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1. Statistics of thermal avalanches in driven amorphous systems

   https://doi.org/10.1063/5.0330828  

   Cao, Zhiyu; Wolynes, Peter G (April 2026, The Journal of Chemical Physics)

   Within the framework of the random first-order transition theory of glasses, we discuss the statistics of “thermal avalanches,” the large scale rearrangements in driven amorphous systems near their instability. Stringy excitations yield non-Poisson waiting-time statistics. Embedding these statistics in a generalized master equation captures the non-Markovian, aging dynamics of avalanche clusters. We apply this framework to analyze nonequilibrium signatures of thermal avalanches—auto-correlation functions and effective temperatures—under both quasi-static shear and stochastic shaking protocols. We use full counting statistics to derive the complete distribution of both the avalanche magnitudes and avalanche counts, uncovering the intermediate-time behavior. 

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2. Many-Body Resonances in the Avalanche Instability of Many-Body Localization

   https://doi.org/10.1103/PhysRevLett.130.250405  

   Ha, Hyunsoo; Morningstar, Alan; Huse, David A. (June 2023, Physical Review Letters)

   Many-body localized (MBL) systems fail to reach thermal equilibrium under their own dynamics, even though they are interacting, nonintegrable, and in an extensively excited state. One instability toward thermalization of MBL systems is the so-called “avalanche,” where a locally thermalizing rare region is able to spread thermalization through the full system. The spreading of the avalanche may be modeled and numerically studied in finite one-dimensional MBL systems by weakly coupling an infinite-temperature bath to one end of the system. We find that the avalanche spreads primarily via strong many-body resonances between rare near-resonant eigenstates of the closed system. Thus we find and explore a detailed connection between many-body resonances and avalanches in MBL systems. 

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3. Avalanche scaling in large neural populations with distributed coupling to multiple dynamical latent variables

   Morrell, Mia C.; Nemenman, Ilya; Sederberg, Audrey J. (January 2023, arXiv)

   Observations of power laws in neural activity data have raised the intriguing notion that brains may operate in a critical state. One example of this critical state is "avalanche criticality," which has been observed in a range of systems, including cultured neurons, zebrafish, and human EEG. More recently, power laws have also been observed in neural populations in the mouse under a coarse-graining procedure, and they were explained as a consequence of the neural activity being coupled to multiple latent dynamical variables. An intriguing possibility is that avalanche criticality emerges due to a similar mechanism. Here, we determine the conditions under which dynamical latent variables give rise to avalanche criticality. We find that a single, quasi-static latent variable can generate critical avalanches, but that multiple latent variables lead to critical behavior in a broader parameter range. We identify two regimes of avalanches, both of which are critical, but differ in the amount of information carried about the latent variable. Our results suggest that avalanche criticality arises in neural systems in which there is an emergent dynamical variable or shared inputs creating an effective latent dynamical variable, and when this variable can be inferred from the population activity. 

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4. Microscopic dynamics underlying the stress relaxation of arrested soft materials

   https://doi.org/10.1073/pnas.2201566119  

   Song, Jake; Zhang, Qingteng; de Quesada, Felipe; Rizvi, Mehedi H.; Tracy, Joseph B.; Ilavsky, Jan; Narayanan, Suresh; Del Gado, Emanuela; Leheny, Robert L.; Holten-Andersen, Niels; et al (July 2022, Proceedings of the National Academy of Sciences)

   Arrested soft materials such as gels and glasses exhibit a slow stress relaxation with a broad distribution of relaxation times in response to linear mechanical perturbations. Although this macroscopic stress relaxation is an essential feature in the application of arrested systems as structural materials, consumer products, foods, and biological materials, the microscopic origins of this relaxation remain poorly understood. Here, we elucidate the microscopic dynamics underlying the stress relaxation of such arrested soft materials under both quiescent and mechanically perturbed conditions through X-ray photon correlation spectroscopy. By studying the dynamics of a model associative gel system that undergoes dynamical arrest in the absence of aging effects, we show that the mean stress relaxation time measured from linear rheometry is directly correlated to the quiescent superdiffusive dynamics of the microscopic clusters, which are governed by a buildup of internal stresses during arrest. We also show that perturbing the system via small mechanical deformations can result in large intermittent fluctuations in the form of avalanches, which give rise to a broad non-Gaussian spectrum of relaxation modes at short times that is observed in stress relaxation measurements. These findings suggest that the linear viscoelastic stress relaxation in arrested soft materials may be governed by nonlinear phenomena involving an interplay of internal stress relaxations and perturbation-induced intermittent avalanches. 

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5. Origin of yield stress and mechanical plasticity in model biological tissues

   https://doi.org/10.1038/s41467-025-58526-7  

   Nguyen, Anh Q; Huang, Junxiang; Bi, Dapeng (December 2025, Nature Communications)

   During development and under normal physiological conditions, biological tissues are continuously subjected to substantial mechanical stresses. In response to large deformations, cells in a tissue must undergo multicellular rearrangements to maintain integrity and robustness. However, how these events are connected in time and space remains unknown. Here, using theoretical modeling, we study the mechanical plasticity of cell monolayers under large deformations. Our results suggest that the jamming-unjamming (solid-fluid) transition can vary significantly depending on the degree of deformation, implying that tissues are highly unconventional materials. We elucidate the origins of this behavior. We also demonstrate how large deformations are accommodated through a series of cellular rearrangements, similar to avalanches in non-living materials. We find that these ‘tissue avalanches’ are governed by stress redistribution and the spatial distribution of “soft” or vulnerable spots, which are more prone to undergo rearrangements. Finally, we propose a simple and experimentally accessible framework to infer tissue-level stress and predict avalanches based on static images. 

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