Pith. sign in

REVIEW 4 major objections 5 minor 74 references

Wigner Cat Phases: A finely tunable system for exploring the transition to quantum chaos

T0 review · 4 major / 5 minor · reviewed 2026-08-03 · deepseek-v4-flash

Pith's one-line read A single tunable parameter moves a mixed random-matrix ensemble from Wigner-Dyson chaos to a heavy-tailed, cat-eared localized phase without ever reaching Poisson statistics.

desk verdict The paper is a transparent numerical study of a size-mixing GOE ensemble, but the claimed MBL phase is likely an artifact of periodic padding that creates exact degeneracies. read the letter →

arxiv 2512.22169 v4 pith:37LCGVCD submitted 2025-12-17 quant-ph cond-mat.stat-mech

classification quant-phcond-mat.stat-mech PACS 05.45.Mt
keywords quantumchaosrandommatrixtheorymany-bodylocalizationeigenstatethermalizationspectralstatisticsmixedGaussianorthogonalensemblegapratioWignercatphase
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper proposes a mixed Gaussian Orthogonal Ensemble (mGOE), built from GOE matrices of random sizes, with one tuning parameter μ that continuously adjusts the degree of mixing. At μ = 1 the ensemble reproduces standard Wigner-Dyson level statistics; as μ is lowered, the spectral density grows M-shaped 'cat ears,' the nearest-neighbour spacing distribution acquires heavy tails, and the mean adjacent-gap ratio drops below the Poisson value — yet full Poisson statistics are never reached. The author interprets these regimes as a new family of many-body localized phases, 'Wigner Cat Phases,' which are heavy-tailed and non-thermal. This matters because mGOE gives a simple, finely tunable testbed for the transition to localization and for eigenstate thermalization, and because it reveals a limitation of the standard gap-ratio statistic, which can read such heavy-tailed phases as integrable.

What carries the argument

The key object is the mixed Gaussian Orthogonal Ensemble (mGOE), an ensemble whose members are GOE matrices of different sizes ni drawn from a binomial distribution with success probability μ and then padded by periodic boundary conditions — eigenvalues are repeated up to the base size N — so that all spectra can be compared on equal footing. This periodic alignment is the mechanism that produces degeneracy and the 'defect' the paper identifies as driving localization; the parameter μ acts as the single continuous dial from the chaotic (μ→1) Wigner-Dyson regime to the localized (μ lower) 'cat-eared' regime. The adjacent-gap ratio (the ratio of consecutive spacings) serves as the principal pr

What would settle it

Take a single GOE spectrum of size n and pad it by repeating eigenvalues up to the base size N exactly as the periodic boundary rule prescribes; compute the nearest-neighbour spacing distribution and the mean adjacent-gap ratio. If the padded single spectrum alone reproduces the heavy tails and a mean gap ratio near 0.21, then the reported Wigner Cat Phase is an artifact of the alignment rule rather than a property of the mixed-size ensemble.

Watch

Extended reading notes

Core claim

On the paper's own terms, the central discovery is that a mixed Gaussian Orthogonal Ensemble, formed by sampling GOE matrices of sizes drawn from a binomial distribution and aligning their spectra by periodic boundary conditions, exhibits a continuous transition as the mixture parameter μ decreases: the eigenvalue density develops an M-shaped 'cat-ears' structure, the nearest-neighbour spacing distribution becomes heavy-tailed, and the mean adjacent-gap ratio falls to values well below the Poisson integrable limit (e.g., 0.21 at μ = 0.70) without the system ever showing Poisson statistics. The paper concludes that these 'Wigner Cat Phases' represent new heavy-tailed many-body localized state

Load-bearing premise

The load-bearing premise is that repeating eigenvalues to align spectra of differently sized matrices is a physical degeneracy (periodic boundary condition) and not just a numerical stitching step; if the repeated eigenvalues are an artifact, the heavy-tailed spacings, the cat-ears density, and the sub-Poisson gap ratios all follow from that padding rule, and the claimed new many-body localized phase collapses.

