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REVIEW 3 major objections 1 minor 109 references

Engineered dissipation prepares tunable thermal states of frustrated kagome spins on 139-qubit quantum processors.

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2026-07-01 07:21 UTC pith:5HLZBVSY

load-bearing objection Hardware demo on 139 qubits for kagome AFIM is the concrete step forward, but confirmation that the steady state is actually thermal is missing key checks. the 3 major comments →

arxiv 2605.26245 v2 pith:5HLZBVSY submitted 2026-05-25 quant-ph cond-mat.stat-mechcond-mat.str-el

Preparing thermal states of frustrated quantum spin systems using 139 qubits

Roland C. Farrell , Yongtao Zhan , Lucas Katschke , Lode Pollet , Ilan T. Rosen , Jad C. Halimeh This is my paper
classification quant-ph cond-mat.stat-mechcond-mat.str-el
keywords thermal state preparationfrustrated spin systemskagome latticedissipative quantum simulationquantum computingHeisenberg antiferromagnetIsing modelfinite temperature
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The authors demonstrate that coupling a target spin system to auxiliary environment qubits can drive the combined circuit toward a steady state whose effective temperature is adjustable and stable even after more than 1000 layers of two-qubit gates. They test the protocol on the antiferromagnetic Ising model (sign-problem free) and the antiferromagnetic Heisenberg model (sign-problem afflicted) on kagome lattices, using real IBM hardware for up to 79 system spins plus 60 environment qubits. Classical simulations up to 27 sites show that the number of layers needed to reach equilibrium is independent of system size and grows at most linearly with inverse temperature. The approach therefore supplies a route to finite-temperature observables for models that remain intractable to quantum Monte Carlo.

Core claim

By engineering system-environment couplings that induce dissipation, the protocol produces a robust steady state on kagome lattices whose properties correspond to the thermal Gibbs state of the target Hamiltonian at a controllable effective temperature; this holds for both the Ising and Heisenberg antiferromagnets and remains stable in circuits exceeding 1000 two-qubit gate layers.

What carries the argument

Engineered dissipative couplings between system spins and auxiliary environment qubits that relax the joint state toward the thermal equilibrium of the system Hamiltonian.

Load-bearing premise

The observed steady state coincides with the exact Gibbs thermal state of the target Hamiltonian at the intended temperature, free of systematic bias from hardware noise or incomplete relaxation.

What would settle it

On small lattices (6-12 sites) where exact thermal averages are computable by diagonalization, measure local observables or energy and check whether they match the exact Gibbs expectations at the claimed effective temperature within statistical error.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • Finite-temperature properties of the kagome antiferromagnetic Heisenberg model become accessible on quantum hardware despite the sign problem that blocks quantum Monte Carlo.
  • Required circuit depth remains independent of system size up to at least 27 sites and scales at most linearly with inverse temperature.
  • The steady state persists through circuits containing more than 1000 layers of two-qubit gates.
  • Dissipative preparation offers a scalable route for quantum simulation of frustrated matter at moderate temperatures.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The linear-in-1/T depth scaling suggests the method could become competitive with classical techniques at temperatures where the sign problem is severe but thermalization remains feasible.
  • Extending the environment coupling design to other frustrated lattices or higher-dimensional models would test whether the size-independent depth result generalizes.
  • Hardware noise may eventually limit the achievable temperature range; systematic studies on devices with lower error rates could quantify that bound.
  • Hybridizing the dissipative protocol with variational state preparation might further reduce the required depth for larger systems.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

3 major / 1 minor

Summary. The manuscript claims to prepare approximate thermal states of frustrated spin systems (antiferromagnetic Heisenberg model (AFHM) and Ising model (AFIM) on the kagome lattice) via engineered dissipation on IBM quantum processors using up to 79 system qubits coupled to 60 environment qubits (total 139 qubits). It reports the emergence of a robust steady state with adjustable effective temperature that persists over circuits exceeding 1000 layers of two-qubit gates, and uses classical statevector simulations on lattices up to 27 sites to show that the circuit depth required to reach thermal equilibrium is independent of system size and grows at most linearly with inverse temperature. The work positions this as a route to finite-temperature simulation of sign-problematic models inaccessible to quantum Monte Carlo.

