum 4, 040317 (2023).
  12. D. Gottesman, The heisenberg representation of quantum computers, Group22: Proceedings of the XXII International Colloquium on Group Theoretical Methods in Physics, eds. S. P. Corney, R. Delbourgo, and P. D. Jarvis (Cambridge, Massachusetts, International Press, 1999) (1998), p. 32, ArXiv:quant-ph/9807006.
  13. S. Aaronson and D. Gottesman, Improved simulation of stabilizer circuits, Phys. Rev. A 70, 052328 (2004).
  14. M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information: 10th Anniversary Edition (Cambridge University Press, Cambridge, 2010).
  15. S. Sarkar, C. Mukhopadhyay, and A. Bayat, Characterization of an operational quantum resource in a critical many-body system, New J. Phys. 22, 083077 (2020).
  16. T. Haug and L. Piroli, Stabilizer entropies and nonstabilizerness monotones, Quantum 7, 1092 (2023).
  17. T. Haug and L. Piroli, Quantifying nonstabilizerness of matrix product states, Phys. Rev. B 107, 035148 (2023).
  18. G. Lami and M. Collura, Nonstabilizerness via perfect Pauli sampling of matrix product states, Phys. Rev. Lett. 131, 180401 (2023).
  19. P. S. Tarabunga, Critical behaviors of non-stabilizerness in quantum spin chains, Quantum 8, 1413 (2024).
  20. P. S. Tarabunga and C. Castelnovo, Magic in generalized Rokhsar-Kivelson wavefunctions, Quantum 8, 1347 (2024).
  21. L. Leone, S. F. E. Oliviero, Y. Zhou, and A. Hamma, Quantum chaos is quantum, Quantum 5, 453 (2021).
  22. L. Leone, S. F. E. Oliviero, and A. Hamma, Stabilizer Rényi entropy, Phys. Rev. Lett. 128, 050402 (2022).
  23. D. Qian and J. Wang, Quantum nonlocal nonstabilizerness, Phys. Rev. A 111, 052443 (2025).
  24. S. F. E. Oliviero, L. Leone, and A. Hamma, Magic-state resource theory for the ground state of the transverse-field Ising model, Phys. Rev. A 106, 042426 (2022).
  25. K. Goto, T. Nosaka, and M. Nozaki, Probing chaos by magic monotones, Phys. Rev. D 106, 126009 (2022).
  26. L. Susskind, Entanglement is not enough, Fortschr. Phys. 64, 49 (2016).
  27. L. Susskind, Computational complexity and black hole horizons, Fortschr. Phys. 64, 24 (2016).
  28. D. Stanford and L. Susskind, Complexity and shock wave geometries, Phys. Rev. D 90, 126007 (2014).
  29. D. A. Roberts, D. Stanford, and L. Susskind, Localized shocks, J. High Energy Phys. 2015, 51 (2015).
  30. M. Howard and E. Campbell, Application of a resource theory for magic states to fault-tolerant quantum computing, Phys. Rev. Lett. 118, 090501 (2017).
  31. S. Bravyi, D. Browne, P. Calpin, E. Campbell, D. Gosset, and M. Howard, Simulation of quantum circuits by low-rank stabilizer decompositions, Quantum 3, 181 (2019).
  32. K. Warmuz, E. Dokudowiec, C. Radhakrishnan, and T. Byrnes, A magic monotone for faithful detection of non-stabilizerness in mixed states, ArXiv:2409.18570.
  33. L. Leone and L. Bittel, Stabilizer entropies are monotones for magic-state resource theory, Phys. Rev. A 110, L040403 (2024).
  34. X. Turkeshi, M. Schirò, and P. Sierant, Measuring nonstabilizerness via multifractal flatness, Phys. Rev. A 108, 042408 (2023).
  35. E. Tirrito, P. S. Tarabunga, G. Lami, T. Chanda, L. Leone, S. F. E. Oliviero, M. Dalmonte, M. Collura, and A. Hamma, Quantifying nonstabilizerness through entanglement spectrum flatness, Phys. Rev. A 109, L040401 (2024).