Editorial extensions

If this is right

  • If the Wigner Cat Phases are genuine, the standard adjacent-gap-ratio statistic alone cannot distinguish integrability from heavy-tailed non-thermal phases; MBL diagnostics should combine gap ratios with spacing distributions and spectral-shape measures.
  • mGOE provides a continuously tunable random-matrix model to study the transition to many-body localization and the breakdown of eigenstate thermalization, with fine resolution on the approach to the localized regime.
  • The cat-ears shape of the eigenvalue density is proposed as a global, topological fingerprint of the localization transition, usable as a complementary diagnostic in numerical studies and possibly experiments.
  • The result implies that heavy-tailed nearest-neighbour spacing distributions are compatible with integrable-looking mean gap ratios, so simulations or experiments that only report mean gap ratios may miss such localized phases.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A critical test is whether the periodic padding rule itself is responsible for all the reported effects: applying the same repeat-eigenvalues padding to a single Poisson spectrum may produce the same heavy tails and low gap ratios, which would make the cat-ears phase an artifact of the alignment rule.
  • The M-shaped density may simply be the superposition of different semicircle laws from the heterogeneous matrix sizes; if so, the cat-ears reflect ensemble averaging over sizes rather than an interaction-driven many-body phase.
  • If the mechanism is genuine, the same construction should work with unitary or symplectic ensembles, so observing cat-ears in mixed unitary ensembles would provide a universality check; if it fails, the phenomenon is specific to the orthogonal symmetry.
  • The sub-Poisson mean gap ratio of 0.21 is so far below the Poisson value (about 0.386) that it suggests a strong degeneracy effect; checking how the ratio behaves as the number of repeated eigenvalues is varied would clarify whether this is a real phase or a scaling artifact.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 5 minor

Summary. The paper introduces a mixed Gaussian Orthogonal Ensemble (mGOE) in which matrix sizes are drawn from a Binomial(N, μ) distribution and the resulting spectra of different lengths are aligned by 'periodic boundary conditions' — i.e., eigenvalues are repeated up to a common base size N. The author numerically studies the spectral density, nearest-neighbour spacing distribution, and adjacent gap ratio as μ is varied, and reports a continuous crossover from Wigner-Dyson statistics at μ≈1 to a localized 'Wigner Cat Phase' at lower μ, characterised by an M-shaped eigenvalue density and heavy-tailed spacings but no Poisson statistics. The conclusion states that this demonstrates MBL phases with heavy-tailed nearest-neighbour spacings and exposes limitations of gap-ratio statistics.

Significance. If established, the claimed mGOE phase would be a simple, finely tunable random-matrix model interpolating between quantum chaos and a non-thermal localized regime, with a cautionary message about relying solely on the mean gap ratio. The numerical work is transparent: histograms are presented with bootstrapped 95% confidence intervals, the construction is easy to reproduce, and the author makes the code publicly available. However, the central physical claim currently rests on a spectral-alignment procedure that mechanically injects exact degeneracies; without a control that separates this artifact from a genuine localization phenomenon, the 'Wigner Cat Phase' is not established as a property of a quantum system.

