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Inferring Network Connectivity from Event Timing patterns

Physical Review Letters 2018年第5期121卷 054101-054101页

作者： Jose Casadiego Dimitra Maoutsa Marc Timme Chair for Network Dynamics Institute of Theoretical Physics and Center for Advancing Electronics Dresden (cfaed) Technical University of Dresden 01062 Dresden Germany Network Dynamics Max Planck Institute for Dynamics and Self-Organization (MPIDS) 37077 Göttingen Germany Artificial Intelligence Group Department of Software Engineering and Theoretical Computer Science Technical University of Berlin 10587 Berlin Germany Bernstein Center for Computational Neuroscience (BCCN) 37077 Göttingen Germany Max Planck Institute for the Physics of Complex Systems 01069 Dresden Germany

Reconstructing network connectivity from the collective dynamics of a system typically requires access to its complete continuous-time evolution, although these are often experimentally inaccessible. Here we propose a theory for revealing physical connectivity of networked systems only from the event time series their intrinsic collective dynamics generate. Representing the patterns of event timings in an event space spanned by interevent and cross-event intervals, we reveal which other units directly influence the interevent times of any given unit. For illustration, we linearize an event-space mapping constructed from the spiking patterns in model neural circuits to reveal the presence or absence of synapses between any pair of neurons, as well as whether the coupling acts in an inhibiting or activating (excitatory) manner. The proposed model-independent reconstruction theory is scalable to larger networks and may thus play an important role in the reconstruction of networks from biology to social science and engineering.

关键词： Collective behavior in networks Collective dynamics Network structure Neural information Neuronal dynamics Neuronal networks patterns in complex systems Synapses Topological tools

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Shearlet-based measures of entropy and complexity for two-dimensional patterns

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Physical Review E 2018年第6期97卷 061301(R)-061301(R)页

作者： Alexey Brazhe Department of Biophysics Faculty of Biology Moscow State University Leninskie gory 1/24 119234 Russia

New spatial entropy and complexity measures for two-dimensional patterns are proposed. The approach is based on the notion of disequilibrium and is built on statistics of directional multiscale coefficients of the fast finite shearlet transform. Shannon entropy and Jensen-Shannon divergence measures are employed. Both local and global spatial complexity and entropy estimates can be obtained, thus allowing for spatial mapping of complexity in inhomogeneous patterns. The algorithm is validated in numerical experiments with a gradually decaying periodic pattern and Ising surfaces near critical state. It is concluded that the proposed algorithm can be instrumental in describing a wide range of two-dimensional imaging data, textures, or surfaces, where an understanding of the level of order or randomness is desired.

关键词： Order parameters patterns in complex systems Phase transitions Scaling laws of complex systems Structural order parameter

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Suppression of spatially periodic patterns by dc voltage

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Physical Review E 2016年第4期93卷 042701-042701页

作者： Nándor Éber Péter Salamon Balázs András Fekete Ridvan Karapinar Alexei Krekhov Ágnes Buka Institute for Solid State Physics and Optics Wigner Research Centre for Physics Hungarian Academy of Sciences H-1525 Budapest P.O. Box 49 Hungary 100. Yil University Department of Physics 650580 Van Turkey Max Planck Institute for Dynamics and Self-Organization 37077 Göttingen Germany

The effect of superposed dc and ac applied voltages on two types of spatially periodic instabilities in nematic liquid crystals, flexoelectric domains (FD), and electroconvection (EC) was studied. The onset characteristics, threshold voltages, and critical wave vectors were determined. We found that in general the superposition of driving with different time symmetries inhibits the pattern forming mechanisms for FD and EC as well. As a consequence, the onset extends to much higher voltages than the individual dc or ac thresholds. A dc-bias-induced reduction of the crossover frequency from the conductive to the dielectric EC regimes and a peculiar transition between two types of flexodomains with different wavelengths were detected. Direct measurements of the change of the electrical conductivity and its anisotropy, induced by the applied dc voltage component, showed that the dc bias substantially affects both parameters. Taking into account the experimentally detected variations of the conductivity in the linear stability analysis of the underlying nematohydrodynamic equations, a qualitative agreement with the experimental findings on the onset behavior of spatially periodic instabilities was obtained.