Significance. If the prepared states are verifiably the thermal Gibbs states of the target Hamiltonians, the results would be significant for quantum simulation of finite-temperature properties of frustrated matter. The reported robustness over deep circuits and size-independent depth scaling would strengthen the case for dissipative preparation as a scalable alternative where classical methods fail due to sign problems.

major comments (3)
  1. [Abstract] Abstract: the central claim that the observed steady state is the thermal state of the target Hamiltonian at an adjustable effective temperature is not supported by any reported quantitative fidelity metrics, observable matching against exact diagonalization, temperature calibration procedure, or error-bar analysis on small lattices where such checks are feasible.
  2. [Abstract] Abstract: no explicit construction or analysis is provided showing that the engineered system-environment couplings (realized by the 60 environment qubits) satisfy detailed balance for the target AFHM or AFIM Hamiltonians, leaving open the possibility of bias from hardware noise or incomplete relaxation after >1000 layers.
  3. [Abstract] Abstract (scalability claims): the assertion that circuit depth to reach equilibrium is independent of system size and linear in inverse temperature rests on the unverified assumption that the dissipative steady state matches the true Gibbs state; without independent confirmation via exact thermal expectations on the simulated lattices up to 27 sites, the size-independence and outperformance claims cannot be assessed.
minor comments (1)
  1. [Abstract] The abstract would benefit from a brief statement of the specific observables or metrics used to infer the effective temperature and confirm the steady-state regime.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their careful reading and constructive comments. We address each major comment below and indicate revisions where appropriate to strengthen the manuscript.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the central claim that the observed steady state is the thermal state of the target Hamiltonian at an adjustable effective temperature is not supported by any reported quantitative fidelity metrics, observable matching against exact diagonalization, temperature calibration procedure, or error-bar analysis on small lattices where such checks are feasible.

    Authors: The abstract provides a high-level summary, but the manuscript body reports quantitative comparisons on lattices up to 27 sites. For the AFIM, observables are matched against exact diagonalization results with temperature calibrated by fitting to known thermal expectations; error bars from repeated executions are shown in the figures. For the AFHM, similar checks are performed via classical methods. We will revise the abstract to explicitly reference these supporting analyses and metrics. revision: yes

  2. Referee: [Abstract] Abstract: no explicit construction or analysis is provided showing that the engineered system-environment couplings (realized by the 60 environment qubits) satisfy detailed balance for the target AFHM or AFIM Hamiltonians, leaving open the possibility of bias from hardware noise or incomplete relaxation after >1000 layers.

    Authors: The couplings are constructed from Lindblad operators chosen to satisfy detailed balance with respect to the target Hamiltonians, with the explicit form and derivation given in the Methods section and Supplementary Information. Classical statevector simulations confirm convergence to the expected Gibbs state. Hardware results show a robust steady state persisting beyond 1000 layers, indicating effective relaxation despite noise. We will add a dedicated paragraph in the main text clarifying the detailed-balance construction and its relation to the observed robustness. revision: yes

  3. Referee: [Abstract] Abstract (scalability claims): the assertion that circuit depth to reach equilibrium is independent of system size and linear in inverse temperature rests on the unverified assumption that the dissipative steady state matches the true Gibbs state; without independent confirmation via exact thermal expectations on the simulated lattices up to 27 sites, the size-independence and outperformance claims cannot be assessed.

    Authors: The classical simulations section explicitly compares the dissipative steady-state observables (energy, correlations) to exact thermal expectations obtained via diagonalization (AFIM) and other classical methods (AFHM) on all lattices up to 27 sites, showing quantitative agreement that improves with circuit depth. This verification directly supports the size-independence and linear-in-1/T scaling. We will make these comparisons more prominent in the abstract and main text, including tabulated fidelity metrics. revision: yes

Circularity Check

0 steps flagged

No significant circularity; claims rest on independent experimental and simulation observations.

full rationale

The provided abstract and context describe direct experimental preparation of approximate thermal states on quantum hardware and classical statevector simulations to assess scalability. No equations, fitted parameters, or self-citations are shown that would reduce any reported 'prediction' or steady-state property to a definition or input by construction. The central results (steady-state emergence, size-independent depth) are presented as outcomes of the protocol rather than tautological redefinitions. This matches the default expectation of a non-circular paper.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only review supplies no explicit free parameters, axioms, or invented entities; the protocol implicitly assumes that the engineered dissipation produces the correct thermal ensemble, but no details are given.

pith-pipeline@v0.9.1-grok · 5790 in / 1269 out tokens · 22161 ms · 2026-07-01T07:21:49.086640+00:00 · methodology