major comments (4)
  1. [Section 3.1, Eq. (2) and Figures 1–3] The periodic-padding alignment is the load-bearing step. Repeating eigenvalues of matrices of size n_i < N until base size N is reached creates exact zero spacings at every repetition. These degeneracies alone can produce a heavy-tailed NNSD, an M-shaped superposed density, and a mean gap ratio as low as 0.21 (Fig. 3d), below the Poisson value 0.386. The paper provides no control experiment in which the duplicated eigenvalues are removed or an alternative alignment rule is used. Without such a control, the reported signatures are explained by the padding rule itself, and the claimed new MBL phase is not supported.
  2. [Abstract and Section 3.1] The abstract proposes a physical setting of a frozen qubit composed with a thermalized chaotic system, but this setting never appears again in the body. No Hamiltonian, coupling, or selective-observation protocol is defined, and the localization mechanism is only 'conjectured to be an inherent property of the mixed ensemble' (Section 3.1). A claim of a novel quantum MBL phase requires at least a concrete physical model or a derivation connecting the spectral construction to a quantum many-body system; neither is supplied.
  3. [Section 3.2] The self-consistent unfolding selects a polynomial degree by requiring that the mean fluctuation be closest to one. Because the heavy-tailed NNSD is one of the central pieces of evidence, this self-consistency criterion can bias the inferred distribution. The paper does not report how the NNSD varies with the polynomial degree or with the truncation of outliers for the mGOE case. The gap-ratio analysis is less sensitive to unfolding, but the spacing-distribution claim requires an independent robustness check.
  4. [Section 4.3, Figure 4] The linear interpolation of mean gap ratios in Figure 4 is presented as a 'transition from quantum chaos to localisation,' but no quantitative criterion distinguishes a genuine phase crossover from a trivial consequence of mixing two different spectral densities with weights set by μ. The r(μ) curve should be compared with the expectation from the padding-degeneracy mechanism alone, e.g., by computing r for spectra that are randomly padded without the GOE size-mixing step.
minor comments (5)
  1. [Section 3, notation] The parameter order of mGOE is given as mGOE(M,N,μ) in Section 3 but as mGOE(N,M,μ) in Section 3.1; please make the notation consistent.
  2. [Section 4.3, Figure 4] The text says the linear behaviour 'is quantified in Figure 3.2,' but the figure is numbered Figure 4.
  3. [Throughout] There are several typos and misspellings, e.g., 'Neareast', 'Emprical', 'indicing', 'S¨ uzen' in headers, and 'i.e.' vs. 'e.g.' misuse. These do not affect the science but should be corrected.
  4. [Section 4.1] The phrase 'small mixtures, i.e., higher μ values' is confusing; μ is called the 'degree of mixture,' so larger μ corresponds to less mixing. Please rephrase to avoid ambiguity.
  5. [References] The DOI links for Refs. [62] and [63] appear to be placeholders or malformed (e.g., '10.1103/txkh-wftd') and should be checked.

Circularity Check

2 steps flagged · score 7.0 of 10

Wigner Cat/MBL signatures are inscribed by the periodic-padding step: repeated eigenvalues force the heavy-tailed NNSD and r≈0.21 by construction.

  1. self definitional [Section 3.1 (Spectral Periodicity: Degeneracy and inducing localisation); used in Sections 4.2–4.3]
    "The matrix with size n_i will produce n_i eigenvalues. Periodicity dictates repeated eigenvalues up to the base size N for mGOE, recall the parameters of the ensemble mGOE(N, M, µ). This leads to degeneracy in the energy levels."

    The adjacent gap ratio is defined as min(δ_i,δ_{i−1})/max(δ_i,δ_{i−1}), so any repeated eigenvalue yields δ_i=0 and r=0. Periodic padding inserts exactly such repetitions for every matrix with n_i<N, and decreasing µ makes smaller matrices more frequent through Binomial(µ,N). The heavy-tailed NNSD and the mean r≈0.21 reported at µ=0.70 are therefore mechanical consequences of the alignment rule, not an emergent property of a quantum system: the 'prediction' is equivalent to the construction.

  2. other [Section 3.1 and Section 4.1 (Wigner Cat Phases: Spectral Densities)]
    "This is not a finite-size effect, rather conjectured to be an inherent property of the mixed ensemble. ... We identify that this phenomenon originates from the combination of eigenstate degeneracy and randomness creating an effect of a defect, as discussed in the formulation of mGOE generation."