  36. P. S. Tarabunga, E. Tirrito, M. C. Bañuls, and M. Dalmonte, Nonstabilizerness via matrix product states in the Pauli basis, Phys. Rev. Lett. 133, 010601 (2024).
  37. Z. Liu and B. K. Clark, Non-equilibrium quantum monte carlo algorithm for stabilizer Rényi entropy in spin systems, ArXiv:2405.19577.
  38. J. D’Emidio, Entanglement entropy from nonequilibrium work, Phys. Rev. Lett. 124, 110602 (2020).
  39. Y.-M. Ding, J.-S. Sun, N. Ma, G. Pan, C. Cheng, and Z. Yan, Reweight-annealing method for evaluating the partition function via quantum Monte Carlo calculations, Phys. Rev. B 110, 165152 (2024).
  40. Y.-M. Ding, Y. Tang, Z. Wang, Z. Wang, B.-B. Mao, and Z. Yan, Tracking the variation of entanglement Rényi negativity: A quantum Monte Carlo study, Phys. Rev. B 111, L241108 (2025).
  41. Z. Wang, Z. Wang, Y.-M. Ding, B.-B. Mao, and Z. Yan, Bipartite reweight-annealing algorithm of quantum Monte Carlo to extract large-scale data of entanglement entropy and its derivative, Nat. Commun. 16, 5880 (2025).
  42. W. Jiang, G. Pan, Z. Wang, B.-B. Mao, H. Shen, and Z. Yan, High-efficiency quantum monte carlo algorithm for extracting entanglement entropy in interacting fermion systems, ArXiv:2409.20009.
  43. Z. Wang, Z. Liu, Z. Wang, and Z. Yan, Addressing general measurements in quantum Monte Carlo, ArXiv:2412.01384.
  44. Z. Wang, Z. Deng, Z. Wang, Y.-M. Ding, W. Guo, and Z. Yan, Probing phase transition and underlying symmetry breaking via entanglement entropy scanning, ArXiv:2409.09942.
  45. N. Ma, J.-S. Sun, G. Pan, C. Cheng, and Z. Yan, Defining a universal sign to strictly probe a phase transition, Phys. Rev. B 110, 125141 (2024).
  46. R. M. Neal, Probabilistic inference using Markov chain Monte Carlo methods, (1993).
  47. L. Pollet, C. Kollath, K. V. Houcke, and M. Troyer, Temperature changes when adiabatically ramping up an optical lattice, New J. Phys. 10, 065001 (2008).
  48. K.-H. Wu, T.-C. Lu, C.-M. Chung, Y.-J. Kao, and T. Grover, Entanglement Renyi negativity across a finite temperature transition: A Monte Carlo study, Phys. Rev. Lett. 125, 140603 (2020).
  49. D. Frenkel and B. Smit, in Understanding Molecular Simulation (Second Edition), edited by D. Frenkel and B. Smit (Academic Press, San Diego, California, 2002), 2nd ed., p. 167.
  50. A. Gelman and X.-L. Meng, Simulating normalizing constants: From importance sampling to bridge sampling to path sampling, Stat. Sci. 13, 163 (1998).
  51. C. H. Bennett, Efficient estimation of free energy differences from Monte Carlo data, J. Comput. Phys. 22, 245 (1976).
  52. A. M. Hahn and H. Then, Characteristic of Bennett’s acceptance ratio method, Phys. Rev. E 80, 031111 (2009).
  53. S. V. Isakov, M. B. Hastings, and R. G. Melko, Topological entanglement entropy of a Bose-Hubbard spin liquid, Nat. Phys. 7, 772 (2011).
  54. R. G. Melko, A. B. Kallin, and M. B. Hastings, Finite-size scaling of mutual information in Monte Carlo simulations: Application to the spin-12XXZ model, Phys. Rev. B 82, 100409 (2010).
  55. S. Humeniuk and T. Roscilde, Quantum Monte Carlo calculation of entanglement Rényi entropies for generic quantum systems, Phys. Rev. B 86, 235116 (2012).
