Statistical physics articles within Nature Communications

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  • Article
    | Open Access

    Inertial active matter can self-organize into coexisting phases that feature different temperatures, but experimental realizations are limited. Here, the authors report the coexistence of hot liquid and cold gas states in mixtures of overdamped active and inertial passive Brownian particles, giving a broader relevance.

    • Lukas Hecht
    • , Iris Dong
    •  & Benno Liebchen

  • Article
    | Open Access

    The frequency scaling exponent of low-frequency vibrational excitations in glasses remains controversial in the literature. Here, Schirmacher et al. show that the exponent depends on the statistics of the small values of the local stresses, which is governed by the detail of interaction potential.

    • Walter Schirmacher
    • , Matteo Paoluzzi
    •  & Giancarlo Ruocco

  • Article
    | Open Access

    Active matter systems, such as zebrafish groups, demonstrate similar collective dynamics to assemblies of particles, or interacting agents. The authors show that majority of dynamics patterns seen in large zebrafish groups are exhibited by a minimal group of three fish.

    • Alexandra Zampetaki
    • , Yushi Yang
    •  & C. Patrick Royall

  • Article
    | Open Access

    Studying bounds on the speed of information propagation across interacting boson systems is notoriously difficult. Here, the authors find tight bounds for both the transport of boson particles and information propagation, for arbitrary time-dependent Bose-Hubbard-type Hamiltonians in arbitrary dimensions.

    • Tomotaka Kuwahara
    • , Tan Van Vu
    •  & Keiji Saito

  • Article
    | Open Access

    The authors propose a generalization of the equipartition theorem of thermal physics to account for non-Hermitian trapping forces, relevant for the problems in non-equilibrium open systems and advanced nanotechnology.

    • Xiao Li
    • , Yongyin Cao
    •  & Jack Ng

  • Article
    | Open Access

    Learning the dynamics governing a simulation or experiment usually requires coarse graining or projection, as the number of transition rates typically grows exponentially with system size. The authors show that transformers, neural networks introduced initially for natural language processing, can be used to parameterize the dynamics of large systems without coarse graining.

    • Corneel Casert
    • , Isaac Tamblyn
    •  & Stephen Whitelam

  • Article
    | Open Access

    Variational autoregressive networks have been employed in the study of equilibrium statistical mechanics, chemical reaction networks and quantum many-body systems. Using these tools, Tang et al. develop a general approach to nonequilibrium statistical mechanics problems, such as dynamical phase transitions.

    • Ying Tang
    • , Jing Liu
    •  & Pan Zhang

  • Article
    | Open Access

    Periodically driven quantum systems have been extensively studied but with a predominant focus on long-time dynamics. Here, the authors study short-to-intermediate-time dynamics of an isolated many-body system, showing that its response to driving is supressed for the initial state close to thermal equilibrium.

    • Lennart Dabelow
    •  & Peter Reimann

  • Article
    | Open Access

    Predicting the effective assembly of a set of proteins into a desired structure has traditionally been a challenging task. Here, authors demonstrate that advancements in automatic differentiation make it possible to address this problem using classical statistical mechanics.

    • Agnese I. Curatolo
    • , Ofer Kimchi
    •  & Michael P. Brenner

  • Article
    | Open Access

    Grain boundary atomic structures of crystalline materials have long been believed to be commensurate with the crystal periodicity of the adjacent crystals. Here, the authors discover an incommensurate grain boundary structure based on direct observations and theoretical calculations.

    • Takehito Seki
    • , Toshihiro Futazuka
    •  & Naoya Shibata

  • Article
    | Open Access

    Heavy traffic jams are difficult to predict due to the complexity of traffic dynamics. The authors propose a framework to unveil identifiable early signals and predict the eventual outcome of traffic bottlenecks, which may be useful for designing effective methods preventing traffic jams.

    • Jinxiao Duan
    • , Guanwen Zeng
    •  & Shlomo Havlin

  • Article
    | Open Access

    Packing a finite number of spheres in a compact cluster does not always result in the densest packing. Here, the authors provide a physical realization of the finite sphere packing problem by enclosing colloids in a flaccid lipid vesicle and mapping out a state diagram that displays linear, planar, and cluster conformations of spheres, as well as bistable states that alternate between cluster-plate and plate-linear conformations.

    • Susana Marín-Aguilar
    • , Fabrizio Camerin
    •  & Marjolein Dijkstra

  • Article
    | Open Access

    Non-reciprocal interactions (NRI) are ubiquitous in active systems, but, in the presence of NRI, it is difficult to predict which microscopic systems correspond to a given macroscopic description. Dinelli et al. relate microscopic and macroscopic dynamics of active mixtures and show that non-reciprocity strongly depends on the scale of description.