    The paper's own text labels the localization mechanism a conjecture and attributes the cat-ears density to eigenstate degeneracy and randomness introduced in the generation recipe. Thus the central 'Wigner Cat Phase' is not derived or independently benchmarked; it is the chosen stitching rule restated as a discovery. No physical Hamiltonian or alternative alignment (e.g., trimming instead of padding) is provided to show the signatures are robust rather than artifacts.

full rationale

The paper is internally consistent and the µ=1.0 GOE limit is correctly benchmarked against Wigner-Dyson and semicircle behavior. However, every novel signature that supports the claimed MBL transition—the M-shaped 'cat-ears' density, the heavy-tailed NNSD, and the sub-Poisson mean gap ratio 0.21—is forced by the periodic boundary padding rule in Section 3.1. Since µ directly controls how many spectra are drawn with n_i<N and then padded by repeating eigenvalues, the 'transition' is a restatement of the construction: fewer/ more repeated eigenvalues produce more/fewer zero spacings and larger/smaller boundary gaps. The paper itself concedes the localization mechanism is 'conjectured' and attributes the phenomenon to 'eigenstate degeneracy and randomness' in the formulation. The conclusion that a new MBL phase exists therefore reduces to the definition of the mixed ensemble, not to an independently established physical result. This warrants a score of 7: partial circularity, with the GOE limit providing a legitimate but peripheral check.

Assumptions & free parameters 3 free parameters · 4 assumptions · 2 invented entities

The central claim rests on a special stitching rule and on the identification of GOE statistics with quantum chaos; neither is derived in the paper.

free parameters (3)
  • µ (degree of mixture) = scanned: 0.54, 0.70, 0.86, 0.88, 0.92, 0.98 (no fit)
    Central tuning parameter; success probability of Binomial(N,µ). All claimed phases depend on it, and it is chosen by hand, not derived.
  • Unfolding polynomial degree
    Selected per spectrum so that mean fluctuations are closest to one (Section 3.2). This post-hoc choice can reshape NNSD and is not fixed by theory.
  • Computational sizes N, M = N=1000/500, M=100
    Finite computational choices. No convergence study across M, and only two N values are shown, so finite-size dependence of the 'cat-ears' is untested.
assumptions (4)
  • domain assumption BGS conjecture: GOE level statistics indicate quantum chaos and thermalization.
    Invoked in Sections 1 and 2 to interpret the µ=1.0 limit as ETH/quantum chaos.
  • ad hoc to paper Periodic boundary condition on spectra: repeating eigenvalues up to base size N is a valid alignment.
    Section 3.1 states 'Periodicity dictates repeated eigenvalues up to the base size N.' This is the key stitching rule on which all observed signatures depend.
  • ad hoc to paper Mixing sizes via Binomial(N,µ) plus periodic padding represents induced disorder/localization.
    Section 3.1 asserts this produces a defect driving localization, but calls it a conjecture rather than a derivation.
  • domain assumption IQR truncation and self-consistent polynomial unfolding preserve the level-spacing statistics.
    Section 3.2 assumes these procedures do not distort the NNSD, yet the unfolding degree is tuned to make mean fluctuations near one.
invented entities (2)
  • Wigner Cat Phases (cat-ears)
    purpose: Name for the M-shaped empirical spectral density claimed to be a new MBL phase.
    No independent observable or falsifiable prediction; the shape is the direct histogram of mixed GOE spectra.
  • Spectral defect induced by size mixing
    purpose: Proposed mechanism for localization in mGOE (Section 3.1).
    Conjectured, not derived or measured independently; no handle outside this model.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Wigner Cat Phases: A finely tunable system for exploring the transition to quantum chaos." pith.science (2026). https://pith.science/paper/37LCGVCD

@misc{pith2026251222169,
  author       = {Pith},
  title        = {Pith review of: Wigner Cat Phases: A finely tunable system for exploring the transition to quantum chaos},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/37LCGVCD}},
  note         = {Machine review of arXiv:2512.22169}
}
read the original abstract