关键词： Flexoelectricity patterns in complex systems Nematic liquid crystals

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Quantifying spatiotemporal patterns in classical and quantum systems out of equilibrium

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Physical Review E 2024年第2期109卷 024105-024105页

作者： E. A. Maletskii I. A. Iakovlev V. V. Mazurenko Theoretical Physics and Applied Mathematics Department Ural Federal University Mira Street 19 620002 Ekaterinburg Russia

A rich variety of nonequilibrium dynamical phenomena and processes unambiguously calls for the development of general numerical techniques to probe and estimate a complex interplay between spatial and temporal degrees of freedom in many-body systems of completely different nature. In this work we provide a solution to this problem by adopting a structural complexity measure to quantify spatiotemporal patterns in the time-dependent digital representation of a system. On the basis of very limited amount of data our approach allows us to distinguish different dynamical regimes and define critical parameters in both classical and quantum systems. By the example of the discrete time crystal realized in nonequilibrium quantum systems we provide a complete low-level characterization of this nontrivial dynamical phase with only processing bitstrings, which can be considered as a valuable alternative to previous studies based on the calculations of qubit correlation functions.

关键词： Dynamical phase transitions Magnetization dynamics patterns in complex systems Quantum phase transitions

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Active Tuning of Synaptic patterns Enhances Immune Discrimination

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Physical Review Letters 2018年第23期121卷 238101-238101页

作者： Miloš Knežević Hongda Jiang Shenshen Wang Department of Physics and Astronomy University of California Los Angeles Los Angeles California 90095 USA

Immune cells learn about their antigenic targets using tactile sense: a self-organized motif named immunological synapse forms between an immune cell and an antigen-presenting cell (APC) during recognition. Via synapses, immune cells apply mechanical pulling forces to selectively extract antigen (Ag) from APCs. Curiously, depending on its stage of development, a B lymphocyte exhibits distinct synaptic patterns and uses force at different strength and timing, which appears to strongly impact its ability to distinguish Ag affinities. We use a statistical-mechanical model to study how the experimentally observed synaptic architectures can originate from normal cytoskeletal forces coupled to the lateral organization of mobile receptors, and show how this active regulation scheme, collective in nature, may enhance the efficiency and capacity of discrimination.

关键词： Cell adhesion Cell mechanics Classical statistical mechanics Force sensing Membranes patterns in complex systems Phase separation Cell junctions Metropolis algorithm

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Electroconvective Instability in Water Electrolysis: An Evaluation of Electroconvective patterns and Their Onset Features

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Physical Review Applied 2021年第3期16卷 034021-034021页

作者： Nakul Pande Jeffery A. Wood Guido Mul Detlef Lohse Bastian T. Mei Dominik Krug Physics of Fluids University of Twente 7500AE Enschede Netherlands PhotoCatalytic Synthesis University of Twente 7500AE Enschede Netherlands Soft matter Fluidics and Interfaces University of Twente 7500AE Enschede Netherlands

In electrochemical systems, an understanding of the underlying transport processes is required to aid in their better design. This includes knowledge of possible near-electrode convective mixing that can enhance measured currents. Here, for a binary acidic electrolyte in contact with a platinum electrode, we provide evidence of electroconvective instability during electrocatalytic proton reduction. The current-voltage characteristics indicate that electroconvection, visualized with a fluorescent dye, drives current densities larger than the diffusion transport limit. The onset and transition times of the instability do not follow the expected inverse-square dependence on the current density, but, above a bulk-reaction-limited current density, are delayed by the water dissociation reaction, that is, the formation of H+ and OH− ions. The dominant size of the electroconvective patterns is also measured and found to vary with the diffusion length scale, confirming previous predictions on the size of electroconvective vortices.

关键词： Chemical kinetics, dynamics & catalysis Convection Electrochemistry Electrokinetic flows Energy sources patterns in complex systems

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Theory of Turing patterns on Time Varying Networks

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Physical Review Letters 2017年第14期119卷 148301-148301页

作者： Julien Petit Ben Lauwens Duccio Fanelli Timoteo Carletti naXys Namur Institute for Complex Systems University of Namur B5000 Namur Belgium Department of Mathematics Royal Military Academy B1000 Brussels Belgium Dipartimento di Fisica e Astronomia and CSDC Università degli Studi di Firenze 50019 Sesto Fiorentino Italy INFN Sezione di Firenze 50019 Sesto Fiorentino Italy

The process of pattern formation for a multispecies model anchored on a time varying network is studied. A nonhomogeneous perturbation superposed to an homogeneous stable fixed point can be amplified following the Turing mechanism of instability, solely instigated by the network dynamics. By properly tuning the frequency of the imposed network evolution, one can make the examined system behave as its averaged counterpart, over a finite time window. This is the key observation to derive a closed analytical prediction for the onset of the instability in the time dependent framework. Continuously and piecewise constant periodic time varying networks are analyzed, setting the framework for the proposed approach. The extension to nonperiodic settings is also discussed.

