Statistical physics, thermodynamics and nonlinear dynamics articles within Nature Communications

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  • 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

  • Article
    | Open Access

    There has been much interest in using the probabilistic switching of magnetic tunnel junctions in unconventional computing, but to do so requires a detailed understanding of this switching. Here, Funatsu et al rigorously determine the switching exponents in superparamagnetic tunnel junctions.

    • Takuya Funatsu
    • , Shun Kanai
    •  & Hideo Ohno

  • Article
    | Open Access

    Confining plasma for fusion requires controlling many parameters. Here the authors report the existence of a narrow parameter space for the simultaneous confinement of energetic alpha particles and removal of slowed-down helium ash in a magnetically confined fusion plasma by using kinetic-magnetohydrodynamic hybrid simulations.

    • A. Bierwage
    • , K. Shinohara
    •  & S. Ide

  • Article
    | Open Access

    The authors investigate the influence of brain injury (strokes) on the criticality of neural dynamics using directly measured connectomes and whole-brain models. They show that lesions engender a sub-critical state that recovers over time in parallel with behavior.

    • Rodrigo P. Rocha
    • , Loren Koçillari
    •  & Maurizio Corbetta

  • Article
    | Open Access

    Boolean networks modelling various biological processes are characterized by nonlinear reversible dynamics that makes their control challenging. The authors introduce extended concepts of influence and control, typically considered in the study of spreading processes, for Boolean dynamics.

    • Thomas Parmer
    • , Luis M. Rocha
    •  & Filippo Radicchi

  • Article
    | Open Access

    Topological phases are challenging to identify in systems with general, strong nonlinearities. Here, the authors establish the analytic methodology that defines the topological invariant of nonlinear normal modes. Strongly nonlinear topological boundary modes are guaranteed by the nontrivial topological index.

    • Di Zhou
    • , D. Zeb Rocklin
    •  & Yugui Yao

  • Article
    | Open Access

    Light–matter interaction is expected to be isotropic in free-electron-like materials. Here, by using time- and phase-resolved photoemission, the authors observe signatures of an anisotropic interaction on a noble metal surface, that can only be accounted for by optical transition dipoles with a fixed orientation.

    • Tobias Eul
    • , Eva Prinz
    •  & Benjamin Stadtmüller

  • Article
    | Open Access

    Helium isotopes are interesting platforms for testing the quantum properties of fluids. Here the authors demonstrate quantum one-dimensional behaviour of helium (4He) confined in nanopores by using neutron scattering.

    • Adrian Del Maestro
    • , Nathan S. Nichols
    •  & Paul E. Sokol

  • Article
    | Open Access

    Understanding the transport of the particles and fuel in the fusion plasma is fundamentally important. Here the authors report a cross-link interaction between electron- and ion-scale turbulences in plasma in terms of trapped electron mode and electron temperature gradient modes and their implication to fusion plasma.

    • Shinya Maeyama
    • , Tomo-Hiko Watanabe
    •  & Akihiro Ishizawa

  • Article
    | Open Access

    Defining the dimension in bounded, inhomogeneous or discrete physical systems may be challenging. The authors introduce here a dynamics-based notion of dimension by analysing diffusive processes in space, relevant for non-ideal physical systems and networks.

    • Robert Peach
    • , Alexis Arnaudon
    •  & Mauricio Barahona

  • Article
    | Open Access

    Rumors and information spreading emerge naturally from human-to-human interaction and have a growing impact on people’s lives due to increasing and faster access to information, whether trustworthy or not. The authors study the Maki–Thompson rumor model and its variation, revealing a phase transition and providing insights into the nature of this transition.

    • Guilherme Ferraz de Arruda
    • , Lucas G. S. Jeub
    •  & Yamir Moreno

  • Article
    | Open Access

    Data-driven recovery of topology is challenging for networks beyond pairwise interactions. The authors propose a framework to reconstruct complex networks with higher-order interactions from time series, focusing on networks with 2-simplexes where social contagion and Ising dynamics generate binary data.

    • Huan Wang
    • , Chuang Ma
    •  & Hai-Feng Zhang

  • Article
    | Open Access

    Pre-exposure prophylaxis (PrEP) is an effective HIV prevention measure but identifying those most at risk to target for treatment is challenging. Here, the authors demonstrate that non-selective PrEP distribution outperforms targeted strategies when use is not consistent, and/or prevalence of untreated HIV is high.

