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We study the low energy states of finite spin chains with isotropic (Heisenberg) and anisotropic (XY and Ising-like) exchange interaction with uniform and non-uniform coupling constants. We show that for an odd number of sites a spin…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 Florian Meier , Jeremy Levy , Daniel Loss

Clustering is grouping of data by the proximity of some properties. We report on the possibility of increasing the efficiency of clustering of points in a plane using artificial quantum neural networks after the replacement of the two-level…

Quantum Physics · Physics 2021-02-19 V. E. Zobov , I. S. Pichkovskiy

Cluster growth in a coagulating system of active particles (such as microswimmers in a solvent) is studied by theory and simulation. In contrast to passive systems, the net velocity of a cluster can have various scalings dependent on the…

Soft Condensed Matter · Physics 2014-03-21 P. Cremer , H. Löwen

Quantum spin systems with strong geometric restrictions give rise to rich quantum phases such as valence bond solids and spin liquid states. However, the geometric restrictions often hamper the application of sophisticated numerical…

Statistical Mechanics · Physics 2019-05-01 Zheng Yan , Yongzheng Wu , Chenrong Liu , Olav F. Syljuåsen , Jie Lou , Yan Chen

In the context of clustering, we assume a generative model where each cluster is the result of sampling points in the neighborhood of an embedded smooth surface; the sample may be contaminated with outliers, which are modeled as points…

Machine Learning · Statistics 2011-11-30 Ery Arias-Castro , Guangliang Chen , Gilad Lerman

Magnetic clusters, i.e., assemblies of a finite number (between two or three and several hundred) of interacting spin centers which are magnetically decoupled from their environment, can be found in many materials ranging from inorganic…

Strongly Correlated Electrons · Physics 2015-06-12 Albert Furrer , Oliver Waldmann

Spin models like the Heisenberg Hamiltonian effectively describe the interactions of open-shell transition-metal ions on a lattice and can account for various properties of magnetic solids and molecules. Numerical methods are usually…

Strongly Correlated Electrons · Physics 2025-06-24 Shadan Ghassemi Tabrizi , Thomas D. Kühne

The explosion in the amount of data available for analysis often necessitates a transition from batch to incremental clustering methods, which process one element at a time and typically store only a small subset of the data. In this paper,…

Machine Learning · Computer Science 2014-06-26 Margareta Ackerman , Sanjoy Dasgupta

A methodology is developed to identify clusters in a bulk phase which are topologically equivalent to certain reference clusters. The selected reference clusters are the Morse clusters with 13 or less atoms and the 13 atom clusters found in…

Soft Condensed Matter · Physics 2007-05-23 Stephen R. Williams

Resent achievements in statistical theory, namely, a possibility to reproduce almost unlimited Mayer's activity series based on the information about their convergence radius, on the one hand, and generalization of the lattice statistics by…

The geometrical critical behaviour of the two-dimensional Q-state Potts model is usually studied in terms of the Fortuin-Kasteleyn (FK) clusters, or their surrounding loops. In this paper we study a quite different geometrical object: the…

Statistical Mechanics · Physics 2019-01-23 Jerome Dubail , Jesper Lykke Jacobsen , Hubert Saleur

The use of combinatorial optimization algorithms has contributed substantially to the major progress that has occurred in recent years in the understanding of the physics of disordered systems, such as the random-field Ising model. While…

Disordered Systems and Neural Networks · Physics 2023-02-22 Manoj Kumar , Martin Weigel

Using the concept of finite-size scaling, Monte Carlo calculations of various models have become a very useful tool for the study of critical phenomena, with the system linear dimension as a variable. As an example, several recent studies…

Statistical Mechanics · Physics 2009-10-31 Kurt Binder , Erik Luijten , Marcus Müller , Nigel B. Wilding , Henk W. J. Blöte

For a second-order phase transition the critical energy range of interest is larger than the energy range covered by a canonical Monte Carlo simulation at the critical temperature. Such an extended energy range can be covered by performing…

Statistical Mechanics · Physics 2008-11-26 Bernd A. Berg , Wolfhard Janke

The cluster mean-field approximations are performed, up to 13 cluster sizes, to study the critical behavior of the driven pair contact process with diffusion (DPCPD) and its precedent, the PCPD in one dimension. Critical points are…

Statistical Mechanics · Physics 2007-05-23 Su-Chan Park , Hyunggyu Park

We apply a simple statistical mechanics cluster approximation for studying clustering in the Kern and Frenkel model of Janus fluids. The approach is motivated by recent Monte Carlo simulations work on the same model revealing that the vapor…

Soft Condensed Matter · Physics 2011-03-14 Riccardo Fantoni , Achille Giacometti , Francesco Sciortino , Giorgio Pastore

Currently, simulations of many-body quantum systems are known to be computationally too demanding to be solved on classical computers. The main problem is that the computation time and memory necessary for performing the calculations…

Materials Science · Physics 2021-08-04 Yadhu Krishnan Edathumkandy , Dariusz Sztenkiel

We give a uniform geometric realization for the cluster algebra of an arbitrary finite type with principal coefficients at an arbitrary acyclic seed. This algebra is realized as the coordinate ring of a certain reduced double Bruhat cell in…

Rings and Algebras · Mathematics 2008-05-19 Shih-Wei Yang , Andrei Zelevinsky

A cluster density matrix is introduced in the form suitable for the self-consistent calculation of relevant thermodynamic averages for the Ising model with spin S=1/2. On this basis, derivation of the Gibbs free-energy for the effective…

Statistical Mechanics · Physics 2007-11-20 Tadeusz Balcerzak

We present a novel framework exploiting the cascade of phase transitions occurring during a simulated annealing of the Expectation-Maximisation algorithm to cluster datasets with multi-scale structures. Using the weighted local covariance,…

Machine Learning · Statistics 2021-01-13 T. Bonnaire , A. Decelle , N. Aghanim
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