A quantum mechanical setting consisting of a frozen qubit composed with a fully thermalized chaotic system of N states is proposed, with potential relevance to quantum control. Observing the states of the composed system selectively retaining the states leads to the observation of novel localization in the subsystem. At a tuning parameter of 1.0, implying no selection, the system exhibits Wigner-Dyson level spacing statistics, indicative of quantum chaos. As the tuning parameter is reduced and selection occurs at a cutoff, the nearest-neighbor level spacing distribution develops heavier tails, a signature of suppressed spectral mixing and the emergence of non-thermal dynamics. In these regimes, the eigendensity develops a pronounced "cat-ears" structure, reflecting the formation of spatially localized bimodal eigenstates. These topological features persist without transitioning to Poisson statistics, indicating a transition from quantum chaos to a non-thermal, novel many-body localized (MBL) regime-referred to as Wigner Cat Phases. The proposed mixed random matrix ensemble offers a practical probe for sustaining this novel quantum localization setting. Results from our rigorous spectral statistics analysis show how "cat-ears" form in spectral densities based on the degree of selection or disorder and indicate that gap ratio statistics must be used with caution in detecting the full integrable limit due to the possibility of heavy-tailed Wigner-Dyson distributions.

Figures

Figures reproduced from arXiv: 2512.22169 by the authors.

Figure 1
Figure 1. Spectral densities are numerically identified for different tuning parameters, at (1a) µ = 0.54, (1b) µ = 0.70, (1c) µ = 0.88 and, (1d) µ = 0.98. These are so-called Wigner Cat Phases due to their M-shaped densities deviating from Wigner’s semi-circle law. Uncertainties are computed over mGOE ensemble via bootstrapped 95% confidence intervals appear as error bars. We see that semicircle law is recovered at small mix… view at source ↗
Figure 2
Figure 2. Nearest-neighbour spacings for different µ values are shown, (2a) µ = 0.54, (2b) µ = 0.70, (2c) µ = 0.86, and (2d) µ = 0.98. Deviation from Wigner-Dyson distribution at smaller µ values is demonstrated with lower values indicating heavy-tailed distribution. There is no observed full integrability even in small µ values, i.e., Poisson distribution is not observed. Uncertainties are computed over mGOE ensemble via boo… view at source ↗
Figure 3
Figure 3. Density of adjacent gap ratios with mean values marked at different degree of mixtures, (3a) µ = 0.98, (3b) µ = 0.92, (3c) µ = 0.86 and (3d) µ = 0.70. Uncertainties are computed over mGOE ensemble via bootstrapped 95% confidence intervals appear as error bars. We see that tail is changing at higher mixtures, i.e., lower µ values. If we invoke BGS conjecture, as it is shown recently that BGS has better statistical pr… view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: Average (Mean) gap ratios over different mixture µ strengths. These values inform us how localisation changes. Horizontal lines describe reaching full ETH and full integrability respectively reported average gap ratio statistics in the literature. 4 Numerical Experimen…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

74 extracted references · 22 canonical work pages

  1. [1]

    Berry M V 1987New Scientist1944 URLhttps://www.osti.gov/etdeweb/biblio/5707886

  2. [2]

    Martinis J M, Devoret M H and Clarke J 1987Phys. Rev. B35(10) 4682–4698 URL https://link.aps.org/doi/10.1103/PhysRevB.35.4682

  3. [3]

    Ford J and Mantica G 1992American Journal of Physics601086–1098 URL https://doi.org/10.1119/1.16954

  4. [4]

    Gutzwiller M C 1992Scientific American26678–85 URL https://www.jstor.org/stable/24938902

  5. [5]

    Heller E J and Tomsovic S 1993Physics Today4638–46 URL https://doi.org/10.1063/1.881358

  6. [6]

    Berry M V 1977Journal of Physics A: Mathematical and General102083 URL https://doi.org/10.1088/0305-4470/10/12/016 7 S¨ uzen

  7. [7]

    Chirikov B, Izrailev F and Shepelyansky D 1988Physica D: Nonlinear Phenomena3377–88 URLhttps://doi.org/10.1016/S0167-2789(98)90011-2

  8. [8]

