Statistical physics, thermodynamics and nonlinear dynamics articles within Nature Communications

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  • Article
    | Open Access

    Megaripples are sand landforms found in wind-blown environments. A newly identified characteristic signature of the underlying bimodal sand transport process is found in the grain-size distribution on megaripples and could lend insight into transport conditions on Earth and other planetary bodies.

    • Katharina Tholen
    • , Thomas Pähtz
    •  & Klaus Kroy

  • Article
    | Open Access

    Thermal metamaterials can be used to manipulate heat flow but experimental fabrication is challenging. Here, the authors report robustly printable freeform thermal metamaterials to tackle this challenge by topology optimization and 3D printing.

    • Wei Sha
    • , Mi Xiao
    •  & Run Hu

  • Article
    | Open Access

    Navigation through porous environments poses a major challenge for swimming microorganisms and future microrobots. This study predicts that their spreading becomes optimal when their run length is comparable to the longest available pore length.

    • Christina Kurzthaler
    • , Suvendu Mandal
    •  & Howard A. Stone

  • Article
    | Open Access

    Generative models have become increasingly popular in protein design, yet rigorous metrics that allow the comparison of these models are lacking. Here, the authors propose a set of such metrics and use them to compare three popular models.

    • Francisco McGee
    • , Sandro Hauri
    •  & Allan Haldane

  • Article
    | Open Access

    Gradient-based and non-gradient-based methods for training neural networks are usually considered to be fundamentally different. The authors derive, and illustrate numerically, an analytic equivalence between the dynamics of neural network training under conditioned stochastic mutations, and under gradient descent.

    • Stephen Whitelam
    • , Viktor Selin
    •  & Isaac Tamblyn

  • Article
    | Open Access

    Deviations from Brownian motion leading to anomalous diffusion are ubiquitously found in transport dynamics but often difficult to characterize. Here the authors compare approaches for single trajectory analysis through an open competition, showing that machine learning methods outperform classical approaches.

    • Gorka Muñoz-Gil
    • , Giovanni Volpe
    •  & Carlo Manzo

  • Article
    | Open Access

    Experimental data obtained in single-particle tracking experiments are challenging to interpret. The authors propose an approach for determining the dynamics of the stochastic motion of molecules based on the power spectrum, relevant to various non-stationary scale-free random walks.

    • Zachary R. Fox
    • , Eli Barkai
    •  & Diego Krapf

  • Article
    | Open Access

    Active matter can spontaneously form complex patterns and assemblies via a one-way energy flow from the environment into the system. Here, the authors demonstrate that a two-way coupling, where active particles act back on the environment can give rise to novel superstructures, named as active droploids.

    • Jens Grauer
    • , Falko Schmidt
    •  & Benno Liebchen

  • Article
    | Open Access

    Langevin dynamics describe transient behavior of many complex systems, however, inferring Langevin equations from noisy data is challenging. The authors present an inference framework for non-stationary latent Langevin dynamics and test it on models of spiking neural activity during decision making.

    • Mikhail Genkin
    • , Owen Hughes
    •  & Tatiana A. Engel

  • Article
    | Open Access

    Superconductivity reported in metals driven away from equilibrium via optical pumping has been proposed to arise from nonlinear coupling between electrons and optically excited phonons. The authors use an exact approach to show that here, disorder, which disfavors superconductivity, emerges even though the system is translationally invariant.

    • John Sous
    • , Benedikt Kloss
    •  & Andrew J. Millis

  • Article
    | Open Access

    Social convention change due to diffusion is often described by agent-based models focusing on the role of social coordination. In this work the authors uncover two additional individual-level mechanisms, trend-seeking and inertia, that can critically shape the collective behavior of the population.

    • Mengbin Ye
    • , Lorenzo Zino
    •  & Ming Cao

  • Article
    | Open Access

    Systems of interacting oscillatory units show various types of dynamics, from uniform low-dimensional motion to high-dimensional disorder. The authors follow the path from synchronous to turbulent state via variety of complex patterns that split and collide, explaining mechanisms of their formation.

    • Sindre W. Haugland
    • , Anton Tosolini
    •  & Katharina Krischer

  • Article
    | Open Access

    Whereas transitions from solid- to fluid-like states in systems of active particles have received much attention, the characterization of phase transitions in active fluids with self-organized vortices so far has remained elusive. James et al. take us on a numerical tour de force from active turbulence to active vortex crystals.

    • Martin James
    • , Dominik Anton Suchla
    •  & Michael Wilczek

  • Article
    | Open Access

    Higher order synchronization in optomechanical devices is relatively unexplored. Here the authors use nonlinear parametric effects to entrain an optomechanical oscillator with a drive signal several octaves away from the oscillation frequency, and demonstrate RF frequency division.

