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REVIEW 3 major objections 5 minor 67 references

Swap Monte Carlo for diatomic molecules

T0 review · 3 major / 5 minor · reviewed 2026-08-16 · deepseek-v4-flash

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Pith's one-line read This paper shows a simple polydisperse dumbbell liquid can be equilibrated with Swap Monte Carlo down to temperatures near the experimental glass transition, with estimated speedups of 10^3–10^6 over standard molecular dynamics.

desk verdict First credible Swap MC extension to non-spherical molecules, with a real but contained weakness: the headline speedup is extrapolated from fits the paper does not report. read the letter →

arxiv 2504.15238 v2 pith:CZGRSGJ7 submitted 2025-04-21 cond-mat.soft

Till Böhmer , Jeppe C. Dyre , Lorenzo Costigliola This is my paper · ORCID
classification cond-mat.soft
keywords swapMonteCarlomolecularglassformerasymmetricdumbbellspolydispersitysupercooledliquidsorientationalrelaxationtransitiondynamicssimulation
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

This paper introduces a minimal molecular model—size-polydisperse asymmetric dumbbells—that can be equilibrated with Swap Monte Carlo at temperatures low enough to approach the experimental glass transition, something previously possible only for spherical point particles. The authors report estimated speedups of $10^{3}$–$10^{6}$ over standard molecular dynamics at 5–10% polydispersity, and show that the orientational relaxation of the largest and smallest molecules differs by at most factors of 1.2 and 1.5, respectively. A sympathetic reader would care because this gives a route to simulating the rotational degrees of freedom of deeply supercooled molecular liquids directly, rather than inferring them from atomic models. The paper also confirms the swapped configurations are true equilibrium states by showing the absence of aging and continuity of potential energy with temperature.

What carries the argument

The load-bearing object is the size-polydisperse asymmetric dumbbell (ASD) model with molecule-level swaps: each molecule is a harmonic-bonded pair of a large A particle and a small B particle, and polydispersity enters by scaling both sizes of a molecule by the same factor drawn uniformly from [1-Δ,1+Δ] with 500 discrete types. The swap algorithm alternates short NVT molecular-dynamics runs (t=0.32) with 2N attempts to exchange the size parameters of randomly chosen molecule pairs, accepted by Metropolis rules. The argument is carried by comparing orientational relaxation times from P2(t) during swap and standard MD, and by extrapolating the MD relaxation times using the VFT and parabolic formulas to estimate the speedup at T=0.29 and the glass-transition temperature via the criterion τMD(Tg)/τ0 = $10^{12}$. The machinery also includes checks for equilibrium: absence of aging in P2(t) halves and continuity of potential energy across temperatures.

What would settle it

Run standard MD on the δ=10% system at T=0.31, measure the orientational relaxation time directly, and compare it with the VFT and parabolic extrapolations anchored at higher temperatures; a measured value well below the extrapolated band would invalidate the estimated $10^{4}$–$10^{6}$ speedup at T=0.29, while agreement would support it.

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Extended reading notes

Core claim

The central claim is that Swap Monte Carlo works for a molecular liquid when the swapped property is the molecular size: each molecule is an asymmetric dumbbell of large and small particles (modeling toluene-like chemistry), and the two particle sizes of a given molecule are scaled together so that the whole molecule swaps size with another molecule. With only 5–10% size polydispersity, the algorithm accelerates both rotational and translational relaxation by the same large factor, reaching T=0.29 in reduced units, near the estimated Tg of 0.25–0.285. The size-resolved orientational autocorrelation functions P2(t) show that the smallest and largest molecules relax nearly alike—a ratio of relaxation times at most 1.2 for 5% and 1.5 for 10% polydispersity—in contrast to the factor-of-50 differences reported for highly polydisperse point-particle systems. The authors therefore propose the model as a minimal, realistic system for studying deeply supercooled molecular liquids in silico.

Load-bearing premise

The quantitative speedup and glass-transition estimates rest on assuming that the standard formulas used to extrapolate the molecular-dynamics relaxation time from warmer temperatures down to T=0.29 remain accurate in that unmeasured range.

Editorial extensions

If this is right

  • Equilibrium configurations of a molecular liquid can now be generated at temperatures where τMD/τ0 ≈ 10^6–10^12, enabling direct simulation of the ultraviscous regime with rotations.
  • The model can serve as a baseline for comparing simulated dielectric relaxation spectra with experiments on molecular glass formers, e.g., checking for the predicted 1/√ω high-frequency decay of the α process.
  • The small size-resolved dynamical differences indicate that polydispersity artifacts seen in point-particle swap models do not contaminate this molecular model at 5–10% polydispersity.
  • Because swaps work at only 5% polydispersity, the approach may be extended to more complex molecules such as trimers, although efficiency is expected to drop for larger molecules.