  56. J. Zhao, B.-B. Chen, Y.-C. Wang, Z. Yan, M. Cheng, and Z. Y. Meng, Measuring Rényi entanglement entropy with high efficiency and precision in quantum Monte Carlo simulations, npj Quantum Mater. 7, 69 (2022).
  57. J. Zhao, Y.-C. Wang, Z. Yan, M. Cheng, and Z. Y. Meng, Scaling of entanglement entropy at deconfined quantum criticality, Phys. Rev. Lett. 128, 010601 (2022).
  58. R. Yu, H. Saleur, and S. Haas, Entanglement entropy in the two-dimensional random transverse field Ising model, Phys. Rev. B 77, 140402 (2008).
  59. J. D’Emidio, M. S. Block, and R. K. Kaul, Rényi entanglement entropy of critical SU(n) spin chains, Phys. Rev. B 92, 054411 (2015).
  60. M. Troyer and U.-J. Wiese, Computational complexity and fundamental limitations to fermionic quantum Monte Carlo simulations, Phys. Rev. Lett. 94, 170201 (2005).
  61. G. Pan and Z. Y. Meng, in Encyclopedia of Condensed Matter Physics (Second Edition), edited by T. Chakraborty (Academic Press, Oxford, 2024), 2nd ed., p. 879.
  62. J. R. Fliss, Knots, links, and long-range magic, J. High Energy Phys. 2021, 90 (2021).
  63. N. Bao, C. Cao, and V. P. Su, Magic state distillation from entangled states, Phys. Rev. A 105, 022602 (2022).
  64. M. Frau, P. S. Tarabunga, M. Collura, E. Tirrito, and M. Dalmonte, Stabilizer disentangling of conformal field theories, ArXiv:2411.11720.
  65. X. Wang, M. M. Wilde, and Y. Su, Quantifying the magic of quantum channels, New J. Phys. 21, 103002 (2019).
  66. Y.-M. Zhan, Y.-G. Chen, B. Chen, Z. Wang, Y. Yu, and X. Luo, Universal topological quantum computation with strongly correlated Majorana edge modes, New J. Phys. 24, 043009 (2022).
  67. H. Zhu, R. Kueng, M. Grassl, and D. Gross, The Clifford group fails gracefully to be a unitary 4-design, ArXiv:1609.08172.
  68. A. W. Sandvik, Stochastic series expansion method with operator-loop update, Phys. Rev. B 59, R14157 (1999).
  69. A. W. Sandvik, Stochastic series expansion method for quantum Ising models with arbitrary interactions, Phys. Rev. E 68, 056701 (2003).
  70. R. G. Melko, in Strongly Correlated Systems: Numerical Methods, edited by A. Avella and F. Mancini (Springer-Verlag, Berlin, 2013), p. 185.
  71. Z. Yan, Y. Wu, C. Liu, O. F. Syljuåsen, J. Lou, and Y. Chen, Sweeping cluster algorithm for quantum spin systems with strong geometric restrictions, Phys. Rev. B 99, 165135 (2019).
  72. Z. Yan, Global scheme of sweeping cluster algorithm to sample among topological sectors, Phys. Rev. B 105, 184432 (2022).
  73. E. Y. Loh, J. E. Gubernatis, R. T. Scalettar, S. R. White, D. J. Scalapino, and R. L. Sugar, Sign problem in the numerical simulation of many-electron systems, Phys. Rev. B 41, 9301 (1990).
  74. M. Takasu, S. Miyashita, and M. Suzuki, Monte Carlo simulation of quantum Heisenberg magnets on the triangular lattice, Prog. Theor. Phys. 75, 1254 (1986).
  75. N. Hatano and M. Suzuki, Representation basis in quantum Monte Carlo calculations and the negative-sign problem, Phys. Lett. A 163, 246 (1992).
  76. V. I. Iglovikov, E. Khatami, and R. T. Scalettar, Geometry dependence of the sign problem in quantum Monte Carlo simulations, Phys. Rev. B 92, 045110 (2015).