    • Caique C. Rodrigues
    • , Cauê M. Kersul
    •  & Gustavo S. Wiederhecker

  • Article
    | Open Access

    Network dismantling allows to find minimum set of units attacking which leads to system’s break down. Grassia et al. propose a deep-learning framework for dismantling of large networks which can be used to quantify the vulnerability of networks and detect early-warning signals of their collapse.

    • Marco Grassia
    • , Manlio De Domenico
    •  & Giuseppe Mangioni

  • Article
    | Open Access

    The question whether a given isolated quantum many-body system would thermalize has currently no general answer. Here, Shiraishi and Matsumoto demonstrate the computational universality of thermalization phenomena already for simplified 1D systems, thus proving that the thermalization problem is undecidable.

    • Naoto Shiraishi
    •  & Keiji Matsumoto

  • Article
    | Open Access

    The motion of the ocean transports microorganisms, pollutants, and other particles, but these are challenging to track. Here the authors present a Lagrangian form of Betweenness Centrality which identifies bottlenecks in dynamical systems and fluid flows as well as an interpretation of diversity hotspots.

    • Enrico Ser-Giacomi
    • , Alberto Baudena
    •  & Emilio Hernández-García

  • Article
    | Open Access

    Micro scale heat engines may be subjected to quite intriguing scenarios. Roy et al superimpose artificial random kicks on an optically trapped colloid, emulating a memoryless non-gaussian reservoir that markedly alters the conditions under which the engine performs at optimum efficiency.

    • Niloyendu Roy
    • , Nathan Leroux
    •  & Rajesh Ganapathy

  • Article
    | Open Access

    Prediction of contagion dynamics is of relevance for epidemic and social complex networks. Murphy et al. propose a data-driven approach based on deep learning which allows to learn mechanisms governing network dynamics and make predictions beyond the training data for arbitrary network structures.

    • Charles Murphy
    • , Edward Laurence
    •  & Antoine Allard

  • Article
    | Open Access

    In their supercritical state simple fluids are generally thought to assume a homogeneous phase throughout. Lee et al. find that liquid droplets temporarily formed in a supercritical background after sub-critical injection can survive for a surprisingly long time.

    • Seungtaek Lee
    • , Juho Lee
    •  & Gunsu Yun

  • Article
    | Open Access

    The analysis of networks and network processes can require low-dimensional representations, possible for specific structures only. The authors propose a geometric formalism which allows to unfold the mechanisms of dynamical processes propagation in various networks, relevant for control and community detection.

    • Adam Gosztolai
    •  & Alexis Arnaudon

  • Article
    | Open Access

    Spontaneous symmetry breaking can induce instabilities in natural and engineered systems. Nicolaou et al. show that such instabilities can be prevented by introducing suitable system asymmetry in the form of spatial heterogeneity, relevant for the development of novel control and design techniques.

    • Zachary G. Nicolaou
    • , Daniel J. Case
    •  & Adilson E. Motter

  • Article
    | Open Access

    It was predicted that complex thermalizing behaviour can arise in many-body systems in the absence of disorder. Here, the authors observe non-ergodic dynamics in a tilted optical lattice that is distinct from previously studied regimes, and propose a microscopic mechanism that is due to emergent kinetic constrains.

    • Sebastian Scherg
    • , Thomas Kohlert
    •  & Monika Aidelsburger

  • Article
    | Open Access

    Neuromorphic nanowire networks are found to exhibit neural-like dynamics, including phase transitions and avalanche criticality. Hochstetter and Kuncic et al. show that the dynamical state at the edge-of-chaos is optimal for learning and favours computationally complex information processing tasks.

    • Joel Hochstetter
    • , Ruomin Zhu
    •  & Zdenka Kuncic

  • Article
    | Open Access

    Dissipative solitons and their symmetry breaking is important for photonic applications. Here the authors show that dissipative solitons can undergo spontaneous symmetry breaking in a two-component nonlinear optical ring resonator, resulting in the coexistence of distinct vectorial solitons with asymmetric, mirror-like states of polarization.

    • Gang Xu
    • , Alexander U. Nielsen
    •  & Miro Erkintalo

  • Article
    | Open Access

    Network embedding is a machine learning technique for construction of low-dimensional representations of large networks. Gu et al. propose a method for the identification of an optimal embedding dimension for the encoding of network structural information inspired by natural language processing.

    • Weiwei Gu
    • , Aditya Tandon
    •  & Filippo Radicchi

  • Article
    | Open Access

    Self-organisation of Min protein patterns observed in vivo and in vitro differ qualitatively and quantitatively. Here the authors reconstituted Min proteins in laterally wide microchambers with a well-controlled height and show that the Min protein dynamics on the membrane crucially depend on the micro chamber height.