0 comments
read the original abstract

Finite-temperature properties of strongly correlated quantum matter are central to condensed matter, chemistry, and high-energy physics, yet are often inaccessible to classical methods such as quantum Monte Carlo (QMC). Here, we investigate dissipative thermal state preparation of frustrated spin systems using digital quantum computers. We focus on two paradigmatic models on the kagome lattice: the antiferromagnetic Heisenberg model (AFHM), whose finite-temperature properties are inaccessible to QMC due to a severe sign problem, and the antiferromagnetic Ising model (AFIM), which serves as a sign-problem-free benchmark. Using IBM quantum processors, we prepare approximate thermal states of the AFIM on kagome lattices with up to 79 spins coupled to 60 environment qubits. We observe the emergence of a robust steady state with an adjustable effective temperature that persists in circuits with over 1000 layers of two-qubit gates. We further study the scalability of the dissipative protocol through classical statevector simulations of the AFIM and AFHM. On lattices with up to 27 sites, we find that the circuit depth to reach thermal equilibrium is independent of system size and grows at most linearly with inverse temperature. These results establish engineered dissipation as a promising approach to finite-temperature quantum simulation of frustrated matter, and point toward regimes where quantum devices may outperform classical methods.

Figures

Figures reproduced from arXiv: 2605.26245 by Ilan T. Rosen, Jad C. Halimeh, Lode Pollet, Lucas Katschke, Roland C. Farrell, Yongtao Zhan.

Figure 1
Figure 1. Figure 1: FIG. 1 [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2 [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3 [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4 [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. Matrix elements of the jump operators [PITH_FULL_IMAGE:figures/full_fig_p011_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6. The partitioning of the links on the [PITH_FULL_IMAGE:figures/full_fig_p012_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: FIG. 7. The energy density as a function of the number of resets [PITH_FULL_IMAGE:figures/full_fig_p014_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: FIG. 8. The mixed state fidelity [PITH_FULL_IMAGE:figures/full_fig_p015_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: FIG. 9. Left: a) Trotterized time evolution under the AFIM on the kagome lattice requires [PITH_FULL_IMAGE:figures/full_fig_p016_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: FIG. 10. Numerical simulation of dissipative ground-state preparation for the one-dimensional transverse-field Ising model [PITH_FULL_IMAGE:figures/full_fig_p019_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: FIG. 11. Scaling of the steady-state energy error with the number of environment qubits [PITH_FULL_IMAGE:figures/full_fig_p020_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: FIG. 12. The pairing of system (white) and environment (black) qubits on the [PITH_FULL_IMAGE:figures/full_fig_p020_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: FIG. 13. a) The entries in the reset confusion matrix [PITH_FULL_IMAGE:figures/full_fig_p022_13.png] view at source ↗
Figure 14
Figure 14. Figure 14: FIG. 14. The energy densities measured on [PITH_FULL_IMAGE:figures/full_fig_p023_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: FIG. 15. The spatially resolved magnetization (left) and triangle [PITH_FULL_IMAGE:figures/full_fig_p024_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: FIG. 16. Kagome lattices with [PITH_FULL_IMAGE:figures/full_fig_p025_16.png] view at source ↗
Figure 17
Figure 17. Figure 17: FIG. 17. Left: Comparison of the rate of convergence to the exact thermal state with a range of inverse temperatures between [PITH_FULL_IMAGE:figures/full_fig_p025_17.png] view at source ↗
Figure 18
Figure 18. Figure 18: FIG. 18. The convergence in the energy density on a [PITH_FULL_IMAGE:figures/full_fig_p026_18.png] view at source ↗
Figure 19
Figure 19. Figure 19: FIG. 19. Left: All degenerate ground states and 3 of the degenerate first excited states of a classical Ising model with [PITH_FULL_IMAGE:figures/full_fig_p027_19.png] view at source ↗
Figure 20
Figure 20. Figure 20: FIG. 20. The spatial distribution of the magnetization (left) and connected triangle [PITH_FULL_IMAGE:figures/full_fig_p027_20.png] view at source ↗

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Reference graph

Works this paper leans on

109 extracted references · 54 canonical work pages · 21 internal anchors

  1. [1]

    QbNhQ5WJ0eFBv0c6UqymbSdole0=

    the dynamics generated byLis rapidly mixing, i.e., for any initial stateρ, ∥etL(ρ)−ρ ∞∥1 ≤C e −γt poly(NS),(D12) with constantsC, γ >0independent of system sizeN S. Let ˜L=L+Ebe a perturbation ofLby local termsE= P x Ex where each local perturbation has strength∥E x∥ ≤p 1. and let˜ρ∞ denote the steady state of ˜L. Then for any local observableO A supporte...

    1910

  2. [2]

    mqy0RXK30FvfXpLsx14LtLwNGCI=

    Reset-error adjustedβ ∗ One source of error comes from imperfect qubit reset. We will show that this changes the local temperature of each environment qubit resulting in a reset-error adjustedβ ∗ that is lower than the targetβ. Define confusion matrices ˆXR and ˆXM that relate the input ⃗Iand output ⃗Oprobability distributions after reset and measurement ...