Reading between the lines

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

  • The reported speedup range depends on extrapolating τMD from higher temperatures with VFT and parabolic fits; a direct measurement of τMD at T≈0.31–0.35, even approximate, would significantly narrow the 10^3–10^6 uncertainty.
  • If the near-equality of size-resolved relaxation persists at the estimated Tg, the model becomes a test bed for whether rotational and translational decoupling observed experimentally in molecular liquids arises from intrinsic molecular asymmetry rather than from polydispersity.
  • The successful removal of polydispersity at a shifted temperature (as in Fig. 5) hints that one could equilibrate with swaps and then 'de-polydisperse' to study a monodisperse molecular liquid at a renormalized temperature, effectively using swap MC as a preparation step rather than as the production ensemble.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. The paper introduces a size-polydisperse asymmetric-dumbbell (ASD) molecular model, based on earlier toluene-model parameters, and shows that a Swap Monte Carlo scheme that alternates short MD trajectories with swaps of molecular size parameters can equilibrate this model at temperatures down to T=0.29 in reduced units, near the estimated experimental glass-transition temperature. The central claims are (i) an estimated speedup of 10^3–10^6 relative to standard MD at the lowest temperature, depending on polydispersity, and (ii) that size-resolved orientational relaxation times differ by only small factors (≤1.2 for 5% polydispersity and ≤1.5 for 10%), in contrast to strongly polydisperse point-particle swap models. The authors support the equilibrium nature of the Swap-generated configurations by showing absence of aging in P2(t) and continuity of the potential energy as a function of temperature. They also report consistency between rotational and translational relaxation and provide additional correlation functions and swap-acceptance rates in the appendices.

Significance. If the central claims hold, this is a useful extension of Swap Monte Carlo from point particles to molecular degrees of freedom, enabling future numerical studies of rotational dynamics in deeply supercooled molecular liquids. The paper has clear strengths: the equilibrium checks in Fig. 3 (absence of aging and no kink in the energy curve) are appropriate and directly support the validity of the Swap-equilibrated configurations; the size-resolved P2(t) data in Fig. 4 provide direct evidence that low polydispersity does not introduce large dynamic heterogeneity; and the appendices extend the main conclusions to translational and first-order orientational correlators. The main weakness is that the headline speedup and Tg estimates rely on an extrapolation of τMD(T) whose fitting details are not reported, making the quantitative claim not independently reproducible as written.

major comments (3)
  1. [Section II, paragraph beginning "To estimate the maximum speedup..."] The central quantitative claims—the speedup of 10^3–10^6 at T=0.29 and the Tg estimates—depend on extrapolating τMD(T) from the lowest measured temperatures (near T=0.35–0.37 for the two polydispersities) down to T=0.29 using the VFT equation and the parabolic law. The manuscript does not report the fitted parameters, the fitting window, the number of data points, residuals, or any uncertainty estimate for either extrapolation. Since both functional forms are three-parameter empirical expressions and neither is constrained in the extrapolated regime, the stated ranges are not independently verifiable. Please add a table or paragraph with the full fit details, and also assess the sensitivity of the speedup and Tg estimates to the fitting window or to the inclusion/exclusion of individual data points.
  2. [Section II, same paragraph] The Tg estimates, obtained via the criterion τMD(Tg)/τ0 = 10^12, inherit the same extrapolation uncertainty as the speedup estimates. The reported ranges Tg(δ=10%) ≈ 0.265–0.285 and Tg(δ=5%) ≈ 0.250–0.270 are presented without error bars or a discussion of how the spread between VFT and parabolic extrapolations translates into an uncertainty interval. This should be stated explicitly, and the same fit documentation requested above should be used to quantify the uncertainty in Tg.
  3. [Section II, Fig. 2 and its discussion] The phrase "maximum speedup achieved in this study" in the abstract and Section II is stronger than what is actually measured: the speedup at T=0.29 is not directly measured but is obtained by combining measured τSwap(T=0.29) with extrapolated τMD(T=0.29). The wording "estimated" is used, which is appropriate, but the separation between directly measured speedups (at the lowest temperature where both τSwap and τMD are available) and extrapolated speedups should be made explicit in the text, ideally with the direct speedup values reported as well.
minor comments (5)
  1. [Section II, Eq. (2) and Fig. 1(a)] The definition of polydispersity δ in Eq. (2) is stated for the A-particle size distribution, but the caption of Fig. 1(a) merely says "particle-size distribution"; please clarify in the caption that the shown distribution is of the molecular (A-particle) sizes, not of all interaction sites.
  2. [Section II, simulation details] The text states that "The MD units used refer to the size and energy of the A particles of the monodisperse model." Please specify the complete set of MD units (length σ_A, energy ε_A, mass m_A, and the temperature unit ε_A/k_B) so that the reduced units are unambiguous.
  3. [Section II, simulation details] The sentence "resulting in acceptance rates of 15-30% (SI)" appears to conflict with Fig. 8, which shows acceptance rates decreasing with temperature and falling below 15% at the lowest temperatures. Please check the reported range or clarify whether the 15–30% range refers only to the higher-temperature portion of the data.
  4. [Appendix B, Fig. 8] The y-axis label in Fig. 8 reads "acceptance rate swaps"; for readability, write "swap acceptance rate" and add a unit or clarify it is dimensionless, as is conventional for Metropolis acceptance probabilities.
  5. [References] Reference [7] is given as "G. L. Hunter and E. R. Weeks" but should include the co-authors of "The physics of the colloidal glass transition" (the article has an additional author, M. D. Ediger or similar, depending on the journal version). Please verify the complete author list and also check reference [58] for the same issue.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the swap-speedup and size-resolved dynamics claims rest on direct simulation measurements, and the low-temperature speedup and Tg estimates are explicitly labeled extrapolations rather than fitted predictions.

