Statistical physics, thermodynamics and nonlinear dynamics articles within Nature Communications

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  • Article
    | Open Access

    Here the authors identify a generic coupling in phase-separated liquids between motility and phase equilibria perturbations: phase-separated droplets swim to their dissolution. This suggests alternative transport mechanism for biomolecular condensates.

    • Etienne Jambon-Puillet
    • , Andrea Testa
    •  & Eric R. Dufresne

  • Article
    | Open Access

    Creating accurate digital twins and controlling nonlinear systems displaying chaotic dynamics is challenging due to high system sensitivity to initial conditions and perturbations. The authors introduce a nonlinear controller for chaotic systems, based on next-generation reservoir computing, with improved accuracy, energy cost, and suitable for implementation with field-programmable gate arrays.

    • Robert M. Kent
    • , Wendson A. S. Barbosa
    •  & Daniel J. Gauthier

  • Article
    | Open Access

    Finding an optimal shape for transport networks, represented as multilayer structures, is a challenging problem. The authors propose analytical and computational frameworks to analyze sharp transitions from symmetric to asymmetric shapes in optimal networks, that can be applied for planning and development of improved multimodal transportation systems within a city.

    • Siddharth Patwardhan
    • , Marc Barthelemy
    •  & Filippo Radicchi

  • Article
    | Open Access

    The study of defects and boundaries in the context of conformal field theory is important but challenging in dimensions higher than two. Here the authors use the recently developed fuzzy sphere regularization approach to perform non-perturbative analysis of defect conformal field theory in 3D

    • Liangdong Hu
    • , Yin-Chen He
    •  & W. Zhu

  • Article
    | Open Access

    Thurner and colleagues explore how economic shocks spread risk through the globalized economy. They find that rich countries expose poor countries stronger to systemic risk than vice-versa. The risk is highly concentrated, however higher risk levels are not compensated with a risk premium in GDP levels, nor higher GDP growth. The findings put the often-praised benefits for developing countries from globalized production in a new light, by relating them to risks involved in the production processes

    • Abhijit Chakraborty
    • , Tobias Reisch
    •  & Stefan Thurner

  • 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

  • Comment
    | Open Access

    Can many-body systems be beneficial to designing quantum technologies? We address this question by examining quantum engines, where recent studies indicate potential benefits through the harnessing of many-body effects, such as divergences close to phase transitions. However, open questions remain regarding their real-world applications.

    • Victor Mukherjee
    •  & Uma Divakaran

  • Article
    | Open Access

    Collective cooperation is found across many social and biological systems. Here, the authors find that infrequent hub updates promote the emergence of collective cooperation and develop an algorithm that optimises collective cooperation with update rates.

    • Yao Meng
    • , Sean P. Cornelius
    •  & Aming Li

  • 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

    Collective behavior of nonlinear soft valves forming fluid flow networks is not well understood. The authors reveal the mechanisms underlying the collective behavior of soft flow networks with negative differential resistance elements.

    • Alejandro Martínez-Calvo
    • , Matthew D. Biviano
    •  & Miguel Ruiz-García

  • Article
    | Open Access

    Evolution processes of complex networked systems in biology and social sciences, and their underlying mechanisms, still need better understanding. The authors propose a machine learning approach to reconstruct the evolution history of complex networks.

    • Junya Wang
    • , Yi-Jiao Zhang
    •  & Yanqing Hu

  • 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

    For reservoir computing, improving prediction accuracy while maintaining low computing complexity remains a challenge. Inspired by the Granger causality, Li et al. design a data-driven and model-free framework by integrating the inference process and the inferred results on high-order structures.

    • Xin Li
    • , Qunxi Zhu
    •  & Wei Lin

  • Article
    | Open Access

    The understanding of salty water droplet freezing is limited. The authors examine the formation of brine film on top of frozen salty droplets and discover a new ice crystal growth pattern sprouting from the bottom of the brine film.

    • Fuqiang Chu
    • , Shuxin Li
    •  & Nenad Miljkovic

  • Article
    | Open Access

    Forecasting the future behaviors based on observed data remains a challenging task especially for large nonlinear systems. The authors propose a data-driven approach combining manifold learning and delay embeddings for prediction of dynamics for all components in high-dimensional systems.

    • Tao Wu
    • , Xiangyun Gao
    •  & Jürgen Kurths

  • Article
    | Open Access

    Authors control heat transfer through twisting moiré conductive thermal metasurface, showcasing the potential for manipulating thermal conductivity and temperature gradients with imitated magic angles, thereby realizing multifunctional thermal metadevices.

    • Huagen Li
    • , Dong Wang
    •  & Cheng-Wei Qiu

  • Perspective
    | Open Access

    Reservoir Computing has shown advantageous performance in signal processing and learning tasks due to compact design and ability for fast training. Here, the authors discuss the parallel progress of mathematical theory, algorithm design and experimental realizations of Reservoir Computers, and identify emerging opportunities as well as existing challenges for their large-scale industrial adoption.

    • Min Yan
    • , Can Huang
    •  & Jie Sun

  • 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

    Studying out-of-equilibrium entanglement fluctuations is beyond the scope of current theories. Lim et al. present an analytical theory of fluctuations in long-time dynamics of entanglement in two classes of integrable lattice models, showing features reminiscent of universal mesoscopic fluctuations.