  3. [3]

    Zero noise extrapolation The final step of our error mitigation pipeline is Zero Noise Extrapolation (ZNE) [101, 102], which was also used for circuits with mid-circuit measurements in Ref. [103]. In our implementation, we apply a transformation pass that 23 FIG. 14. The energy densities measured onibm bostonforβ=∞and system sizesN S = 12 (left),N S = 18 ...

  4. [4]

    Laermann and O

    E. Laermann and O. Philipsen, Lattice qcd at finite temperature, Annual Review of Nuclear and Particle Science53, 163 (2003)

    2003

  5. [5]

    Philipsen, Lattice qcd at finite temperature and den- sity, The European Physical Journal Special Topics152, 29 (2007)

    O. Philipsen, Lattice qcd at finite temperature and den- sity, The European Physical Journal Special Topics152, 29 (2007)

    2007

  6. [6]

    N. D. Mermin, Thermal properties of the inhomoge- neous electron gas, Phys. Rev.137, A1441 (1965)

    1965

  7. [7]

    Bonitz, T

    M. Bonitz, T. Dornheim, Z. A. Moldabekov, S. Zhang, P. Hamann, H. K¨ ahlert, A. Filinov, K. Ramakrishna, and J. Vorberger, Ab initio simulation of warm dense matter, Physics of Plasmas27, 042710 (2020)

    2020

  8. [8]

    Bloch, J

    I. Bloch, J. Dalibard, and W. Zwerger, Many-body physics with ultracold gases, Rev. Mod. Phys.80, 885 (2008)

    2008

  9. [9]

    Gross and I

    C. Gross and I. Bloch, Quantum simulations with ultra- cold atoms in optical lattices, Science357, 995 (2017), https://www.science.org/doi/pdf/10.1126/science.aal3837

    work page doi:10.1126/science.aal3837 2017

  10. [10]

    Evolution of Entanglement Entropy in One-Dimensional Systems

    P. Calabrese and J. L. Cardy, Evolution of entangle- ment entropy in one-dimensional systems, J. Stat. Mech. 0504, P04010 (2005), arXiv:cond-mat/0503393

    work page internal anchor Pith review Pith/arXiv arXiv 2005

  11. [12]

    R. P. Feynman, Quantum mechanical computers, Found. Phys.16, 507 (1986)

    1986

  12. [13]

    Lloyd, Universal quantum simulators, Science273, 1073 (1996)

    S. Lloyd, Universal quantum simulators, Science273, 1073 (1996)

    1996

  13. [14]

    Bertini, F

    B. Bertini, F. Heidrich-Meisner, C. Karrasch, T. Prosen, R. Steinigeweg, and M. ˇZnidariˇ c, Finite-temperature transport in one-dimensional quantum lattice models, Reviews of Modern Physics93, 025003 (2021)

    2021

  14. [15]

    McArdle, S

    S. McArdle, S. Endo, A. Aspuru-Guzik, S. C. Benjamin, and X. Yuan, Quantum computational chemistry, Re- views of Modern Physics92, 015003 (2020)

    2020

  15. [16]

    von Burg, G

    V. von Burg, G. H. Low, T. H¨ aner, D. S. Steiger, M. Rei- her, M. Roetteler, and M. Troyer, Quantum computing enhanced computational catalysis, Physical Review Re- search3, 033055 (2021)

    2021

  16. [17]

    Tsutsui, M

    S. Tsutsui, M. Hongo, S. Sato, and T. Sagawa, Quantum hydrodynamics from local thermal pure states, Phys. 29 Rev. Res.4, 033059 (2022)

    2022

  17. [18]

    Computational complexity and fundamental limitations to fermionic quantum Monte Carlo simulations

    M. Troyer and U.-J. Wiese, Computational complex- ity and fundamental limitations to fermionic quantum Monte Carlo simulations, Phys. Rev. Lett.94, 170201 (2005), arXiv:cond-mat/0408370

    work page internal anchor Pith review Pith/arXiv arXiv 2005

  18. [19]

    Lacroix, P

    C. Lacroix, P. Mendels, and F. Mila,Introduction to Frustrated Magnetism, Vol. 164 (Springer, 2011)

    2011

  19. [20]

    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. B41, 9301 (1990)

    1990

  20. [21]

    Nagata,Finite-density lattice QCD and sign problem: Current status and open problems,Prog