full rationale

The paper's central claims are (i) a size-polydisperse asymmetric-dumbbell model can be equilibrated by Swap MC, (ii) Swap is orders of magnitude faster than standard MD, and (iii) size-resolved orientational relaxation times differ by only modest factors. Claims (i) and (iii) are supported by direct simulation data: equilibrium is checked by the absence of aging in Fig. 3(a) and by continuous potential-energy curves in Fig. 3(b), while the size-resolved relaxation-time ratios in Fig. 4(c) are measured quantities. The speedup at the lowest temperature is not an input disguised as an output: the paper explicitly states that τMD(T=0.29) exceeds the resolvable MD time scale and that the VFT and parabolic-law fits are used to extrapolate it, giving a range. This is an extrapolation estimate, not a parameter fitted to the target quantity and then renamed a prediction. The Tg estimates use the same extrapolated τMD with a standard 10^12 criterion; this is a definitional criterion applied to an extrapolation, not circular. The model interaction parameters are adopted from earlier toluene-model work (refs. 53-55) as external inputs; although two of those references are authored by Dyre, they are not invoked as proof of the present swap result, and the parameters are fixed inputs rather than outputs of the derivation. No self-citation chain forces the conclusion, no uniqueness theorem is imported, and no ansatz is smuggled in via citation. The concern about unreported fit parameters and extrapolation uncertainty is a reproducibility and robustness issue, not circularity.

Assumptions & free parameters 2 free parameters · 5 assumptions · 0 invented entities

The central claims rest on standard simulation methodology plus two empirical extrapolation fits. The model parameters come from prior toluene-model literature and are treated as inputs. No new physical entities, forces, or conservation laws are introduced. The main unverified ingredient is the VFT and parabolic extrapolation to T=0.29, which carries the quantitative speedup estimate.

free parameters (2)
  • VFT fit parameters (A, D, T0) for delta=5% and delta=10% MD relaxation times = not reported in the paper
    Fitted to the measured tau_MD(T) data and used to extrapolate tau_MD to T=0.29; the maximum speedup and Tg estimates depend on these values.
  • Parabolic-law fit parameters for delta=5% and delta=10% MD relaxation times = not reported in the paper
    Second empirical extrapolation of the same tau_MD data; used as an alternative to VFT and brackets the claimed speedup range.
assumptions (5)
  • domain assumption MD in the NVT ensemble with a Nosé-Hoover thermostat samples the canonical equilibrium distribution for the ASD model.
    Standard simulation practice; invoked implicitly in Section II when all equilibration and production data are generated.
  • standard math Swap moves with Metropolis acceptance preserve equilibrium with respect to the same Hamiltonian as the MD dynamics.
    Detailed balance is standard; the algorithm alternates MD and swap updates as described in Section II.
  • ad hoc to paper The VFT and parabolic functional forms correctly describe tau_MD(T) below the lowest directly simulated temperature down to T=0.29.
    This extrapolation is the basis for the claimed maximum speedup; its validity is assumed rather than tested.
  • domain assumption The criterion tau_MD(Tg)/tau_0 = 10^12 defines the experimental glass-transition temperature.
    A common convention in the field, used also in the standard Swap MC papers; it enters the Tg estimates in Section II.
  • domain assumption The shifted-force Lennard-Jones potential with Lorentz-Berthelot mixing rules provides an adequate representation of the molecular interactions for studying supercooled dynamics.
    Model choice adopted from Refs. 53-55; all reported results are conditional on this interaction model.