    • Benjamin Steinegger
    • , Iacopo Iacopini
    •  & Eugenio Valdano

  • Article
    | Open Access

    While topology is crucial in complex systems, stochastic thermodynamics uncovers universal constraints for non-equilibrium fluctuations. The authors combine these two areas and formulate a fluctuation theorem for the heat dissipated along closed loops in vortex force fields, which is found to be topologically protected.

    • Benoît Mahault
    • , Evelyn Tang
    •  & Ramin Golestanian

  • Article
    | Open Access

    Biological and artificial microswimmers often navigate channels under external flow, where in many biomicroswimmers the active upstream motion is oscillatory. Here the authors demonstrate that regular, controllable, and reproducible oscillatory rheotaxis can be observed in artificial microswimmers.

    • Ranabir Dey
    • , Carola M. Buness
    •  & Corinna C. Maass

  • Article
    | Open Access

    The power generated by an ideal thermal machine cannot exceed the Carnot limit in classical physics. Here, Ryu et al., demonstrate that a periodically driven quantum chiral conductor can exhibit efficiencies beyond the Carnot limit while the second law of thermodynamics is preserved.

    • Sungguen Ryu
    • , Rosa López
    •  & David Sánchez

  • Article
    | Open Access

    Modern power grids undergo a transition due to the integration of renewable energy generation technologies that bring heterogeneity in the grid. The authors study the synchronization and stability of power grids with heterogeneous inertia and damping factors, and demonstrate power feasibility of operating a system consisting of only renewable generation technologies with enhanced stability.

    • Amirhossein Sajadi
    • , Rick Wallace Kenyon
    •  & Bri-Mathias Hodge

  • Article
    | Open Access

    Electric circuits represent a versatile platform for simulations of exotic phenomena that are difficult to realize is condensed matter systems. Here the authors simulate particle statistics-dependent Bloch oscillations with electric circuits and observe features predicted for a model of anyons on a 1D lattice.

    • Weixuan Zhang
    • , Hao Yuan
    •  & Xiangdong Zhang

  • Article
    | Open Access

    “A hallmark of living systems is their homochirality, the selection of specific mirror symmetry in their molecules. Here, the authors show that chiral symmetry can be spontaneously broken in complex, random chemical systems via exploitation of environmental energy sources – a possible mechanism for the emergence of homochirality in life.”

    • William D. Piñeros
    •  & Tsvi Tlusty

  • Article
    | Open Access

    Reconfigurability at the micro-scale is rare. Here, authors present a versatile magnetic microrobot collective that reconfigures on-demand among miscellaneous behaviors that allow for exploration, navigation, and interaction with diverse environments.

    • Gaurav Gardi
    • , Steven Ceron
    •  & Metin Sitti

  • Article
    | Open Access

    Cellular adhesions have the remarkable property that they adapt their stability to the applied mechanical load. Here, authors describe a generic physical mechanism that explains self-stabilization of idealized adhesion systems under shear.

    • Andrea Braeutigam
    • , Ahmet Nihat Simsek
    •  & Benedikt Sabass

  • Article
    | Open Access

    The dynamic structure of supramolecular polymers is challenging to determine both in experiments and in simulations. Here the authors use coarse-grained molecular models to provide a comprehensive analysis of the molecular communication in these complex molecular systems.

    • Martina Crippa
    • , Claudio Perego
    •  & Giovanni M. Pavan

  • Article
    | Open Access

    Understanding of the collective motion seen in biological systems is crucial for development of autonomous robots and swarm computing. The authors introduce an experimental platform with liquid crystal driven by external electric field, that mimics the collective motion of living systems.

    • Yuan Shen
    •  & Ingo Dierking

  • Article
    | Open Access

    Turbulent flows are observed in atmosphere, ocean, and technology, with turbulent mixing due to stretching and folding of material elements. The authors analyze a geometric perspective of this process and uncover statistical properties of an ensemble of material loops in a turbulent environment.

    • Lukas Bentkamp
    • , Theodore D. Drivas
    •  & Michael Wilczek

  • Article
    | Open Access

    Metallic microsamples deform in a sequence of abrupt strain bursts. Here, the authors demonstrate by analysing the elastic waves emitted by these bursts that this intermittent process resembles earthquakes in several aspects, although on completely different spatial and temporal scales.