关键词： Collective behavior in networks Dynamics of networks Evolving networks Network diffusion Pattern formation patterns in complex systems

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Mixing patterns and individual differences in networks

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Physical Review E 2019年第4期99卷 042306-042306页

作者： George T. Cantwell M. E. J. Newman Department of Physics University of Michigan Ann Arbor Michigan 48109 USA Center for the Study of Complex Systems University of Michigan Ann Arbor Michigan 48109 USA

We study mixing patterns in networks, meaning the propensity for nodes of different kinds to connect to one another. The phenomenon of assortative mixing, whereby nodes prefer to connect to others that are similar to themselves, has been widely studied, but here we go further and examine how and to what extent nodes that are otherwise similar can have different preferences. Many individuals in a friendship network, for instance, may prefer friends who are roughly the same age as themselves, but some may display a preference for older or younger friends. We introduce a network model that captures this behavior and a method for fitting it to empirical network data. We propose metrics to characterize the mean and variation of mixing patterns and show how to infer their values from the fitted model, either using maximum-likelihood estimates of model parameters or in a Bayesian framework that does not require fixing any parameters.

关键词： Clustering Community structure patterns in complex systems Real world networks Block models

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Generic patterns in the evolution of urban water networks: Evidence from a large Asian city

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Physical Review E 2017年第3期95卷 032312-032312页

作者： Elisabeth Krueger Christopher Klinkhamer Christian Urich Xianyuan Zhan P. Suresh C. Rao Lyles School of Civil Engineering 550 Stadium Mall Drive Purdue University West Lafayette Indiana 47907 USA Helmholtz Centre for Environmental Research–UFZ Permoserstr. 15 04318 Leipzig Germany Monash Infrastructure (MI) Research Institute Department of Civil Engineering 23 College Walk Monash University Clayton VIC 3800 Australia Department of Agronomy Purdue University West Lafayette Indiana 47907 USA

We examine high-resolution urban infrastructure data using every pipe for the water distribution network (WDN) and sanitary sewer network (SSN) in a large Asian city (≈4 million residents) to explore the structure as well as the spatial and temporal evolution of these infrastructure networks. Network data were spatially disaggregated into multiple subnets to examine intracity topological differences for functional zones of the WDN and SSN, and time-stamped SSN data were examined to understand network evolution over several decades as the city expanded. Graphs were generated using a dual-mapping technique (Hierarchical Intersection Continuity Negotiation), which emphasizes the functional attributes of these networks. Network graphs for WDNs and SSNs are characterized by several network topological metrics, and a double Pareto (power-law) model approximates the node-degree distributions of both water infrastructure networks (WDN and SSN), across spatial and hierarchical scales relevant to urban settings, and throughout their temporal evolution over several decades. These results indicate that generic mechanisms govern the networks’ evolution, similar to those of scale-free networks found in nature. Deviations from the general topological patterns are indicative of (1) incomplete establishment of network hierarchies and functional network evolution, (2) capacity for growth (expansion) or densification (e.g., in-fill), and (3) likely network vulnerabilities. We discuss the implications of our findings for the (re-)design of urban infrastructure networks to enhance their resilience to external and internal threats.

关键词： Engineering patterns in complex systems Scaling laws of complex systems

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Control of the chirality of spiral waves and recreation of spatial excitation patterns through optogenetics

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Physical Review E 2022年第1期105卷 014214-014214页

作者： Teng-Chao Li Wei Zhong Bao-quan Ai Alexander V. Panfilov Hans Dierckx KU Leuven Campus Kortrijk-Kulak Department of Mathematics Etienne Sabbelaan 53 8500 Kortrijk Belgium and iSi Health - KU Leuven Institute of Physics-based Modeling for In Silico Health KU Leuven Belgium

Spiral waves lead to dangerous arrhythmias in the cardiac system. In 2015 Burton et al. demonstrated the reversal of the spiral wave chirality through the rotating spiral-shaped illumination on the optogenetically modified cardiac monolayers. We show that this process entails the recreation of a spiral wave. We show how this methodology can be used to control and create the desired spatial excitation pattern. We found that the control is sensitive to the area of illuminated region but independent of the phase difference of the existing spiral wave and the applied spiral-shaped light. We also discovered that our methodology can temporarily resynchronize a turbulent system. The results offer numerical evidence for the control of spatial pattern in biological excitable systems with optogenetics.

关键词： Cardiac dynamics Control & applications of chaos patterns in complex systems Spiral & scroll waves

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