Statistical physics, thermodynamics and nonlinear dynamics articles within Nature Communications

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  • 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

    Based on fundamental thermodynamics, traditional electronic computers, which operate serially, require more energy per computation the faster they operate. Here, the authors show that the energy cost per operation of a parallel computer can be kept very small.

    • Michael Konopik
    • , Till Korten
    •  & Heiner Linke

  • Article
    | Open Access

    In this Bayesian inference study, the authors aim to quantify the impact of the men’s 2020 UEFA Euro Football Championship on COVID-19 spread in twelve participating countries. They estimate that 0.84 million cases and 1,700 deaths were attributable to the championship, with most impacts in England and Scotland.

    • Jonas Dehning
    • , Sebastian B. Mohr
    •  & Viola Priesemann

  • Article
    | Open Access

    Shortest paths between the nodes of complex networks are challenging to obtain if the information on network structure is incomplete. Here the authors show that the shortest paths are geometrically localized in hyperbolic representations of networks, and can be detected even if the large amount of network links are missing. The authors demonstrate the utility of geometric pathfinding in Internet routing and the reconstruction of cellular pathways.

    • Maksim Kitsak
    • , Alexander Ganin
    •  & Igor Linkov

  • Article
    | Open Access

    Feedback control applied to mechanical resonators can lead to the formation of various complex dynamic behaviors. Here the authors demonstrate flexible and controllable switching between dynamical structures in the response of harmonically driven micro-mechanical resonators.

    • Axel M. Eriksson
    • , Oriel Shoshani
    •  & David A. Czaplewski

  • Article
    | Open Access

    The A–B transition in superfluid 3He is a pure experimental model system to study first-order phase transitions in the early Universe. Tian et al. observe the path dependence of the supercooling of the A phase in a wide parameter range and provide explanations for the heterogeneous nucleation of the B phase.

    • Y. Tian
    • , D. Lotnyk
    •  & J. M. Parpia

  • 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

    Here the authors introduce dual communities, characterized by strong connections at their boundaries, and show that they are formed as a trade-off between efficiency and resilience in supply networks.

    • Franz Kaiser
    • , Philipp C. Böttcher
    •  & Dirk Witthaut

  • Article
    | Open Access

    Tanner’s law describes the spreading dynamics of droplets made of Newtonian viscous fluids. Here, the authors demonstrate that this law remains valid for phase-separated binary liquids close to their critical point, and thus for all the associated universality class.

    • Raphael Saiseau
    • , Christian Pedersen
    •  & Jean-Pierre Delville

  • Article
    | Open Access

    Here the authors, by using data from three electrical companies in the USA, find that the recovery duration of an outage is connected with the downtime of its nearby outages and blackout intensity and present a cluster-based recovery framework.

    • Hao Wu
    • , Xiangyi Meng
    •  & Albert-László Barabási

  • Article
    | Open Access

    The manifold’s geometry underlying the connectivity of a complex network determines its navigation ruled by the nodes distances in the geometrical space. In this work, the authors propose an algorithm which allows to uncover the relation between the measures of geometrical congruency and efficient greedy navigability in complex networks.

    • Carlo Vittorio Cannistraci
    •  & Alessandro Muscoloni

  • 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

    Adding prior experimentally or theoretically obtained knowledge to the training of recurrent neural networks may be challenging due to their feedback nature with arbitrarily long memories. The authors propose a path sampling approach that allows to include generic thermodynamic or kinetic constraints for learning of time series relevant to molecular dynamics and quantum systems.

    • Sun-Ting Tsai
    • , Eric Fields
    •  & Pratyush Tiwary

  • Perspective
    | Open Access

    Theoretical models and structures recovered from measured data serve for analysis of complex networks. The authors discuss here existing gaps between theoretical methods and real-world applied networks, and potential ways to improve the interplay between theory and applications.

    • Leto Peel
    • , Tiago P. Peixoto
    •  & Manlio De Domenico

  • Article
    | Open Access

    The communication in active systems plays an important role in their self-organization, yet the detail is not fully understood. Here, Ziepke et al. show the formation of complex structures at multiple scales amongst interactive agents that locally process information transmitted by chemical signals.

    • Alexander Ziepke
    • , Ivan Maryshev
    •  & Erwin Frey

  • 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

    Some active matter systems as they evolve, can be characterized by spatially varying density, with some regions that are dense and immobile, and other regions with lower density that accommodate most mobile particles. The authors show that this phenomenon can also be observed as an effect of the social interactions between fire ants.

    • Caleb Anderson
    •  & Alberto Fernandez-Nieves

  • 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

    Investigations of quantum thermal machines and Liouvillian exceptional points have rarely crossed each other. Here, the authors realize experimentally a quantum Otto engine using a single trapped ion, and show that crossing a Liouvillian exceptional point during the cycle increases the engine performance.