    • Lih-King Lim
    • , Cunzhong Lou
    •  & Chushun Tian

  • Article
    | Open Access

    Soft composite solids are building blocks for many functional and biological materials, yet it remains challenging to predict their mechanical properties. Zhao et al. propose a criticality framework to connect the mechanics to the critical behaviour near the shear-jamming transition of the dispersed inclusions.

    • Yiqiu Zhao
    • , Haitao Hu
    •  & Qin Xu

  • Article
    | Open Access

    Kinks define boundaries between distinct configurations of a material. Here, the authors reveal the emergence of propagating kinks in purely dissipative kirigami and show that such structures can shape-change into different textures depending on how fast they are stretched enabling basic mechanical tasks.

    • Shahram Janbaz
    •  & Corentin Coulais

  • 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

    Early warning signals for rapid regime shifts in complex networks are of importance for ecology, climate and epidemics, where heterogeneities in network nodes and connectivity make construction of early warning signals challenging. The authors propose a method for selecting an optimal set of nodes from which a reliable early warning signal can be obtained.

    • Naoki Masuda
    • , Kazuyuki Aihara
    •  & Neil G. MacLaren

  • Article
    | Open Access

    Achieving genetic circuits on single DNA molecules could have varied applications. Here, authors observed proteins emerging from single DNA molecules through coupled transcription-translation complexes, and show that nascent proteins lingered on DNA, regulating cascaded reactions on the same DNA and allowing the design of a pulsatile genetic circuit.

    • Ferdinand Greiss
    • , Nicolas Lardon
    •  & Roy Bar-Ziv

  • Article
    | Open Access

    The ability of living systems to process signals and information is of vital importance. Inspired by nature, Wang and Cichos show an experimental realization of a physical reservoir computer using self-propelled active microparticles to predict chaotic time series such as the Mackey–Glass and Lorenz series.

    • Xiangzun Wang
    •  & Frank Cichos

  • 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

    Identification of nodes that play a crucial role in the complex network functionality is of high relevance for supply, transportation, and epidemic spreading networks. The authors propose a metric to evaluate nodal dominance based on competition dynamics that integrate local and global topological information, revealing fragile structures in complex networks.

    • Marcus Engsig
    • , Alejandro Tejedor
    •  & Chaouki Kasmi

  • Article
    | Open Access

    Approaches for assessing epidemic risks meet challenges when dealing with high-resolution data available nowadays, that includes behaviors, disease progression, and interventions. The authors propose an analytical framework to compute the epidemic threshold for arbitrary models of diseases, interventions, and hosts contact patterns.

    • Eugenio Valdano
    • , Davide Colombi
    •  & Vittoria Colizza

  • 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

    Embedding of complex networks in the latent geometry allows for a better understanding of their features. The authors propose a framework for mapping complex networks into high-dimensional hyperbolic space to capture their intrinsic dimensionality, navigability and community structure.

    • Robert Jankowski
    • , Antoine Allard
    •  & M. Ángeles Serrano

  • Article
    | Open Access

    The physics of confinement manifested in quantum spin chain models has been recently studied in quantum simulators. Here the authors report a numerical study of confinement of soliton excitations in a nonintegrable bosonic quantum field theory realized with a superconducting quantum electronic circuit.

    • Ananda Roy
    •  & Sergei L. Lukyanov

  • Article
    | Open Access

    Quantum oscillations serve as an important probe of electronic structure of quantum materials. Yang et al. study quantum oscillations in the electronic specific heat of natural graphite, unveiling a double-peak structure absent in commonly used theory, and show its utility in determining the Landé g-factors.

    • Zhuo Yang
    • , Benoît Fauqué
    •  & Yoshimitsu Kohama

  • 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

    Degree distributions are often used as informative descriptions of complex networks, however previous studies mainly focused on characterizing the tail of the distribution. The authors propose an evolutionary model that integrates the weight and degree of a node, which allows to better capture degree and degree ratio distributions of real networks and replicate their evolution processes.

    • Bin Zhou
    • , Petter Holme
    •  & Xiangyi Meng

  • Article
    | Open Access

    High-temperature behaviour of thermopower is special in cuprates, allowing for theory-experiment comparisons. Wang et al. use quantum Monte Carlo to compute high temperature thermopower in the Hubbard model, demonstrating qualitative and quantitative agreement with experiments across multiple cuprate families.

    • Wen O. Wang
    • , Jixun K. Ding
    •  & Thomas P. Devereaux

  • Article
    | Open Access

    Many-body localization is observed in synthetic systems, but experiments on real materials with Coulomb interactions are vital for insights in higher dimensions. Stanley et al. report a prethermal regime in the dynamics of a 2D disordered electron system in Si MOSFETs and explore the effects of interaction range.

    • L. J. Stanley
    • , Ping V. Lin
    •  & Dragana Popović

  • 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

    The authors use a complexity-based approach to analyze Arctic weather variability. They identify a pronounced link between the Arctic’s shrinking sea ice and global weather patterns, underscoring the critical role of the Arctic in shaping global climate.

    • Jun Meng
    • , Jingfang Fan
    •  & Jürgen Kurths

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