    Zurek W H and Paz J P 1995Physica D: Nonlinear Phenomena83300–308 URL https://doi.org/10.1016/0167-2789(94)00271-Q

Show all 74 references
  1. [9]

    Nakamura K 1994Quantum chaos: a new paradigm of nonlinear dynamicsvol 3 (CUP Archive)

  2. [10]

    Chirikov B and Casati G 1995Quantum Chaos: Between Order and Disorder(Cambridge University Press) URL https://www.cambridge.org/er/universitypress/subjects/physics/ nonlinear-science-and-fluid-dynamics/quantum-chaos-between-order-and-disorder

  3. [11]

    St¨ ockmann H J 2009Quantum Chaos: An Introduction(Cambridge University Press) URL https://doi.org/10.1017/CBO9780511524622

  4. [12]

    Gutzwiller M C 2013Chaos in Classical and Quantum Mechanics(Springer Science & Business Media) URLhttps://doi.org/10.1007/978-1-4612-0983-6

  5. [13]

    Wimberger S 2014Nonlinear dynamics and quantum chaosvol 10 (Springer) URL https://doi.org/10.1007/978-3-319-06343-0

  6. [14]

    Haake F, Gnutzmann S and Ku´ s M 2018Quantum Signatures of Chaos4th ed (Springer Cham) URLhttps://doi.org/10.1007/978-3-319-97580-1

  7. [15]

    Heller E J 2018The semiclassical way to dynamics and spectroscopy(Princeton University Press)

  8. [16]

    Bohigas O, Giannoni M J and Schmit C 1984Physical Review Letters521 URL https://doi.org/10.1103/PhysRevLett.52.1

  9. [17]

    Wishart J 1928Biometrika2032–52 URLhttps://doi.org/10.2307/2331939

  10. [18]

    Wigner E P 1951Mathematical Proceedings of the Cambridge Philosophical Society47 790–798 URLhttps://doi.org/10.1017/S0305004100027237

  11. [19]

    Wigner E P 1955Annals of Mathematics62548–564 URL https://doi.org/10.2307/1970079

  12. [20]

    Wigner E P 1957Annals of Mathematics65203–207 URL https://doi.org/10.2307/1969956

  13. [21]

    Wigner E P 1958Annals of Mathematics67325–327 URL https://doi.org/10.2307/1970008

  14. [22]

    Wigner E P 1967SIAM Review91–23 URLhttps://www.jstor.org/stable/2027409

  15. [23]

    Dyson F J 1962Journal of Mathematical Physics31199–1233 URL https://doi.org/10.1063/1.1703871

  16. [24]

    Dyson F J 1962Journal of Mathematical Physics3157–165 URL https://doi.org/10.1063/1.1703774

  17. [25]

    Dyson F J 1962Journal of Mathematical Physics3166–175 ISSN 0022-2488 URL https://doi.org/10.1063/1.1703775

  18. [26]

    Dyson F J and Mehta M L 1963Journal of Mathematical Physics4701–712 URL https://doi.org/10.1063/1.1704008

  19. [27]

    Mehta M L and Dyson F J 1963Journal of Mathematical Physics4713–719 URL https://doi.org/10.1063/1.1704009

  20. [28]

    Mehta M L 2004Random Matrices3rd ed vol 142 (Elsevier) URL https://doi.org/10.1016/S0079-8169(04)80088-6

  21. [29]

    Tao T 2012Topics in Random Matrix Theoryvol 132 (American Mathematical Society) URL https://bookstore.ams.org/GSM-132-S/ 8 S¨ uzen

  22. [30]

    Potters M and Bouchaud J P 2020A first course in random matrix theory(Cambridge University Press) URLhttps://doi.org/10.1017/9781108768900

  23. [31]

    Jarzynski C 1997Physical Review E562254 URL https://doi.org/10.1103/PhysRevE.56.2254

  24. [32]

    Deutsch J M 1991Phys. Rev. A43(4) 2046–2049 URL https://link.aps.org/doi/10.1103/PhysRevA.43.2046