    • J.-W. Zhang
    • , J.-Q. Zhang
    •  & M. Feng

  • Article
    | Open Access

    Reducing of dimension is often necessary to detect and analyze patterns in large datasets and complex networks. Here, the authors propose a method for detection of the intrinsic dimensionality of high-dimensional networks to reproduce their complex structure using a reduced tractable geometric representation.

    • Pedro Almagro
    • , Marián Boguñá
    •  & M. Ángeles Serrano

  • Article
    | Open Access

    Spontaneous low-frequency oscillations, which are a feature of biological systems, are challenging to engineer into microrobotic systems. The authors discover a mechanism for asymmetry-induced order and realise electrical and mechanical oscillations in a particle collective to power a microrobotic arm.

    • Jing Fan Yang
    • , Thomas A. Berrueta
    •  & Michael S. Strano

  • 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

    Socioeconomic segregation is one of the main factors behind large-scale inequalities in urban areas and its characterisation remains challenging. The authors propose a family of non-parametric measures to quantify spatial heterogeneity through diffusion, and show how this relates to segregation and deprivation

    • Sandro Sousa
    •  & Vincenzo Nicosia

  • Article
    | Open Access

    It has long been suggested that the inverse Fourier transform of neutron scattering data gives access to space- and time-resolved spin-spin correlations. Scheie et al. perform this procedure on high-precision experimental data from a 1D quantum antiferromagnet and uncover new features in short-term quench dynamics.

    • A. Scheie
    • , P. Laurell
    •  & D. A. Tennant

  • Article
    | Open Access

    2D transition metal ditellurides exhibit nontrivial topological phases, but the controlled bottom-up synthesis of these materials is still challenging. Here, the authors report the layer-by-layer growth of large-area bilayer and trilayer 1T’ MoTe2 films, showing thickness-dependent ferroelectricity and nonlinear Hall effect.

    • Teng Ma
    • , Hao Chen
    •  & Kian Ping Loh

  • Article
    | Open Access

    Increasing the capacity of existing lines or adding new lines in power grids may, counterintuitively, reduce the system performance and promote blackouts. The authors propose an approach for prediction of edges that lower system performance and defining potential constrains for grid extensions.

    • Benjamin Schäfer
    • , Thiemo Pesch
    •  & Marc Timme

  • 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

    Spreading processes and cascading failures on complex networks are often triggered by external perturbations. The authors uncover the impact of network motifs on the processes of perturbations propagation through networks, and networks’ response dynamics.

    • Xiaoge Bao
    • , Qitong Hu
    •  & Jan Nagler

  • Article
    | Open Access

    Dissipatively coupled oscillators, describing lossy flows in power grids, are challenging to analyze due to asymmetry of couplings. Here, Delabays et al. reveal counterintuitive behaviours of increased capacity and increased stability in a network of lossy oscillators.

    • Robin Delabays
    • , Saber Jafarpour
    •  & Francesco Bullo

  • 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

    While inequalities in science are common, most efforts to understand them treat scientists as isolated individuals, ignoring the network effects of collaboration. Here, the authors develop models that untangle the network effects of productivity and prominence of individual scientists from their collaboration networks.

    • Weihua Li
    • , Sam Zhang
    •  & Aaron Clauset

  • Article
    | Open Access

    Networks with higher-order interactions are relevant to variety of real-world applications, they can be good description of data even if the system has only pairwise interactions. The authors uncover the hypernetwork emergence in coupled nonlinear oscillators and electrochemical experiments.

    • Eddie Nijholt
    • , Jorge Luis Ocampo-Espindola
    •  & Tiago Pereira

  • 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

    Magnetohydrodynamic instabilities are related to different characteristics and behavior of fluids. Here the authors report an experiment and simulation combined study of a global non-axisymmetric MHD instability that exists at sufficiently large rotation rates and intermediate magnetic field strengths.

    • Yin Wang
    • , Erik P. Gilson
    •  & Hantao Ji

  • Article
    | Open Access

    In modern power grids, knowing the required electric power demand and its variations is necessary to balance demand and supply. The authors propose a data-driven approach to create high-resolution load profiles and characterize their fluctuations, based on recorded data of electricity consumption.

    • Mehrnaz Anvari
    • , Elisavet Proedrou
    •  & Marc Timme

  • 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

  • Article
    | Open Access

    Memory and information storage play an important role in biological systems, however challenging to implement in synthetic active matter. The authors show that the wave field, propelling the particle, acts as a memory repository, and an excess of memory leads to a memory-less particle dynamics.

    • Maxime Hubert
    • , Stéphane Perrard
    •  & Matthieu Labousse

  • Article
    | Open Access

    Transportation networks undergo permanent changes influenced by a variety of human-induced and natural factors. The authors propose here a machine learning framework for prediction of connections removal that could be useful in building scenarios for transportation infrastructure needs.

    • Weihua Lei
    • , Luiz G. A. Alves
    •  & Luís A. Nunes Amaral

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