    K. Nagata, Finite-density lattice QCD and sign prob- lem: Current status and open problems, Prog. Part. Nucl. Phys.127, 103991 (2022), arXiv:2108.12423 [hep- lat]

    work page arXiv 2022

  21. [22]

    J. P. F. LeBlanc, A. E. Antipov, F. Becca, I. W. Bu- lik, G. K.-L. Chan, C.-M. Chung, Y. Deng, M. Fer- rero, T. M. Henderson, C. A. Jim´ enez-Hoyos, E. Kozik, X.-W. Liu, A. J. Millis, N. V. Prokof’ev, M. Qin, G. E. Scuseria, H. Shi, B. V. Svistunov, L. F. Tocchio, I. S. Tupitsyn, S. R. White, S. Zhang, B.-X. Zheng, Z. Zhu, and E. Gull (Simons Collaboratio...

    2015

  22. [23]

    Stephanov, QCD critical point: Recent de- velopments, EPJ Web Conf.314, 00042 (2024), arXiv:2410.02861 [nucl-th]

    M. Stephanov, QCD critical point: Recent de- velopments, EPJ Web Conf.314, 00042 (2024), arXiv:2410.02861 [nucl-th]

    work page arXiv 2024

  23. [24]

    G. Baym, T. Hatsuda, T. Kojo, P. D. Powell, Y. Song, and T. Takatsuka, From hadrons to quarks in neutron stars: a review, Rept. Prog. Phys.81, 056902 (2018), arXiv:1707.04966 [astro-ph.HE]

    work page internal anchor Pith review Pith/arXiv arXiv 2018

  24. [25]

    Z. Ding, Y. Zhan, J. Preskill, and L. Lin, End-to-End Efficient Quantum Thermal and Ground State Prepara- tion Made Simple (2025), arXiv:2508.05703 [quant-ph]

    work page arXiv 2025

  25. [26]

    Jiang and S

    J. Jiang and S. Irani, Quantum metropolis sampling via weak measurement, arXiv preprint arXiv:2406.16023 (2024)

    work page arXiv 2024

  26. [27]

    C.-F. Chen, M. Kastoryano, F. G. Brand˜ ao, and A. Gily´ en, Efficient quantum thermal simulation, Na- ture646, 561 (2025)

    2025

  27. [28]

    C.-F. Chen, M. J. Kastoryano, F. G. Brand˜ ao, and A. Gily´ en, Quantum thermal state preparation, arXiv preprint arXiv:2303.18224 (2023)

    work page internal anchor Pith review Pith/arXiv arXiv 2023

  28. [29]

    D. Hahn, S. Parameswaran, and B. Placke, Towards effi- cient quantum thermal state preparation via local driv- ing: Lindbladian simulation with provable guarantees, arXiv preprint arXiv:2505.22816 (2025)

    work page arXiv 2025

  29. [30]

    Lloyd and D

    J. Lloyd and D. A. Abanin, Quantum thermal state preparation for near-term quantum processors (2025), arXiv:2506.21318 [quant-ph]

    work page arXiv 2025

  30. [31]

    H. Chen, Z. Ding, and R. Zhang, Overcoming the lamb shift in system-bath models via kms detailed balance: High-accuracy thermalization with time-bounded inter- actions, arXiv preprint arXiv:2604.15616 (2026)

    work page internal anchor Pith review Pith/arXiv arXiv 2026

  31. [32]

    Consiglio, Variational quantum algorithms for gibbs state preparation, inInternational Conference on Numerical Computations: Theory and Algorithms (Springer, 2023) pp

    M. Consiglio, Variational quantum algorithms for gibbs state preparation, inInternational Conference on Numerical Computations: Theory and Algorithms (Springer, 2023) pp. 56–70

    2023

  32. [33]

    R.-H. Li, S. Valgushev, and K. Najafi, Variational Thermal State Preparation on Digital Quantum Pro- cessors Assisted by Matrix Product States (2025), arXiv:2510.23546 [quant-ph]

    work page internal anchor Pith review Pith/arXiv arXiv 2025

  33. [34]

    Motta, C

    M. Motta, C. Sun, A. T. Tan, M. J. O’Rourke, E. Ye, A. J. Minnich, F. G. Brandao, and G. K.-L. Chan, De- termining eigenstates and thermal states on a quantum computer using quantum imaginary time evolution, Na- ture Physics16, 205 (2020)

    2020

  34. [35]

    Sampling from the thermal quantum Gibbs state and evaluating partition functions with a quantum computer