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Cite this review

Pith. "Pith review of Swap Monte Carlo for diatomic molecules." pith.science (2026). https://pith.science/paper/CZGRSGJ7

@misc{pith2026250415238,
  author       = {Pith},
  title        = {Pith review of: Swap Monte Carlo for diatomic molecules},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/CZGRSGJ7}},
  note         = {Machine review of arXiv:2504.15238}
}
read the original abstract

In recent years the Swap Monte Carlo algorithm has led to remarkable progress in equilibrating supercooled model liquids at low temperatures. Applications have so far been limited to systems composed of spherical particles, however, whereas most real-world supercooled liquids are molecular. We here introduce a simple size-polydisperse molecular model that allows for efficient thermal equilibration in silico with the Swap Monte Carlo method, resulting in an estimated speedup of 1,000-1,000,000 at moderate polydispersity (5-10%). The model exhibits little difference between size-resolved orientational time-autocorrelation functions.

Figures

Figures reproduced from arXiv: 2504.15238 by the authors.

Figure 1
Figure 1. FIG. 1. (a) Particle-size distribution of the investigated systems with polydispersities [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2. (a) Rotational relaxation times [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. FIG. 3. Confirming that the configurations obtained from the equilibration procedure using Swap are equilibrium configurations. [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figures from the paper (5 more)
Figure 4
Figure 4. Figure 4: FIG. 4. (a) and (b): Size-resolved orientational time-autocorrelation functions from standard MD simulations for [PITH_FULL_IMAGE:figures/full_fig_p004_4.png]
Figure 5
Figure 5. Figure 5: FIG. 5. Equilibration following the removal of size-polydispersity for [PITH_FULL_IMAGE:figures/full_fig_p007_5.png]
Figure 6
Figure 6. Figure 6: FIG. 6. Intermediate scattering function [PITH_FULL_IMAGE:figures/full_fig_p008_6.png]
Figure 7
Figure 7. Figure 7: FIG. 7. First-order orientational autocorrelation function [PITH_FULL_IMAGE:figures/full_fig_p008_7.png]
Figure 8
Figure 8. Figure 8: FIG. 8. Average equilibrium acceptance rate for molecule swaps as a function of temperature for 5% and 10% polydispersity. [PITH_FULL_IMAGE:figures/full_fig_p009_8.png]

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Works this paper leans on

67 extracted references · 67 canonical work pages

  1. [1]

    The nature of the glassy state and the behavior of liquids at low temperatures,

    W. Kauzmann, “The nature of the glassy state and the behavior of liquids at low temperatures,” Chem. Rev.43, 219–256 (1948)

    work page 1948

  2. [2]

    Harrison, The Dynamic Properties of Supercooled Liquids (Academic, New York, 1976)

    G. Harrison, The Dynamic Properties of Supercooled Liquids (Academic, New York, 1976)

    work page 1976

  3. [3]

    Formation of glasses from liquids and biopolymers,

    C. A. Angell, “Formation of glasses from liquids and biopolymers,” Science267, 1924–1935 (1995)

    work page 1995

  4. [4]

    Supercooled liquids and the glass transition,

    P. G. Debenedetti and F. H. Stillinger, “Supercooled liquids and the glass transition,” Nature410, 259–267 (2001)

    work page 2001

  5. [5]

    The glass transition and elastic models of glass-forming liquids,

    J. C. Dyre, “The glass transition and elastic models of glass-forming liquids,” Rev. Mod. Phys.78, 953–972 (2006)

    work page 2006

  6. [6]

    Theoretical perspective on the glass transition and amorphous materials,

    L. Berthier and G. Biroli, “Theoretical perspective on the glass transition and amorphous materials,” Rev. Mod. Phys.83, 587–645 (2011)

    work page 2011

  7. [7]