    • Alberto Dinelli
    • , Jérémy O’Byrne
    •  & Julien Tailleur

  • Article
    | Open Access

    The trade-off between power and efficiency in designing heat engines has remained unsolved for the last two centuries. The authors overcome this trade-off in a colloidal Stirling engine by electrophoretically inducing system-reservoir interactions to enhance heat transfer during an isochoric process.

    • Sudeesh Krishnamurthy
    • , Rajesh Ganapathy
    •  & A. K. Sood

  • Article
    | Open Access

    Record ages characterise rare and extreme events in stochastic processes, however, their evaluation is challenging when interaction with environment and memory effects are present in the random walk. The authors determine the statistics of record ages for a broad class of non-Markovian random walks and reveal their general features.

    • Léo Régnier
    • , Maxim Dolgushev
    •  & Olivier Bénichou

  • Article
    | Open Access

    Whether stick-slip instabilities can give rise to avalanches of slip lengths is an outstanding issue in solid friction. Here, the authors demonstrated that there indeed exists a critical regime in which stick-slip friction can be described by a common set of statistical laws of avalanche dynamics.

    • Caishan Yan
    • , Hsuan-Yi Chen
    •  & Penger Tong

  • Article
    | Open Access

    What is the physical limit on entropy production in a suspension of active microswimmers? In answer to this question, the authors derive a general theorem that provides an exact lower bound on the total, external and internal dissipation by a microswimmer and apply it to optimize swimmer shapes.

    • Abdallah Daddi-Moussa-Ider
    • , Ramin Golestanian
    •  & Andrej Vilfan

  • Article
    | Open Access

    Many-body localized systems are believed to reach a stationary state without thermalizing. By using analytical and numerical calculations, the authors construct simple initial states for a typical MBL model, which neither equilibrate nor thermalize, similar to non-ergodic behavior in many-body scarred systems.

    • Henrik Wilming
    • , Tobias J. Osborne
    •  & Christoph Karrasch

  • Article
    | Open Access

    It is generally accepted that non-equilibrium conditions would have been necessary for the formation of primitive metabolic structures, but the focus has mostly been on externally imposed non-equilibrium conditions. Here, the authors show that catalytically active particles like enzymes participating in a metabolic cycle can spontaneously self-organize into dynamically structured condensates composed of active mixtures, by employing non-reciprocal interactions.

    • Vincent Ouazan-Reboul
    • , Jaime Agudo-Canalejo
    •  & Ramin Golestanian

  • Article
    | Open Access

    The mechanical forces exerted by active fluids may provide an effective way of transporting microscopic objects, but the details remain elusive. Using space modulated activity, Pellicciotta et al. generate active pressure gradients capable of transporting passive particles in controlled directions.

    • Nicola Pellicciotta
    • , Matteo Paoluzzi
    •  & Roberto Di Leonardo

  • Article
    | Open Access

    The Sherrington-Kirkpatrick model is a paradigmatic model in the field of complex disordered systems such as spin glasses and neural networks. Here the authors study the stochastic thermodynamics of an asymmetric version of the model by using a path integral method and provide exact solutions for the entropy production.

    • Miguel Aguilera
    • , Masanao Igarashi
    •  & Hideaki Shimazaki

  • Article
    | Open Access

    Out-of-time-ordered correlators of local operators can quantify information scrambling in quantum many-body systems, but they are not easily accessible in experiments. Here the authors show that their global versions can be used for the same purpose and has been measured in nuclear magnetic resonance experiments.

    • Tianci Zhou
    •  & Brian Swingle

  • Article
    | Open Access

    Active field theories are powerful tools to explain phenomena such as motility-induced phase separation. The authors report an active analogue to the quantum mechanics tunneling effect, showing similarity to the Schrödinger equation, by introducing an extended model applicable to active particles with inertia.

    • Michael te Vrugt
    • , Tobias Frohoff-Hülsmann
    •  & Raphael Wittkowski

  • Article
    | Open Access

    In the quest to understand how deep neural networks work, identification of slow and fast variables is a desirable step. Inspired by tools from theoretical physics, the authors propose a simplified description of finite deep neural networks based on two matrix variables per layer and provide analytic predictions for feature learning effects.

    • Inbar Seroussi
    • , Gadi Naveh
    •  & Zohar Ringel

  • Article
    | Open Access

    Finding the ground states of spin glasses relevant for disordered magnets and many other physical systems is computationally challenging. The authors propose here a deep reinforcement learning framework for calculating the ground states, which can be trained on small-scale spin glass instances and then applied to arbitrarily large ones.

    • Changjun Fan
    • , Mutian Shen
    •  & Yang-Yu Liu

  • Article
    | Open Access

    Random walks are usually characterized by the spatial territory they cover, described by the number of sites visited at a given time. Here the authors propose an approach that accounts the time between visits to distinct sites, for improved analysis of the exploration process for general random walks, including the case of anomalous diffusion in disordered media.