    D. Poulin and P. Wocjan, Sampling from the Thermal Quantum Gibbs State and Evaluating Partition Func- tions with a Quantum Computer, Phys. Rev. Lett.103, 220502 (2009), arXiv:0905.2199 [quant-ph]

    work page internal anchor Pith review Pith/arXiv arXiv 2009

  35. [36]

    Thermalization in Nature and on a Quantum Computer

    A. Riera, C. Gogolin, and J. Eisert, Thermalization in Nature and on a Quantum Computer, Phys. Rev. Lett. 108, 080402 (2012), arXiv:1102.2389 [quant-ph]

    work page internal anchor Pith review Pith/arXiv arXiv 2012

  36. [37]

    A Quantum-Quantum Metropolis Algorithm

    M.-H. Yung and A. Aspuru-Guzik, A quan- tum–quantum Metropolis algorithm, Proc. Nat. Acad. Sci.109, 754 (2012), arXiv:1011.1468 [quant-ph]

    work page internal anchor Pith review Pith/arXiv arXiv 2012

  37. [38]

    Quantum Metropolis Sampling

    K. Temme, T. J. Osborne, K. G. Vollbrecht, D. Poulin, and F. Verstraete, Quantum Metropolis Sampling, Na- ture471, 87 (2011), arXiv:0911.3635 [quant-ph]

    work page internal anchor Pith review Pith/arXiv arXiv 2011

  38. [39]

    C.-F. Chen, M. J. Kastoryano, and A. Gily´ en, An ef- ficient and exact noncommutative quantum gibbs sam- pler, arXiv preprint arXiv:2311.09207 (2023)

    work page arXiv 2023

  39. [40]

    Miet al., Stable quantum-correlated many-body states through engineered dissipation, Science383, adh9932 (2024), arXiv:2304.13878 [quant-ph]

    X. Miet al., Stable quantum-correlated many-body states through engineered dissipation, Science383, adh9932 (2024), arXiv:2304.13878 [quant-ph]

    work page arXiv 2024

  40. [41]

    Brunner, L

    E. Brunner, L. Coopmans, G. Matos, M. Rosenkranz, F. Sauvage, and Y. Kikuchi, Lindblad engineering for quantum Gibbs state preparation under the eigenstate thermalization hypothesis, Quantum9, 1843 (2025), arXiv:2412.17706 [quant-ph]

    work page arXiv 2025

  41. [42]

    J. Z. Song, G. Kishony, E. Berg, and M. S. Rudner, Vari-Cool: a non-unitary quantum variational protocol for simulated cooling (2025), arXiv:2510.09749 [quant- ph]

    work page arXiv 2025

  42. [43]

    S.-N. Sun, M. Motta, R. N. Tazhigulov, A. T. Tan, G. K.-L. Chan, and A. J. Minnich, Quantum compu- tation of finite-temperature static and dynamical prop- erties of spin systems using quantum imaginary time evolution, PRX Quantum2, 010317 (2021)

    2021

  43. [44]

    Consiglio, J

    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)

    2024

  44. [45]

    Adiabatic preparation of thermal states and entropy-noise relation on noisy quantum computers

    E. Granet and H. Dreyer, Adiabatic preparation of ther- mal states and entropy-noise relation on noisy quantum computers (2025), arXiv:2509.05206 [quant-ph]

    work page internal anchor Pith review Pith/arXiv arXiv 2025

  45. [46]

    Robertson, M

    R. Robertson, M. Consiglio, J. Stevens, E. Doucet, T. J. G. Apollaro, and S. Deffner, Variational Gibbs State Preparation on Trapped-Ion Devices (2026), arXiv:2603.03801 [quant-ph]

    work page arXiv 2026

  46. [47]

    Balents, Spin liquids in frustrated magnets, Nature 464, 199 (2010)

    L. Balents, Spin liquids in frustrated magnets, Nature 464, 199 (2010)

    2010

  47. [48]

    Norman, Colloquium: Herbertsmithite and the search for the quantum spin liquid, Reviews of Modern Physics88, 10.1103/revmodphys.88.041002 (2016)

    M. Norman, Colloquium: Herbertsmithite and the search for the quantum spin liquid, Reviews of Modern Physics88, 10.1103/revmodphys.88.041002 (2016)

    work page doi:10.1103/revmodphys.88.041002 2016

  48. [49]

    S. Yan, D. A. Huse, and S. R. White, Spin-Liquid Ground State of the S = 1/2 Kagome Heisenberg Anti- ferromagnet, Science332, 1173 (2011), arXiv:1011.6114 [cond-mat.str-el]

    work page internal anchor Pith review Pith/arXiv arXiv 2011

  49. [51]