  25. [33]

    Srednicki M 1994Physical Review E50888 URL https://doi.org/10.1103/PhysRevE.50.888

  26. [34]

    Srednicki M 1994arXiv preprint cond-mat/9410046URL https://doi.org/10.48550/arXiv.cond-mat/9410046

  27. [35]

    Srednicki M 1995Annals of the New York Academy of Sciences755757–760 URL https://doi.org/10.1111/j.1749-6632.1995.tb39017.x

  28. [36]

    Srednicki M 1996Journal of Physics A: Mathematical and General29L75 URL https://doi.org/10.1088/0305-4470/29/4/003

  29. [37]

    Srednicki M 1999Journal of Physics A: Mathematical and General321163 URL https://doi.org/10.1088/0305-4470/32/7/007

  30. [38]

    D’Alessio L, Kafri Y, Polkovnikov A and Rigol M 2016Advances in Physics65239–362 URL https://doi.org/10.1080/00018732.2016.1198134

  31. [39]

    Deutsch J M 2018Reports on Progress in Physics81082001 URL https://doi.org/10.1088/1361-6633/aac9f1

  32. [40]

    Foini L and Kurchan J 2019Phys. Rev. E99(4) 042139 URL https://link.aps.org/doi/10.1103/PhysRevE.99.042139

  33. [41]

    Pappalardi S, Foini L and Kurchan J 2022Phys. Rev. Lett.129(17) 170603 URL https://link.aps.org/doi/10.1103/PhysRevLett.129.170603

  34. [42]

    Foini L, Dymarsky A and Pappalardi S 2025SciPost Phys.18136 URL https://scipost.org/10.21468/SciPostPhys.18.4.136

  35. [43]

    Mag´ an J M and Wu Q 2024 Two types of quantum chaos: testing the limits of the Bohigas-Giannoni-Schmit conjecture (Preprint2411.08186) URL https://arxiv.org/abs/2411.08186

  36. [44]

    Weidenm¨ uller H A 2025Journal of Physics A: Mathematical and Theoretical58385003 URL https://doi.org/10.1088/1751-8121/ae066b

  37. [45]

    Cotler J, Hunter-Jones N, Liu J and Yoshida B 2017Journal of High Energy Physics48 URL https://doi.org/10.1007/JHEP11(2017)048

  38. [46]

    Mag´ an J M 2018Journal of High Energy Physics201843 URL https://doi.org/10.1007/JHEP09(2018)043

  39. [47]

    Ali T, Bhattacharyya A, Haque S S, Kim E H, Moynihan N and Murugan J 2020Phys. Rev. D101(2) 026021 URLhttps://link.aps.org/doi/10.1103/PhysRevD.101.026021

  40. [48]

    Altland A, Kim K W, Micklitz T, Rezaei M, Sonner J and Verbaarschot J J M 2024Phys. Rev. Res.6(3) 033286 URLhttps://link.aps.org/doi/10.1103/PhysRevResearch.6.033286

  41. [49]

    B¨ orner S D, Berke C, DiVincenzo D P, Trebst S and Altland A 2024Phys. Rev. Res.6(3) 033128 URLhttps://link.aps.org/doi/10.1103/PhysRevResearch.6.033128

  42. [50]

    Anand A, Srivastava S, Gangopadhyay S and Ghose S 2024Scientific Reports1426890 URL https://doi.org/10.1038/s41598-024-76448-0

  43. [51]

    Google Quantum AI Team 2025Nature646825–830 URL https://doi.org/10.1038/s41586-025-09526-6 9 S¨ uzen

  44. [52]

    Das A K, Cianci C, Cabral D G A, Zarate-Herrada D A, Pinney P, Pilatowsky-Cameo S, Matsoukas-Roubeas A S, Batista V S, del Campo A, Torres-Herrera E J and Santos L F 2025 Phys. Rev. Res.7(1) 013181 URL https://link.aps.org/doi/10.1103/PhysRevResearch.7.013181