    • Fridtjof Brauns
    • , Grzegorz Pawlik
    •  & Cees Dekker

  • Article
    | Open Access

    Ride-sharing, combining similar concurrent trips into one, may support sustainable urban mobility yet lacks broad adoption. Storch et al. reveal how collective interactions in shared rides explain essential characteristics of ride-sharing adoption patterns e.g. observed in New York City and Chicago.

    • David-Maximilian Storch
    • , Marc Timme
    •  & Malte Schröder

  • Article
    | Open Access

    The ability of complex networks to synchronize themselves is limited by available coupling resources. Zhang and Strogatz show that allowing temporal variation in the network structure can lead to synchronization even when stable synchrony is impossible in any static network under the fixed budget.

    • Yuanzhao Zhang
    •  & Steven H. Strogatz

  • Article
    | Open Access

    Social interaction outcomes can depend on the type of information individuals possess and how it is used in decision-making. Here, Zhou et al. find that self-evaluation based decision-making rules lead to evolutionary outcomes that are robust to different population structures and ways of self-evaluation.

    • Lei Zhou
    • , Bin Wu
    •  & Long Wang

  • Article
    | Open Access

    Ito and co-workers unravel how bacteria such as Salmonella switch gears with their flagellar driving machinery. External load triggers the dynamic remodeling of the molecular complex sustaining the torque, and the number of stator units is adapted in a non-trivial, cooperative manner.

    • Kenta I. Ito
    • , Shuichi Nakamura
    •  & Shoichi Toyabe

  • Article
    | Open Access

    Reinbold et al. propose a physics-informed data-driven approach that successfully discovers a dynamical model using high-dimensional, noisy and incomplete experimental data describing a weakly turbulent fluid flow. This approach is relevant to other non-equilibrium spatially-extended systems.

    • Patrick A. K. Reinbold
    • , Logan M. Kageorge
    •  & Roman O. Grigoriev

  • Article
    | Open Access

    A single damage can lead to a complete collapse of supply networks due to a cascading failure mechanism. Kaiser et al. show that by adding new connections network isolators can be created, that can inhibit failure spreading relevant for power grids and water transmission systems.

    • Franz Kaiser
    • , Vito Latora
    •  & Dirk Witthaut

  • Article
    | Open Access

    Furanose species have a key role in the chemistry of life despite their instability over pyranose ones. The authors, through NMR characterization of the anomeric ratios at equilibrium and a non-equilibrium theoretical treatment, show that a steady temperature gradient, at temperatures relevant to the early Earth, favors furanose over pyranose isomers.

    • Avinash Vicholous Dass
    • , Thomas Georgelin
    •  & Francesco Piazza

  • Article
    | Open Access

    Common mitigation measures gradually inhibit the spread of infectious diseases, yielding smooth transitions to large-scale epidemics. As Scarselli et al. show, limited testing may radically change the transition to include jumps, potentially resulting in unforseen, accelerated growth of case numbers.

    • Davide Scarselli
    • , Nazmi Burak Budanur
    •  & Björn Hof

  • Article
    | Open Access

    Network robustness is usually assessed following topological criteria, but disregards the role played by non-topological information. Artime et al. propose a flexible percolation framework that overcomes this limitation and combines both dimensions, offering new ways to protect real systems.

    • Oriol Artime
    •  & Manlio De Domenico

  • Article
    | Open Access

    The famous Kramers turnover describes the extent of friction at which the transition rate of a small particle trapped in a bistable potential becomes a maximum. Militaru et al. present a version of this phenomenon pertaining to active colloids driven by non-conservative forces.

    • A. Militaru
    • , M. Innerbichler
    •  & C. Dellago

  • Article
    | Open Access

    Neuromorphic devices take inspiration from spiking dynamics of neurons in the brain. Here, the authors demonstrate synchronized spiking dynamics in 240 photonic artificial neurons, each of which is implemented with a pair of antisymmetrically coupled degenerate optical parametric oscillators.

    • Takahiro Inagaki
    • , Kensuke Inaba
    •  & Hiroki Takesue

  • Article
    | Open Access

    Electric fields and currents can alter microstructures of materials in unexpected ways. Here the authors report how electrochemical reduction can cause a grain boundary disorder-to-order transition and show the electric field effects on microstructural stability and evolution.

    • Jiuyuan Nie
    • , Chongze Hu
    •  & Jian Luo

  • Article
    | Open Access

    The so-called twist-bend and splay-bend nematic liquid crystal phases are important concepts for studying bent-core mesogens. Chiappini et al. use a theory/simulation approach to suggest that the transition proceed via a twist-splay-bend phase which may be obscured by density modulations.

    • Massimiliano Chiappini
    •  & Marjolein Dijkstra

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