    • Péter Dusán Ispánovity
    • , Dávid Ugi
    •  & István Groma

  • Article
    | Open Access

    Information about an individual’s mobility can leave traces embedded in the social network. The authors show that such traces are also present beyond the social network. Simple colocation contains predictive information about one’s mobility patterns even when the colocators have no social links. In the aggregate, non-social information can sometimes meet or exceed social information.

    • Zexun Chen
    • , Sean Kelty
    •  & Gourab Ghoshal

  • Article
    | Open Access

    Investigating and tailoring the thermodynamic properties of different fluids is crucial to many applied fields such as energy and refrigeration cycles. Here, authors use multistable, gas filled, particles suspension to enhance the macro-properties of thermodynamic fluids.

    • Ofek Peretz
    • , Ezra Ben Abu
    •  & Amir D. Gat

  • Article
    | Open Access

    Ranking lists are relevant to various areas of nature and society, however their evolution with the elements changing rank in time remained unexplored. The authors uncover a mechanism of ranking dynamics induced by the flux governing the arrival of new elements in the list, for improved predictability of ranking models.

    • Gerardo Iñiguez
    • , Carlos Pineda
    •  & Albert-László Barabási

  • Article
    | Open Access

    Quantum heat transport devices are currently intensively studied. Here, the authors report the photonic heat transport modulated by superconducting qubit in a three-terminal device. Flux dependent heat power correlates with microwave measurements.

    • Azat Gubaydullin
    • , George Thomas
    •  & Jukka P. Pekola

  • Article
    | Open Access

    In consensus-based collective dynamics, the occurrence of simple and complex contagions shapes system behavior. The authors analyze a transition from simple to complex contagions in collective decision-making processes based on consensus, and demonstrate it with a swarm robotic system.

    • Nikolaj Horsevad
    • , David Mateo
    •  & Roland Bouffanais

  • Article
    | Open Access

    The authors identify characteristic patterns that describe the propagation of information in online social media platforms. They show that, depending on the topic, the information flows can spread as simple or complex contagion processes, operating at a critical regime.

    • Daniele Notarmuzi
    • , Claudio Castellano
    •  & Filippo Radicchi

  • Article
    | Open Access

    Infrastructure and power systems are often represented as multilayer structures of interdependent networks. Danziger and Barabási demonstrate the presence of recovery coupling in such systems, where the recovery of an element in one network requires resources from nodes and links in another network.

    • Michael M. Danziger
    •  & Albert-László Barabási

  • Article
    | Open Access

    Rotor-like dynamics is observed in many natural systems, from the rotor proteins in cellular membranes to atmospheric models. Here, the authors uncover geometrical conservation laws that limit distribution of driven rotors in a membrane or a soap film and allow to predict their structural states.

    • Naomi Oppenheimer
    • , David B. Stein
    •  & Michael J. Shelley

  • Perspective
    | Open Access

    Many biological processes require changes in the physical properties of cells and their surroundings. Here, Lenne and Trivedi discuss recent findings in biological systems in terms of phase transitions in inert physical systems from both theoretical and experimental perspectives.

    • Pierre-François Lenne
    •  & Vikas Trivedi

  • Article
    | Open Access

    Auxetic materials are characterized by a negative Poisson’s ratio - they become thicker when stretched. Here, authors reach the limit of auxetic behavior, known as hyper-auxetic, in polymer networks, hitting an unconventional mechanical critical point.

    • Andrea Ninarello
    • , José Ruiz-Franco
    •  & Emanuela Zaccarelli

  • Article
    | Open Access

    The evolution of networks with structure changing in time is dependent on their past states and relevant to diffusion and spreading processes. The authors show that temporal network’s memory is described by multidimensional patterns at a microscopic scale, and cannot be reduced to a scalar quantity.

    • Oliver E. Williams
    • , Lucas Lacasa
    •  & Vito Latora

  • Article
    | Open Access

    Optimal control of complex dynamical systems can be challenging due to cost constraints and analytical intractability. The authors propose a machine-learning-based control framework able to learn control signals and force complex high-dimensional dynamical systems towards a desired target state.

    • Lucas Böttcher
    • , Nino Antulov-Fantulin
    •  & Thomas Asikis

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