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In various disordered systems or non-equilibrium dynamical models, the large deviations of some observables have been found to display different scalings for rare values bigger or smaller than the typical value. In the present paper, we…

Statistical Mechanics · Physics 2021-05-12 Cecile Monthus

Field theoretic renormalization group and the operator product expansion are applied to a model of a passive scalar field, advected by the Gaussian strongly anisotropic velocity field. Inertial-range anomalous scaling behavior is…

Chaotic Dynamics · Physics 2016-11-22 L. Ts. Adzhemyan , N. V. Antonov , M. Hnatič , S. V. Novikov

Various real-life networks of current interest are simultaneously scale-free and modular. Here we study analytically the average distance in a class of deterministically growing scale-free modular networks. By virtue of the recursive…

Physics and Society · Physics 2010-12-09 Zhongzhi Zhang , Yuan Lin , Shuigeng Zhou , Zhigang Wang , Jihong Guan

The mean-field limit of a Markovian model describing the interaction of several classes of permanent connections in a network is analyzed. Each of the connections has a self-adaptive behavior in that its transmission rate along its route…

Probability · Mathematics 2009-12-15 Carl Graham , Philippe Robert

This paper deals with the derivation of the mean-field limit for multi-agent systems on a large class of sparse graphs. More specifically, the case of non-exchangeable multi-agent systems consisting of non-identical agents is addressed. The…

Probability · Mathematics 2025-11-21 Pierre-Emmanuel Jabin , David Poyato , Juan Soler

We apply statistical physics to study the task of resource allocation in random networks with limited bandwidths along the transportation links. The mean-field approach is applicable when the connectivity is sufficiently high. It allows us…

Statistical Mechanics · Physics 2015-05-13 C. H. Yeung , K. Y. Michael Wong

Detecting and quantifying non-equilibrium activity is essential for studying internally driven assemblies, including synthetic active matter and complex living systems such as cells or tissue. We discuss a non-invasive approach of measuring…

Biological Physics · Physics 2019-05-22 Grzegorz Gradziuk , Federica Mura , Chase P. Broedersz

Allometric scaling can reflect underlying mechanisms, dynamics and structures in complex systems; examples include typical scaling laws in biology, ecology and urban development. In this work, we study allometric scaling in scientific…

Physics and Society · Physics 2017-03-10 Hongguang Dong , Menghui Li , Ru Liu , Chensheng Wu , Jinshan Wu

A class of models with applications to swarm behavior as well as many other types of spatially extended complex biological and physical systems is studied. Internal fluctuations can play an active role in the organization of the phase…

adap-org · Physics 2008-02-03 Mark M. Millonas

Most real-world networks are endowed with the small-world property, by means of which the maximal distance between any two of their nodes scales logarithmically rather than linearly with their size. The evidence sparkled a wealth of studies…

Physics and Society · Physics 2023-04-21 Tanu Raghav , Stefano Boccaletti , Sarika Jalan

An annealed version of the quenched mean-field model for epidemic spread is introduced and investigated analytically and assisted by numerical calculations. The interaction between individuals follows a prescription that is used to generate…

Populations and Evolution · Quantitative Biology 2025-01-22 K. M. Kim , M. O. Hase

An investigation of the spatial fluctuations and their manifestations in the vicinity of the quantum critical point within the framework of the renormalized $\phi^{4}$ theory is proposed. Relevant features are reported through the…

The exact determination of ground states of small systems is used in a scaling study of the random-field Ising model. While three variants of the model are found to be in the same universality class in 3 dimensions, the Gaussian and bimodal…

Disordered Systems and Neural Networks · Physics 2009-10-30 Michael R. Swift , Alan J. Bray , Amos Maritan , Marek Cieplak , Jayanth R. Banavar

In this paper we study the small-world network model of Watts and Strogatz, which mimics some aspects of the structure of networks of social interactions. We argue that there is one non-trivial length-scale in the model, analogous to the…

Statistical Mechanics · Physics 2009-10-31 M. E. J. Newman , D. J. Watts

The critical behavior of a quenched random hypercubic sample of linear size $L$ is considered, within the ``random-$T_{c}$'' field-theoretical mode, by using the renormalization group method. A finite-size scaling behavior is established…

Statistical Mechanics · Physics 2009-11-07 H. Chamati , E. Korutcheva , N. S. Tonchev

A model for the spread of an infection is analyzed for different population structures. The interactions within the population are described by small world networks, ranging from ordered lattices to random graphs. For the more ordered…

Adaptation and Self-Organizing Systems · Physics 2009-10-31 Marcelo Kuperman , Guillermo Abramson

We discuss the short-time behavior of the majority vote dynamics on scale-free networks at the critical threshold. We introduce a heterogeneous mean-field theory on the critical short-time behavior of the majority-vote model on scale-free…

Statistical Mechanics · Physics 2024-05-24 D. S. M. Alencar , J. F. S. Neto , T. F. A. Alves , F. W. S. Lima , R. S. Ferreira , G. A. Alves , A. Macedo-Filho

We establish a relationship between the Small-World behavior found in complex networks and a family of Random Walks trajectories using, as a linking bridge, a maze iconography. Simple methods to generate mazes using Random Walks are…

Disordered Systems and Neural Networks · Physics 2009-11-07 Bartolo Luque , Miramontes Octavio

Recently there have been a tremendous interest in models of networks with a power-law distribution of degree -- so called "scale-free networks." It has been observed that such networks, normally, have extremely short path-lengths, scaling…

Disordered Systems and Neural Networks · Physics 2007-05-23 Petter Holme

Mean-Field is an efficient way to approximate a posterior distribution in complex graphical models and constitutes the most popular class of Bayesian variational approximation methods. In most applications, the mean field distribution…

Machine Learning · Computer Science 2015-02-23 Pierre Baqué , Jean-Hubert Hours , François Fleuret , Pascal Fua
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