  77. Z. Zhou, W. T. Jin, W. Li, S. Nandi, B. Ouladdiaf, Z. Yan, X. Wei, X. Xu, W. H. Jiao, N. Qureshi, Y. Xiao, Y. Su, G. H. Cao, and T. Brückel, Universal critical behavior in the ferromagnetic superconductor Eu(Fe0.75Ru0.25)2As2, Phys. Rev. B 100, 060406 (2019).
  78. O. F. Syljuåsen and A. W. Sandvik, Quantum Monte Carlo with directed loops, Phys. Rev. E 66, 046701 (2002).
  79. A. W. Sandvik, Stochastic series expansion methods, ArXiv:1909.10591.
  80. A. W. Sandvik, Computational studies of quantum spin systems, AIP Conf. Proc. 1297, 135 (2010).
  81. N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, and E. Teller, Equation of state calculations by fast computing machines, J. Chem. Phys. 21, 1087 (1953).
  82. W. K. Hastings, Monte Carlo sampling methods using Markov chains and their applications, Biometrika 57, 97 (1970).
  83. S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, Optimization by simulated annealing, Science 220, 671 (1983).
  84. H. W. J. Blöte and Y. Deng, Cluster Monte Carlo simulation of the transverse Ising model, Phys. Rev. E 66, 066110 (2002).
  85. X. Turkeshi, A. Dymarsky, and P. Sierant, Pauli spectrum and magic of typical quantum many-body states, ArXiv:2312.11631.
  86. M. Collura, J. D. Nardis, V. Alba, and G. Lami, The quantum magic of fermionic gaussian states, ArXiv:2412.05367.
  87. D. A. Korbany, M. J. Gullans, and L. Piroli, Long-range nonstabilizerness and phases of matter, ArXiv:2502.19504.
  88. F. Wei and Z.-W. Liu, Long-range nonstabilizerness from quantum codes, orders, and correlations, ArXiv:2503.04566.
  89. P. Calabrese and J. Cardy, Entanglement entropy and conformal field theory, J. Phys. A: Math. Theor. 42, 504005 (2009).
  90. T. Nishioka, Entanglement entropy: Holography and renormalization group, Rev. Mod. Phys. 90, 035007 (2018).
  91. M. Hoshino, M. Oshikawa, and Y. Ashida, Stabilizer rényi entropy and conformal field theory, ArXiv:2503.13599.
  92. S. Hesselmann and S. Wessel, Thermal Ising transitions in the vicinity of two-dimensional quantum critical points, Phys. Rev. B 93, 155157 (2016).
  93. P. Calabrese and J. Cardy, Entanglement entropy and quantum field theory, J. Stat. Mech.: Theory Exp. 2004, P06002 (2004).
  94. J. A. M. López and P. Kos, Exact solution of long-range stabilizer Rényi entropy in the dual-unitary XXZ model, J. Phys. A: Math. Theor. 57, 475301 (2024).
  95. Z. Yan and Z. Y. Meng, Unlocking the general relationship between energy and entanglement spectra via the wormhole effect, Nat. Commun. 14, 2360 (2023).
  96. C. Li, R.-Z. Huang, Y.-M. Ding, Z. Y. Meng, Y.-C. Wang, and Z. Yan, Relevant long-range interaction of the entanglement Hamiltonian emerges from a short-range gapped system, Phys. Rev. B 109, 195169 (2024).
  97. B.-B. Mao, Y.-M. Ding, and Z. Yan, Sampling reduced density matrix to extract fine levels of entanglement spectrum, ArXiv:2310.16709.
  98. T.-T. Wang, M. Song, L. Lyu, W. Witczak-Krempa, and Z. Y. Meng, Entanglement microscopy and tomography in many-body systems, Nat. Commun. 16, 96 (2025).
  99. Y.-M. Ding, Data for “evaluating many-body stabilizer rényi entropy by sampling reduced pauli strings: Singularities, volume law, and nonlocal magic”, 2025,
  100. H. G. Evertz, The loop algorithm, Adv. Phys. 52, 1 (2003).
  101. A. M. Ferrenberg and R. H. Swendsen, New Monte Carlo technique for studying phase transitions, Phys. Rev. Lett. 61, 2635 (1988).

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