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Accelerated coarse-graining (CG) algorithms for simulating heterogeneous chemical reactions on surface systems have recently gained much attention. In the present paper, we consider such an issue by investigating the oscillation behavior of…

Statistical Mechanics · Physics 2011-04-18 Ting Rao , Zhen Zhang , Zhonghuai Hou , Houwen Xin

Simulation has become the evaluation method of choice for many areas of distributing computing research. However, most existing simulation packages have several limitations on the size and complexity of the system being modeled. Fine…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-07-01 Dobre Ciprian , Cristea Valentin , Iosif C. Legrand

For optimal processing and design of entangled polymeric materials it is important to establish a rigorous link between the detailed molecular composition of the polymer and the viscoelastic properties of the macroscopic melt. We review…

Soft Condensed Matter · Physics 2015-05-27 J. T. Padding , W. J. Briels

An important challenge in theoretical ecology is to find good, coarse-grained representations of complex food webs. Here we use the approach of generalized modeling to show that it may be possible to formulate a coarse-graining algorithm…

Populations and Evolution · Quantitative Biology 2009-06-03 Thilo Gross , Ulrike Feudel

We examine microscopic mechanisms for coupling stochastic oscillators so that they display similar and correlated temporal variations. Unlike oscillatory motion in deterministic dynamical systems, complete synchronization of stochastic…

Quantitative Methods · Quantitative Biology 2009-09-29 Amitabha Nandi , G. Santhosh , R. K. Brojen Singh , Ram Ramaswamy

The emergence of synchronization in a network of coupled oscillators is a pervasive topic in various scientific disciplines ranging from biology, physics, and chemistry to social networks and engineering applications. A coupled oscillator…

Optimization and Control · Mathematics 2012-09-07 Florian Dörfler , Francesco Bullo

Large-scale graphs are widely used to represent object relationships in many real world applications. The occurrence of large-scale graphs presents significant computational challenges to process, analyze, and extract information. Graph…

Social and Information Networks · Computer Science 2019-10-11 Yu Jin , Andreas Loukas , Joseph F. JaJa

We propose a universal approach for analysis and fast simulations of stiff stochastic biochemical kinetics networks, which rests on elimination of fast chemical species without a loss of information about mesoscopic, non-Poissonian…

Molecular Networks · Quantitative Biology 2009-07-07 N. A. Sinitsyn , Nicolas Hengartner , Ilya Nemenman

In this paper, we investigate the development of generalized synchronization (GS) on typical complex networks, such as scale-free networks, small-world networks, random networks and modular networks. By adopting the auxiliary-system…

Chaotic Dynamics · Physics 2009-11-13 Shuguang Guan , Xingang Wang , Xiaofeng Gong , Kun Li , C. -H. Lai

We explore the interplay of network structure, topology, and dynamic interactions between nodes using the paradigm of distributed synchronization in a network of coupled oscillators. As the network evolves to a global steady state,…

Disordered Systems and Neural Networks · Physics 2015-06-04 Kristina Lerman , Rumi Ghosh

As it is getting increasingly difficult to achieve gains in the density and power efficiency of microelectronic computing devices because of lithographic techniques reaching fundamental physical limits, new approaches are required to…

Emerging Technologies · Computer Science 2017-07-05 Jean C. Coulombe , Mark C. A. York , Julien Sylvestre

Graph Neural Networks (GNNs) play a pivotal role in graph-based tasks for their proficiency in representation learning. Among the various GNN methods, spectral GNNs employing polynomial filters have shown promising performance on tasks…

Machine Learning · Computer Science 2025-01-09 Haipeng Ding , Zhewei Wei , Yuhang Ye

Graph learning methods have recently been receiving increasing interest as means to infer structure in datasets. Most of the recent approaches focus on different relationships between a graph and data sample distributions, mostly in…

Machine Learning · Computer Science 2020-03-23 Hermina Petric Maretic , Pascal Frossard

We have proposed an efficient parameterization method for a recent variant of the Gay-Berne potential for dissimilar and biaxial particles and demonstrated it for a set of small organic molecules. Compared to the previously proposed…

Soft Condensed Matter · Physics 2007-05-23 M. Babadi , R. Everaers , M. R. Ejtehadi

Data-based discovery of effective, coarse-grained (CG) models of high-dimensional dynamical systems presents a unique challenge in computational physics and particularly in the context of multiscale problems. The present paper offers a…

Computational Physics · Physics 2020-08-26 Sebastian Kaltenbach , Phaedon-Stelios Koutsourelakis

Stochastic modelling of complex systems plays an essential, yet often computationally intensive role across the quantitative sciences. Recent advances in quantum information processing have elucidated the potential for quantum simulators to…

Quantum Physics · Physics 2021-06-22 Thomas J. Elliott

We study jamming in granular mixtures from the novel point of view of extended hydrodynamics. Using a hard sphere binary mixture model we predict that a few large grains are expected to get caged more effectively in a matrix of small grains…

Soft Condensed Matter · Physics 2011-11-09 Supurna Sinha

Understanding the structure and dynamics of liquids is pivotal for the study of larger spatiotemporal processes, especially in glass-forming materials at low temperatures. Density scaling, observed in many molecular systems through…

Soft Condensed Matter · Physics 2024-10-29 Jaehyeok Jin , David R. Reichman , Jeppe C. Dyre , Ulf R. Pedersen

We implemented a coarse-graining procedure to construct mesoscopic models of complex molecules. The final aim is to obtain better results on properties depending on slow modes of the molecules. Therefore the number of particles considered…

Soft Condensed Matter · Physics 2009-10-31 Hendrik Meyer , Oliver Biermann , Roland Faller , Dirk Reith , Florian Mueller-Plathe

In this work, we investigate a model of an adaptive networked dynamical system, where the coupling strengths among phase oscillators coevolve with the phase states. It is shown that in this model the oscillators can spontaneously…

Disordered Systems and Neural Networks · Physics 2010-11-02 Menghui Li , Shuguang Guan , C. -H. Lai