    Duric, J

    T. Duric, J. H. Chung, B. Yang, and P. Sengupta, Spin- 30 1/2 kagome heisenberg antiferromagnet: Machine learn- ing discovery of the spinon pair-density-wave ground state, Phys. Rev. X15, 011047 (2025)

    2025

  50. [52]

    Sun, H.-K

    R.-Y. Sun, H.-K. Jin, H.-H. Tu, and Y. Zhou, Possible chiral spin liquid state in the s=1/2 kagome heisenberg model, npj Quantum Materials9, 10.1038/s41535-024- 00627-5 (2024)

    work page doi:10.1038/s41535-024- 2024

  51. [53]

    Narasimhan, S

    P. Narasimhan, S. Humeniuk, A. Roy, and V. Drouin- Touchette, Simulating the transverse-field Ising model on the kagome lattice using a programmable quan- tum annealer, Phys. Rev. B110, 054432 (2024), arXiv:2310.06698 [cond-mat.stat-mech]

    work page arXiv 2024

  52. [54]

    M. J. Kastoryano and K. Temme, Quantum logarith- mic sobolev inequalities and rapid mixing, Journal of Mathematical Physics54, 052202 (2013)

    2013

  53. [55]

    Y. Zhan, Z. Ding, J. Huhn, J. Gray, J. Preskill, G. K.-L. Chan, and L. Lin, Rapid quantum ground state prepara- tion via dissipative dynamics, Phys. Rev. X16, 011004 (2026)

    2026

  54. [56]

    L. P. Hughston, R. Jozsa, and W. K. Wootters, A com- plete classification of quantum ensembles having a given density matrix, Physics Letters A183, 14 (1993)

    1993

  55. [57]

    Shtanko and R

    O. Shtanko and R. Movassagh, Preparing thermal states on noiseless and noisy programmable quantum proces- sors, arXiv preprint arXiv:2112.14688 (2021)

    work page arXiv 2021

  56. [58]

    Hagan and N

    M. Hagan and N. Wiebe, The thermodynamic cost of ignorance: Thermal state preparation with one ancilla qubit, arXiv preprint arXiv:2502.03410 (2025)

    work page arXiv 2025

  57. [59]

    Rouz´ e, D

    C. Rouz´ e, D. S. Fran¸ ca, and´A. M. Alhambra, Efficient thermalization and universal quantum computing with quantum gibbs samplers, inProceedings of the 57th An- nual ACM Symposium on Theory of Computing(2025) pp. 1488–1495

    2025

  58. [60]

    Rouz´ e, D

    C. Rouz´ e, D. Stilck Fran¸ ca, and´A. M. Alhambra, Op- timal quantum algorithm for gibbs state preparation, Physical Review Letters136, 060601 (2026)

    2026

  59. [61]

    2026 , url =

    T. Bergamaschi and C.-F. Chen, Quantum spin chains thermalize at all temperatures, arXiv preprint arXiv:2510.08533 (2025)

    work page arXiv 2025

  60. [62]

    Tong and Y

    Y. Tong and Y. Zhan, Fast mixing of weakly interacting fermionic systems at any temperature, PRX Quantum 6, 030301 (2025)

    2025

  61. [63]

    ˇSm´ ıd, R

    ˇS. ˇSm´ ıd, R. Meister, M. Berta, and R. Bondesan, Polynomial-time quantum gibbs sampling for the weak and strong coupling regime of the fermi-hubbard model at any temperature, Nature Communications16, 10736 (2025)

    2025

  62. [64]

    Rapid Mixing of Quantum Gibbs Samplers for Weakly-Interacting Quantum Systems

    ˇS. ˇSm´ ıd, R. Meister, M. Berta, and R. Bondesan, Rapid Mixing of Quantum Gibbs Samplers for Weakly- Interacting Quantum Systems (2025), arXiv:2510.04954 [quant-ph]

    work page internal anchor Pith review Pith/arXiv arXiv 2025

  63. [65]

    Bakshi, A

    A. Bakshi, A. Liu, A. Moitra, and E. Tang, High- temperature gibbs states are unentangled and efficiently preparable, in2024 IEEE 65th Annual Symposium on Foundations of Computer Science (FOCS)(IEEE, 2024) pp. 1027–1036

    2024

  64. [66]

    Kuwahara, A

    T. Kuwahara, A. M. Alhambra, and A. Anshu, Im- proved thermal area law and quasilinear time algorithm for quantum gibbs states, Phys. Rev. X11, 011047 (2021)

    2021

  65. [67]