    The physics of the colloidal glass transition,

    G. L. Hunter and E. R. Weeks, “The physics of the colloidal glass transition,” Rep. Prog. Phys.75, 066501 (2012)

    work page 2012

  8. [8]

    Supercooled liquids and glasses by dielectric relaxation spectroscopy,

    R. Richert, “Supercooled liquids and glasses by dielectric relaxation spectroscopy,” Adv. Chem. Phys.156, 101–195 (2015)

    work page 2015

Show all 67 references
  1. [9]

    J. C. Mauro, Materials Kinetics: Transport and Rate Phenomena (Elsevier, Amsterdan, Netherlands, 2021)

    2021

  2. [10]

    A perspective on the fragility of glass-forming liquids,

    C. Alba-Simionesco and G. Tarjus, “A perspective on the fragility of glass-forming liquids,” J. Non-Cryst. Solids X14, 100100 (2022)

    2022

  3. [11]

    Perspective: Highly stable vapor-deposited glasses,

    M. D. Ediger, “Perspective: Highly stable vapor-deposited glasses,” J. Chem. Phys.147, 210901 (2017)

    2017

  4. [12]

    Modern computational studies of the glass transition,

    Ludovic Berthier and David R Reichman, “Modern computational studies of the glass transition,” Nat. Phys. Rev.5, 102–116 (2023)

    2023

  5. [13]

    Fast Monte Carlo algorithm for supercooled soft spheres,

    Tomás S. Grigera and Giorgio Parisi, “Fast Monte Carlo algorithm for supercooled soft spheres,” Phys. Rev. E63, 045102 (2001)

    2001

  6. [14]

    Numerical investigation of the entropy crisis in model glass formers,

    Yisroel Brumer and David R. Reichman, “Numerical investigation of the entropy crisis in model glass formers,” J. Phys. Chem. B 108, 6832–6837 (2004)

    2004

  7. [15]

    Critical behavior of the specific heat in glass formers,

    L. A. Fernández, V. Martín-Mayor, and P. Verrocchio, “Critical behavior of the specific heat in glass formers,” Phys. Rev. E 73, 020501 (2006)

    2006

  8. [16]

    Phase diagram of a polydisperse soft-spheres model for liquids and colloids,

    L. A. Fernández, V. Martín-Mayor, and P. Verrocchio, “Phase diagram of a polydisperse soft-spheres model for liquids and colloids,” Phys. Rev. Lett.98, 085702 (2007)

    2007

  9. [17]

    Dynamic relaxation of a liquid cavity under amorphous boundary conditions,

    Andrea Cavagna, Tomás S. Grigera, and Paolo Verrocchio, “Dynamic relaxation of a liquid cavity under amorphous boundary conditions,” J. Chem. Phys.136, 204502 (2012)

    2012

  10. [18]

    The static lengthscale characterizing the glass transition at lower temperatures,

    R. Gutiérrez, S. Karmakar, Y. G. Pollack, and I. Procaccia, “The static lengthscale characterizing the glass transition at lower temperatures,” Europhys. Lett.111, 56009 (2015)

    2015

  11. [19]

    Models and algorithms for the next generation of glass transition studies,

    Andrea Ninarello, Ludovic Berthier, and Daniele Coslovich, “Models and algorithms for the next generation of glass transition studies,” Phys. Rev. X7, 021039 (2017)

    2017

  12. [20]

    Efficient swap algorithms for molecular dynamics simulations of equilibrium supercooled liquids,

    Ludovic Berthier, Elijah Flenner, Christopher J Fullerton, Camille Scalliet, and Murari Singh, “Efficient swap algorithms for molecular dynamics simulations of equilibrium supercooled liquids,” J. Stat. Mech.:Theory Exp.2019, 064004 (2019)

    2019

  13. [21]

    Ultrastable metallic glasses in silico,

    Anshul D. S. Parmar, Misaki Ozawa, and Ludovic Berthier, “Ultrastable metallic glasses in silico,” Phys. Rev. Lett.125, 085505 (2020). 10

    2020

  14. [22]

    Understanding the swap Monte Carlo algorithm in a size-polydisperse model glass- former,

    Niklas Küchler and Jürgen Horbach, “Understanding the swap Monte Carlo algorithm in a size-polydisperse model glass- former,” Phys. Rev. E108, 024127 (2023)

    2023

  15. [23]

    Replica-exchange molecular dynamics simulation for supercooled liquids,

    Ryoichi Yamamoto and Walter Kob, “Replica-exchange molecular dynamics simulation for supercooled liquids,” Phys. Rev. E 61, 5473–5476 (2000)

