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Population annealing is an efficient sequential Monte Carlo algorithm for simulating equilibrium states of systems with rough free energy landscapes. The theory of population annealing is presented, and systematic and statistical errors are…

Disordered Systems and Neural Networks · Physics 2015-12-21 Wenlong Wang , Jonathan Machta , Helmut G. Katzgraber

The ubiquitous occurrence of cluster patterns in nature still lacks a comprehensive understanding. It is known that the dynamics of many such natural systems is captured by ensembles of Stuart-Landau oscillators. Here, we investigate…

Pattern Formation and Solitons · Physics 2019-02-13 Felix P. Kemeth , Sindre W. Haugland , Katharina Krischer

Finding the conditions that foster synchronization in networked oscillatory systems is critical to understanding a wide range of biological and mechanical systems. However, the conditions proved in the literature for synchronization in…

Systems and Control · Computer Science 2018-05-09 Zahra Aminzare , Biswadip Dey , Elizabeth N. Davison , Naomi Ehrich Leonard

We develop a novel method based in the sparse random graph to account the interplay between geometric frustration and disorder in cluster magnetism. Our theory allows to introduce the cluster network connectivity as a controllable…

Statistical Mechanics · Physics 2021-05-12 Alexandre Silveira , R. Erichsen , S. G. Magalhaes

In this work a robust clustering algorithm for stationary time series is proposed. The algorithm is based on the use of estimated spectral densities, which are considered as functional data, as the basic characteristic of stationary time…

Cluster algorithms are developed for simulating quantum spin systems like the one- and two-dimensional Heisenberg ferro- and anti-ferromagnets. The corresponding two- and three-dimensional classical spin models with four-spin couplings are…

High Energy Physics - Lattice · Physics 2019-06-05 U. -J. Wiese , H. -P. Ying

Cluster algorithms are developed for simulating quantum spin systems like the one- and two-dimensional Heisenberg ferro- and anti-ferromagnets. The corresponding two- and three-dimensional classical spin models with four-spin couplings are…

Condensed Matter · Physics 2009-10-22 U. -J. Wiese , H. -P. Ying

This paper considers the cluster synchronization problem of generic linear dynamical systems whose system models are distinct in different clusters. These nonidentical linear models render control design and coupling conditions highly…

Systems and Control · Electrical Eng. & Systems 2021-11-05 Zhongchang Liu , Wing Shing Wong , Hui Cheng

Given discrete degrees of freedom (spins) on a graph interacting via an energy function, what can be said about the energy local minima and associated inherent structures? Using the lid algorithm in the context of a spin glass energy…

Disordered Systems and Neural Networks · Physics 2009-11-11 Z. Burda , A. Krzywicki , O. C. Martin , Z. Tabor

Systems of globally coupled logistic maps (GCLM) can display complex collective behaviour characterized by the formation of synchronous clusters. In the dynamical clustering regime, such systems possess a large number of coexisting…

Disordered Systems and Neural Networks · Physics 2009-11-07 Susanna C. Manrubia , Ugo Bastolla , Alexander S. Mikhailov

The structure of interactions in most of animals and human societies can be best represented by complex hierarchical networks. In order to maintain close to optimal functioning both stability and adaptability are necessary. Here we…

Physics and Society · Physics 2018-02-20 Maryam Zamani , Leonardo Camargo-Forero , Tamas Vicsek

The genetic cluster-exact approximation algorithm is an efficient method to calculate ground states of EA spin glasses. The method can be used to study ground-state landscapes by calculating many independent ground states for each…

Disordered Systems and Neural Networks · Physics 2007-05-23 Alexander K. Hartmann

Due to an extremely rugged structure of the free energy landscape, the determination of spin-glass ground states is among the hardest known optimization problems, found to be NP-hard in the most general case. Owing to the specific structure…

Disordered Systems and Neural Networks · Physics 2011-11-10 Martin Weigel

Spin systems with frustration and disorder are notoriously difficult to study both analytically and numerically. While the simulation of ferromagnetic statistical mechanical models benefits greatly from cluster algorithms, these accelerated…

Disordered Systems and Neural Networks · Physics 2015-08-18 Zheng Zhu , Andrew J. Ochoa , Helmut G. Katzgraber

Using a stochastic algorithm introduced in a previous paper, we study the finite size volume corrections and the fluctuations of the ground state energy in the Sherrington-Kirkpatrick and the Edwards-Anderson models at zero temperature. The…

Disordered Systems and Neural Networks · Physics 2008-07-09 Claudio Giberti , Cecilia Vernia

Efficient extraction of useful knowledge from these data is still a challenge, mainly when the data is distributed, heterogeneous and of different quality depending on its corresponding local infrastructure. To reduce the overhead cost,…

Databases · Computer Science 2017-04-17 Nhien-An Le-Khac , M-Tahar Kechadi

The one-dimensional contact process is analyzed by a cluster approximation. In this approach, the hierarchy of rate equations for the densities of finite length empty intervals are truncated under the assumption that adjacent intervals are…

Condensed Matter · Physics 2009-10-22 E. Ben-Naim , P. L. Krapivsky

In a Newtonian system with localized interactions the whole set of particles is naturally decomposed into dynamical clusters, defined as finite groups of particles having an influence on each other's trajectory during a given interval of…

Mathematical Physics · Physics 2016-11-28 Robert I. A. Patterson , Sergio Simonella , Wolfgang Wagner

Motivated by the recent success of tensor networks to calculate the residual entropy of spin ice and kagome Ising models, we develop a general framework to study frustrated Ising models in terms of infinite tensor networks %, i.e. tensor…

Statistical Mechanics · Physics 2021-01-20 Bram Vanhecke , Jeanne Colbois , Laurens Vanderstraeten , Frank Verstraete , Frédéric Mila

A new model for a cluster of hybrid sensors network with multi sub-clusters is proposed. The model is in particular relevant to the early warning system in a large scale monitoring system in, for example, a nuclear power plant. It mainly…

Artificial Intelligence · Computer Science 2012-10-02 A. A. Waskita , H. Suhartanto , Z. Akbar , L. T. Handoko