  45. [53]

    Sierant P, Lewenstein M, Scardicchio A, Vidmar L and Zakrzewski J 2025Reports on Progress in Physics88026502 URLhttps://doi.org/10.1088/1361-6633/ad9756

  46. [54]

    Santos L F 2004Journal of Physics A: Mathematical and General374723 URL https://doi.org/10.1088/0305-4470/37/17/004

  47. [55]

    Chavda N, Deota H and Kota V 2014Physics Letters A3783012–3017 URL https://doi.org/10.1016/j.physleta.2014.08.021

  48. [56]

    Sierant P and Zakrzewski J 2019Phys. Rev. B99(10) 104205 URL https://link.aps.org/doi/10.1103/PhysRevB.99.104205

  49. [57]

    Pai S, Srivatsa N and Nielsen A E 2020Physical Review B102035117 URL https://doi.org/10.1103/PhysRevB.102.035117

  50. [58]

    Buijsman W, Cheianov V and Gritsev V 2019Phys. Rev. Lett.122(18) 180601 URL https://link.aps.org/doi/10.1103/PhysRevLett.122.180601

  51. [59]

    Rao W J 2022Physica A: Statistical Mechanics and its Applications590126689 ISSN 0378-4371 URL https://www.sciencedirect.com/science/article/pii/S037843712100916X

  52. [60]

    Rao W, Zhao F and Wang Y 2024The European Physical Journal Plus139722 URL https://doi.org/10.1140/epjp/s13360-024-05537-w

  53. [61]

    Shekhar D and Shukla P 2023Journal of Physics A: Mathematical and Theoretical56265303 URLhttps://doi.org/10.1088/1751-8121/acd9fe

  54. [62]

    Shekhar D and Shukla P 2025Phys. Rev. E112(2) 024122 URL https://link.aps.org/doi/10.1103/txkh-wftd

  55. [63]

    Shekhar D and Shukla P 2025Phys. Rev. E112(2) 024123 URL https://link.aps.org/doi/10.1103/n16c-45rh

  56. [64]

    S¨ uzen M 2020arXiv preprint arXiv:2006.13687URL https://doi.org/10.48550/arXiv.2006.13687

  57. [65]

    S¨ uzen M 2021HAL-ScienceURLhttps://hal.science/hal-03464130/

  58. [66]

    Abul-Magd A A and Abul-Magd A Y 2014Physica A: Statistical Mechanics and its Applications396185–194 ISSN 0378-4371 URL https://www.sciencedirect.com/science/article/pii/S0378437113010546

  59. [67]

    Abuelenin S M 2018Physica A: Statistical Mechanics and its Applications492564–570 URL https://doi.org/10.1016/j.physa.2017.08.158

  60. [68]

    Oganesyan V and Huse D A 2007Phys. Rev. B75(15) 155111 URL https://link.aps.org/doi/10.1103/PhysRevB.75.155111

  61. [69]

    Jisha C and Prakash R 2024Europhysics Letters14611001 URL https://doi.org/10.1209/0295-5075/ad2c35

  62. [70]

    Edelman A and Rao N R 2005Acta Numerica14233–297 URL https://doi.org/10.1017/S0962492904000236

  63. [71]

    Tibshirani R J and Efron B 1993571–436 URLhttps://doi.org/10.1201/9780429246593

  64. [72]

    Davison A C and Hinkley D V 1997Bootstrap methods and their application1 (Cambridge University Press) URLhttps://doi.org/10.1017/CBO9780511802843

  65. [73]

    S¨ uzen M 2025arXiv preprint arXiv:2505.23869URL https://doi.org/10.48550/arXiv.2505.23869

  66. [74]

    Suezen M 2025 Leymosun: High-entropy randomness research toolkit URL https://doi.org/10.5281/zenodo.17912257 10

Pith tools

Reviewed August 3, 2026 · model on record in the stance chip above.