    2000

  16. [24]

    Exchange Monte Carlo method and application to spin glass simulations,

    Koji Hukushima and Koji Nemoto, “Exchange Monte Carlo method and application to spin glass simulations,” J. Phys. Soc. Jpn. 65, 1604–1608 (1996)

    1996

  17. [25]

    Johari–Goldsteinβ relaxation in glassy dynamics originates from two-scale energy landscape,

    K. Shiraishi, H. Mizuno, and A. Ikeda, “Johari–Goldsteinβ relaxation in glassy dynamics originates from two-scale energy landscape,” PNAS 120, e2215153120 (2023)

    2023

  18. [26]

    Creating bulk ultrastable glasses by random particle bonding,

    Misaki Ozawa, Yasutaka Iwashita, Walter Kob, and Francesco Zamponi, “Creating bulk ultrastable glasses by random particle bonding,” Nat. Comm.14, 113 (2023)

    2023

  19. [27]

    Generating ultrastable glasses by homogenizing the local virial stress,

    F. Leoni, J. Russo, F. Sciortino, and T. Yanagishima, “Generating ultrastable glasses by homogenizing the local virial stress,” Phys. Rev. Lett.134, 128201 (2025)

    2025

  20. [28]

    Stable glassy configurations of the Kob–Andersen model using swap Monte Carlo,

    Anshul D. S. Parmar, Benjamin Guiselin, and Ludovic Berthier, “Stable glassy configurations of the Kob–Andersen model using swap Monte Carlo,” J. Chem. Phys.153, 134505 (2020)

    2020

  21. [29]

    Fast Monte Carlo algorithm for supercooled soft spheres,

    T. S. Grigera and G. Parisi, “Fast Monte Carlo algorithm for supercooled soft spheres,” Phys. Rev. E63, 045102 (2001)

    2001

  22. [30]

    Self-induced heterogeneity in deeply supercooled liquids,

    Ludovic Berthier, “Self-induced heterogeneity in deeply supercooled liquids,” Phys. Rev. Lett.127, 088002 (2021)

    2021

  23. [31]

    Dynamic heterogeneity at the experimental glass transition predicted by transferable machine learning,

    Gerhard Jung, Giulio Biroli, and Ludovic Berthier, “Dynamic heterogeneity at the experimental glass transition predicted by transferable machine learning,” Phys. Rev. B109, 064205 (2024)

    2024

  24. [32]

    Thirty milliseconds in the life of a supercooled liquid,

    Camille Scalliet, Benjamin Guiselin, and Ludovic Berthier, “Thirty milliseconds in the life of a supercooled liquid,” Phys. Rev. X 12, 041028 (2022)

    2022

  25. [33]

    Microscopic origin of excess wings in relaxation spectra of supercooled liquids,

    Benjamin Guiselin, Camille Scalliet, and Ludovic Berthier, “Microscopic origin of excess wings in relaxation spectra of supercooled liquids,” Nat. Phys.18, 468–472 (2022)

    2022

  26. [34]

    Direct numerical analysis of dynamic facilitation in glass-forming liquids,

    Cecilia Herrero and Ludovic Berthier, “Direct numerical analysis of dynamic facilitation in glass-forming liquids,” Phys. Rev. Lett. 132, 258201 (2024)

    2024

  27. [35]

    Random critical point separates brittle and ductile yielding transitions in amorphous materials,

    Misaki Ozawa, Ludovic Berthier, Giulio Biroli, Alberto Rosso, and Gilles Tarjus, “Random critical point separates brittle and ductile yielding transitions in amorphous materials,” Proc. Natl. Acad. Sci. U.S.A.115, 6656–6661 (2018)

    2018

  28. [36]

    Predicting plasticity in disordered solids from structural indicators,

    D. Richard, M. Ozawa, S. Patinet, E. Stanifer, B. Shang, S. A. Ridout, B. Xu, G. Zhang, P. K. Morse, J.-L. Barrat, L. Berthier, M. L. Falk, P. Guan, A. J. Liu, K. Martens, S. Sastry, D. Vandembroucq, E. Lerner, and M. L. Manning, “Predicting plasticity in disordered solids fro...