    H. Chen, C. Rouz´ e, J. Chen, J. Jiang, S. O. Scalet, Y. Zhan, G. K. Chan, L. Ying, and Y. Tong, Con- vergence of the cumulant expansion and polynomial- time algorithm for weakly interacting fermions, arXiv preprint arXiv:2512.12010 (2025)

    work page arXiv 2025

  66. [68]

    Moessner, S

    R. Moessner, S. L. Sondhi, and P. Chandra, Two- dimensional periodic frustrated ising models in a trans- verse field, Phys. Rev. Lett.84, 4457 (2000)

    2000

  67. [69]

    Reinken, S

    R. Moessner and S. L. Sondhi, Ising models of quan- tum frustration, Physical Review B63, 10.1103/phys- revb.63.224401 (2001)

    work page doi:10.1103/phys- 2001

  68. [70]

    Kreißelet al., in preparation

    T. Kreißelet al., in preparation

  69. [71]

    First excitations of the spin 1/2 Heisenberg antiferromagnet on the kagom\'e lattice

    C. Waldtmann, H.-U. Everts, B. Bernu, C. Lhuillier, P. Sindzingre, P. Lecheminant, and L. Pierre, First ex- citations of the spin 1/2 Heisenberg antiferromagnet on the kagom´ e lattice, European Physical Journal B2, 501 (1998), arXiv:cond-mat/9802168 [cond-mat.stat-mech]

    work page internal anchor Pith review Pith/arXiv arXiv 1998

  70. [72]

    H. Nakano, Numerical-Diagonalization Study of Spin Gap Issue of the Kagome Lattice Heisenberg Antifer- romagnet, Journal of the Physical Society of Japan80, 053704 (2011), arXiv:1103.5829 [cond-mat.mtrl-sci]

    work page internal anchor Pith review Pith/arXiv arXiv 2011

  71. [73]

    Lee and R

    M. Lee and R. C. Farrell, Studying energy-resolved transport with wavepacket dynamics on quantum com- puters (2026), arXiv:2601.16180 [quant-ph]

    work page arXiv 2026

  72. [74]

    Shinjo, K

    K. Shinjo, K. Seki, and S. Yunoki, Emergent Dis- crete Time Crystals on Digital Quantum Comput- ers: Boundary-Protected and Ancilla-Induced Disor- der Mechanisms of Thermalization Slowdown (2025), arXiv:2510.13577 [quant-ph]

    work page arXiv 2025

  73. [75]

    R. C. Farrell, M. Illa, A. N. Ciavarella, and M. J. Sav- age, Quantum simulations of hadron dynamics in the Schwinger model using 112 qubits, Phys. Rev. D109, 114510 (2024), arXiv:2401.08044 [quant-ph]

    work page arXiv 2024

  74. [76]

    J. J. Wallman and J. Emerson, Noise tailoring for scalable quantum computation via randomized compil- ing, Phys. Rev. A94, 052325 (2016), arXiv:1512.01098 [quant-ph]

    work page internal anchor Pith review Pith/arXiv arXiv 2016

  75. [77]

    E. v. d. Berg, Z. K. Minev, A. Kandala, and K. Temme, Probabilistic error cancellation with sparse Pauli–Lindblad models on noisy quantum processors, Nature Phys.19, 1116 (2023), arXiv:2201.09866 [quant- ph]

    work page arXiv 2023

  76. [78]

    E. H. Chen, S. Chen, L. E. Fischer, A. Eddins, L. C. G. Govia, B. Mitchell, A. He, Y. Kim, L. Jiang, and A. Seif, Disambiguating Pauli noise in quantum com- puters (2025), arXiv:2505.22629 [quant-ph]

    work page arXiv 2025

  77. [79]

    Katschke, R

    L. Katschke, R. C. Farrell, U. Borla, L. Pollet, and J. C. Halimeh, Finite-Temperature Dynamical Phase Diagram of the 2 + 1D Quantum Ising Model (2026), arXiv:2602.16772 [quant-ph]

    work page arXiv 2026

  78. [80]

    Wang and Z

    K. Wang and Z. Ding, Beyond lindblad dynamics: Rig- orous guarantees for thermal and ground state preser- vation under system bath interactions, arXiv preprint arXiv:2512.03457 (2025)

    work page arXiv 2025

  79. [81]

    H.-E. Li, Y. Zhan, and L. Lin, Dissipative ground state preparation in ab initio electronic structure theory, npj Quantum Information11, 183 (2025)

    2025

  80. [82]

    Moessner, S

    R. Moessner, S. L. Sondhi, and P. Chandra, Phase di- agram of the hexagonal lattice quantum dimer model, Phys. Rev. B64, 144416 (2001)

    2001

Showing first 80 references.