    • Léo Régnier
    • , Maxim Dolgushev
    •  & Olivier Bénichou

  • Article
    | Open Access

    Viable methods for the production of ultrastable glasses are much sought after. A potential approach for creating bulk ultrastable glasses, based on random particle bonding scenarios, is now numerically investigated. The method is expected to be applicable to molecular and colloidal glasses.

    • Misaki Ozawa
    • , Yasutaka Iwashita
    •  & Francesco Zamponi

  • Article
    | Open Access

    Time-delayed interactions involving perception, decision, and reaction, are omnipresent in the living world. Here, the delayed self-propulsion of a microswimmer toward a target gives rise to chiral orbital motion via a symmetry-breaking bifurcation. Additional swimmers synchronize and stabilize it.

    • Xiangzun Wang
    • , Pin-Chuan Chen
    •  & Frank Cichos

  • Article
    | Open Access

    Some quantum spin models provide a condensed-matter realization of confinement, and previous work has shown that confinement affects the way they thermalize. Here the authors demonstrate for a many-body model with confinement that thermalization dynamics occurs in multiple stages, starting with a prethermal state.

    • Stefan Birnkammer
    • , Alvise Bastianello
    •  & Michael Knap

  • Article
    | Open Access

    Getting a grip on the chaotic properties of quantum systems is difficult. Now, the effect of translational invariance in space in time in an ensemble of random quantum circuits is shown to lead to largely universal scaling laws describing the system without the need of knowing microscopic details.

    • Amos Chan
    • , Saumya Shivam
    •  & Andrea De Luca

  • Article
    | Open Access

    Networks with higher-order interactions are known to provide better representation of real networked systems. Here the authors introduce a framework based on statistical inference to detect overlapping communities and predict hyperedges of any size in hypergraphs.

    • Martina Contisciani
    • , Federico Battiston
    •  & Caterina De Bacco

  • Article
    | Open Access

    Diffusive motions in complex environments such as living biological cells or soft matter systems can be analyzed with single-particle-tracking approaches, where accuracy of output may vary. The authors involve a machine-learning technique for decoding anomalous-diffusion data and provide an uncertainty estimate together with predicted output.

    • Henrik Seckler
    •  & Ralf Metzler

  • Article
    | Open Access

    Homeostasis of DNA density is a hallmark of living cells. The authors show via mathematical modelling how two cycles, a titration-based concentration cycle and a nucleotide activation cycle, together drive replication in E. coli at all growth rates.

    • Mareike Berger
    •  & Pieter Rein ten Wolde

  • Article
    | Open Access

    The melting process in glasses is not fully understood. Experiments with colloidal glasses now show that during melting, a liquid film develops at the surface, below which a region forms with highly mobile particles. This surface glassy layer reflects the properties of the surface and the underlying bulk material.

    • Li Tian
    •  & Clemens Bechinger

  • Article
    | Open Access

    A new study finds that city growth in the U.S. is spatially heterogeneous. Inter-city flows concentrate in core areas. Intra-city flows are generally directed towards external and low density counties of cities, and is the main contributor to urban sprawl.

    • Sandro M. Reia
    • , P. Suresh C. Rao
    •  & Satish V. Ukkusuri

  • Article
    | Open Access

    Dispersive transport through complex media, relevant for semiconductors, liquid crystals, and biological soft matter, is influenced by their microscopic, porous structure. The authors consider the statistics of pore-junction units, in contrast to individual pores, to link morphology and macroscopic transport characteristics.

    • Felix J. Meigel
    • , Thomas Darwent
    •  & Karen Alim

  • Article
    | Open Access

    The persistence of random walker can quantify the kinetics of transport limited reactions and predict the time to reach a target, but is challenging for non-stationary random processes with a large number of degrees of freedom. The authors introduce a method to determine the persistence exponent of random processes with general non-stationary dynamics.

    • N. Levernier
    • , T. V. Mendes
    •  & T. Guérin

  • Article
    | Open Access

    Contrary to states of thermal equilibrium, there is no universal characterization of non-equilibrium steady states displaying constant flows of energy and/or matter. Here, the authors make progress in this direction by deriving an emergent and stricter version of the second law of thermodynamics.

    • José Nahuel Freitas
    •  & Massimiliano Esposito

  • Article
    | Open Access

    Understanding how order emerges in active matter may facilitate macroscopic control of microscopic objects. Here, Williams et al. show how to control the transport of passive microscopic particles in presence of motile algae in conjunction with boundary-induced accumulation of microswimmers.

    • Stephen Williams
    • , Raphaël Jeanneret
    •  & Marco Polin

  • Article
    | Open Access

    The emergence of correlated and self-organized linear structures, known as force chains, is relevant for granular materials, foams, emulsions, and extreme active matter. The authors develop a machine learning-based approach to predict force chain formation in jammed disordered solids under deformation.

    • Rituparno Mandal
    • , Corneel Casert
    •  & Peter Sollich

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