    2020

  29. [37]

    Brittle yielding of amorphous solids at finite shear rates,

    Murari Singh, Misaki Ozawa, and Ludovic Berthier, “Brittle yielding of amorphous solids at finite shear rates,” Phys. Rev. Mater. 4, 025603 (2020)

    2020

  30. [38]

    Glass stability changes the nature of yielding under oscillatory shear,

    Wei-Ting Yeh, Misaki Ozawa, Kunimasa Miyazaki, Takeshi Kawasaki, and Ludovic Berthier, “Glass stability changes the nature of yielding under oscillatory shear,” Phys. Rev. Lett.124, 225502 (2020)

    2020

  31. [39]

    Brittle yielding in supercooled liquids below the critical tem- perature of mode coupling theory,

    Konstantin Lamp, Niklas Küchler, and Jürgen Horbach, “Brittle yielding in supercooled liquids below the critical tem- perature of mode coupling theory,” J. Chem. Phys.157, 034501 (2022)

    2022

  32. [40]

    Rare events and disorder control the brittle yielding of well-annealed amorphous solids,

    Misaki Ozawa, Ludovic Berthier, Giulio Biroli, and Gilles Tarjus, “Rare events and disorder control the brittle yielding of well-annealed amorphous solids,” Phys. Rev. Res.4, 023227 (2022)

    2022

  33. [41]

    Local vs. cooperative: Unraveling glass transition mecha- nisms with seer,

    Massimo Pica Ciamarra, Wencheng Ji, and Matthieu Wyart, “Local vs. cooperative: Unraveling glass transition mecha- nisms with seer,” Proc. Natl. Acad. Sci. U.S.A.121, e2400611121 (2024)

    2024

  34. [42]

    Low-frequency vibrational modes of stable glasses,

    Lijin Wang, Andrea Ninarello, Pengfei Guan, Ludovic Berthier, Grzegorz Szamel, and Elijah Flenner, “Low-frequency vibrational modes of stable glasses,” Nat. Comm.10, 26 (2019)

    2019

  35. [43]

    Low-frequency vibrational density of states of ordinary and ultra-stable glasses,

    Ding Xu, Shiyun Zhang, Hua Tong, Lijin Wang, and Ning Xu, “Low-frequency vibrational density of states of ordinary and ultra-stable glasses,” Nat. Comm.15, 1424 (2024)

    2024

  36. [44]

    Two-step devitrification of ultrastable glasses,

    Cecilia Herrero, Camille Scalliet, M. D. Ediger, and Ludovic Berthier, “Two-step devitrification of ultrastable glasses,” Proc. Natl. Acad. Sci. U.S.A.120, e2220824120 (2023)

    2023

  37. [45]

    Dynamical facilitation governs the equilibration dynamics of glasses,

    Rahul N. Chacko, François P. Landes, Giulio Biroli, Olivier Dauchot, Andrea J. Liu, and David R. Reichman, “Dynamical facilitation governs the equilibration dynamics of glasses,” Phys. Rev. X14, 031012 (2024)

    2024

  38. [46]

    Front propagation in ultrastable glasses is dynamically heteroge- neous,

    Cecilia Herrero, Mark D Ediger, and Ludovic Berthier, “Front propagation in ultrastable glasses is dynamically heteroge- neous,” J. Chem. Phys.159, 114504 (2023)

    2023

  39. [47]

    Glassy dynamics,

    P. Lunkenheimer, U. Schneider, R. Brand, and A. Loid, “Glassy dynamics,” Contemp. Phys.41, 15–36 (2000)

    2000

  40. [48]

    Friedrich Kremer and Alois Loidl,The scaling of relaxation processes (Springer, 2018)

    2018

  41. [49]

    On the spectral shape of the structural relaxation in supercooled liquids,

    T. Böhmer, F. Pabst, J. P. Gabriel, R. Zeißler, and T. Blochowicz, “On the spectral shape of the structural relaxation in supercooled liquids,” J. Chem. Phys.162, 120902 (2025)

    2025

  42. [50]

    Influence of polydispersity on the relaxation mechanisms of glassy liquids,

    Ilian Pihlajamaa, Corentin C. L. Laudicina, and Liesbeth M. C. Janssen, “Influence of polydispersity on the relaxation mechanisms of glassy liquids,” Phys. Rev. Res.5, 033120 (2023)

    2023

  43. [51]

    M. P. Allen and D. J. Tildesley,Computer Simulation of Liquids (Oxford Science Publications (Oxford), 1987)

    1987

  44. [52]

    Communication: Shifted forces in molecular dynamics,

    S. Toxvaerd and J. C. Dyre, “Communication: Shifted forces in molecular dynamics,” J. Chem. Phys.134, 081102 (2011)

    2011

  45. [53]

    Feasibility of a Single-Parameter Description of Equi- librium Viscous Liquid Dynamics,

