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Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically…

Cell Behavior · Quantitative Biology 2016-11-23 Adriano Bonforti , Salva Duran-Nebreda , Raul Montañez , Ricard Solé

We propose a statistical model for networks of event count sequences built on a cascade structure. We assume that each event triggers successor events, whose counts follow additive probability distributions; the ensemble of counts is given…

Methodology · Statistics 2019-02-18 Shinsuke Koyama , Yoshi Fujiwara

The optimal wavelet basis is used to develop quantitative, experimentally applicable criteria for self-organization. The choice of the optimal wavelet is based on the model of self-organization in the wavelet tree. The framework of the…

Mathematical Physics · Physics 2015-06-05 Milos Milovanovic , Milan Rajkovic

We use Daubechies' orthonormal compact wavelets as a variational basis for the $XY$ model in two and three dimensions. Assuming that the fluctuations of the wavelet coefficients are Gaussian and uncorrelated, minimization of the free energy…

High Energy Physics - Lattice · Physics 2009-10-22 C. Best , A. Schaefer

We study the brittle fragmentation of spheres by using a three-dimensional Discrete Element Model. Large scale computer simulations are performed with a model that consists of agglomerates of many particles, interconnected by beam-truss…

Statistical Mechanics · Physics 2009-11-13 H. A. Carmona , F. K. Wittel , F. Kun , H. J. Herrmann

Motion in a one-dimensional (1D) microfluidic array is simulated. Water droplets, dragged by flowing oil, are arranged in a single row, and due to their hydrodynamic interactions spacing between these droplets oscillates with a wave-like…

Fluid Dynamics · Physics 2015-06-05 Bin Liu , J. Goree , Yan Feng

Threshold models of global cascades have been extensively used to model real-world collective behavior, such as the contagious spread of fads and the adoption of new technologies. A common property of those cascade models is that a…

Social and Information Networks · Computer Science 2016-01-18 Teruyoshi Kobayashi

We consider the problem of estimating the latent structure of a social network based on the observed information diffusion events, or cascades, where the observations for a given cascade consist of only the timestamps of infection for…

Machine Learning · Statistics 2020-03-27 Ming Yu , Varun Gupta , Mladen Kolar

Some dynamical properties present in a problem concerning the acceleration of particles in a wave packet are studied. The dynamics of the model is described in terms of a two-dimensional area preserving map. We show that the phase space is…

Chaotic Dynamics · Physics 2011-09-14 Diego F. M. Oliveira , Marko Robnik , Edson D. Leonel

The brittle fragmentation of spheres is studied numerically by a 3D Discrete Element Model. Large scale computer simulations are performed with models that consist of agglomerates of many spherical particles, interconnected by beam-truss…

Materials Science · Physics 2015-09-04 Falk K. Wittel , Humberto A. Carmona , Ferenc Kun , Hans J. Herrmann

Disorder is more the rule than the exception in natural and synthetic materials. Nonetheless, wave propagation within inhomogeneously disordered materials has received scant attention. We combine microwave experiments and theory to find the…

Mesoscale and Nanoscale Physics · Physics 2020-02-12 Yiming Huang , Chushun Tian , Victor A. Gopar , Ping Fang , Azriel Z. Genack

The central place models are fundamentally important in theoretical geography and city planning theory. The texture and structure of central place networks have been demonstrated to be self-similar in both theoretical and empirical studies.…

Physics and Society · Physics 2018-12-20 Yanguang Chen

We introduce and study interval partition diffusions with Poisson--Dirichlet$(\alpha,\theta)$ stationary distribution for parameters $\alpha\in(0,1)$ and $\theta\ge 0$. This extends previous work on the cases $(\alpha,0)$ and…

Probability · Mathematics 2022-07-25 Noah Forman , Douglas Rizzolo , Quan Shi , Matthias Winkel

Precipitation is a complex physical process that varies in space and time. Predictions and interpolations at unobserved times and/or locations help to solve important problems in many areas. In this paper, we present a hierarchical Bayesian…

Applications · Statistics 2013-01-17 Fabio Sigrist , Hans R. Künsch , Werner A. Stahel

Modeling of phenomena such as anomalous transport via fractional-order differential equations has been established as an effective alternative to partial differential equations, due to the inherent ability to describe large-scale behavior…

Analysis of PDEs · Mathematics 2021-10-25 Jorge Suzuki , Mamikon Gulian , Mohsen Zayernouri , Marta D'Elia

Human beings learn causal models and constantly use them to transfer knowledge between similar environments. We use this intuition to design a transfer-learning framework using object-oriented representations to learn the causal…

Machine Learning · Computer Science 2020-07-21 Purva Pruthi , Javier González , Xiaoyu Lu , Madalina Fiterau

Rapid advancements in the micro and nano-technology create unlimited opportunities for design of novel optical materials and their applications. Recently, the possibility of the fast refractive index modulation was demonstrated in…

Optics · Physics 2022-06-23 V. V. Prosentsov

With the present paper we conclude the presentation of a semianalytical model of hierarchical clustering of bound virialized objects formed by gravitational instability from a random Gaussian field of density fluctuations. In paper I, we…

Astrophysics · Physics 2009-10-28 Alberto Manrique , Eduard Salvador-Sole

Remarkably persistent mixing and non-mixing regions (islands) are observed to coexist in a three-dimensional dynamical system where randomness is expected. The track of an x-ray opaque particle in a spherical shell half-filled with dry…

Soft Condensed Matter · Physics 2018-09-05 Zafir Zaman , Mengqi Yu , Paul P. Park , Julio M. Ottino , Richard M. Lueptow , Paul B. Umbanhowar

Generative models have gained popularity for their potential applications in imaging science, such as image reconstruction, posterior sampling and data sharing. Flow-based generative models are particularly attractive due to their ability…

Machine Learning · Computer Science 2023-12-14 Varun A. Kelkar , Rucha Deshpande , Arindam Banerjee , Mark A. Anastasio