    U. R. Pedersen, T. Christensen, T. B. Schrøder, and J. C. Dyre, “Feasibility of a Single-Parameter Description of Equi- librium Viscous Liquid Dynamics,” Phys. Rev. E77, 011201 (2008)

    2008

  46. [54]

    Hidden Scale Invariance in Molecular van der Waals Liquids: A Simulation Study,

    T. B. Schrøder, U. R. Pedersen, N. P. Bailey, S. Toxvaerd, and J. C. Dyre, “Hidden Scale Invariance in Molecular van der Waals Liquids: A Simulation Study,” Phys. Rev. E80, 041502 (2009)

    2009

  47. [55]

    Isomorphs in model molecular liquids,

    T. S. Ingebrigtsen, T. B. Schrøder, and J. C. Dyre, “Isomorphs in model molecular liquids,” J. Phys. Chem. B116, 1018–1034 (2012). 11

    2012

  48. [56]

    Choiceofdiametersinapolydispersemodelglassformer: Deterministicorstochastic?

    NiklasKüchlerandJürgenHorbach,“Choiceofdiametersinapolydispersemodelglassformer: Deterministicorstochastic?” Phys. Rev. E106, 064103 (2022)

    2022

  49. [57]

    GAMDpy: GPU Accelerated Molecular Dynamics in Python,https://github.com/ThomasBechSchroeder/gamdpy (2025)

    2025

  50. [58]

    RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles,

    N. P. Bailey, T. S. Ingebrigtsen, J. S. Hansen, A. A. Veldhorst, L. Bøhling, C. A. Lemarchand, A. E. Olsen, A. K. Bacher, L. Costigliola, U. R. Pedersen, H. Larsen, J. C. Dyre, and T. B. Schrøder, “RUMD: A general purpose molecular dynamics package optimized to utilize GPU har...

    2017

  51. [59]

    Das temperaturabhangigkeitsgesetz der viskositat von flussigkeiten,

    Hans Vogel, “Das temperaturabhangigkeitsgesetz der viskositat von flussigkeiten,” Phys. Z.22, 645–646 (1921)

    1921

  52. [60]

    Corresponding states of structural glass formers,

    Yael S. Elmatad, David Chandler, and Juan P. Garrahan, “Corresponding states of structural glass formers,” J. Phys. Chem. B 113, 5563–5567 (2009)

    2009

  53. [61]

    Aging effects in a Lennard-Jones glass,

    Walter Kob and Jean-Louis Barrat, “Aging effects in a Lennard-Jones glass,” Phys. Rev. Lett.78, 4581–4584 (1997)

    1997

  54. [62]

    Time reversibility during the ageing of materials,

    T. Böhmer, J. P. Gabriel, L. Costigliola, J.-N. Kociok, T. Hecksher, J. C. Dyre, and T. Blochowicz, “Time reversibility during the ageing of materials,” Nat. Phys.20, 637–648 (2024)

    2024

  55. [63]

    Statistical complexity of potential energy landscape as a dynamic signature of the glass transition,

    Dong Han, Dan Wei, Peng-Hui Cao, Yun-Jiang Wang, and Lan-Hong Dai, “Statistical complexity of potential energy landscape as a dynamic signature of the glass transition,” Phys. Rev. B101, 064205 (2020)

    2020

  56. [64]

    NVU view on energy polydisperse Lennard-Jones systems,

    D. Lang, L. Costigliola, and J. C. Dyre, “NVU view on energy polydisperse Lennard-Jones systems,” Phys. Rev. E111, 025420 (2025)

    2025

  57. [65]

    A model for the generic alpha relaxation of viscous liquids,

    J. C. Dyre, “A model for the generic alpha relaxation of viscous liquids,” Europhys. Lett.71, 646–650 (2005)

    2005

  58. [66]

    Solidity of viscous liquids. IV. Density fluctuations,

    J. C. Dyre, “Solidity of viscous liquids. IV. Density fluctuations,” Phys. Rev. E74, 021502 (2006)

    2006

  59. [67]

    Prevalence of approximate√ t relaxation for the dielectricα process in viscous organic liquids,

    A. I. Nielsen, T. Christensen, B. Jakobsen, K. Niss, N. B. Olsen, R. Richert, and J. C. Dyre, “Prevalence of approximate√ t relaxation for the dielectricα process in viscous organic liquids,” J. Chem. Phys.130, 154508 (2009)

    2009

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Reviewed August 16, 2026 · model on record in the stance chip above.