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We present a statistical analysis of spectra of transfer matrices of classical lattice spin models; this continues the work on the eight-vertex model of the preceding paper. We show that the statistical properties of these spectra can serve…

Statistical Mechanics · Physics 2009-10-28 H. Meyer , J. -C. Anglès d'Auriac

We use the single-cluster Monte Carlo update algorithm to simulate the Ising model on two-dimensional Poissonian random lattices with up to 80,000 sites which are linked together according to the Voronoi/Delaunay prescription. In one set of…

High Energy Physics - Lattice · Physics 2009-09-25 W. Janke , M. Katoot , R. Villanova

On the base of a Feynman-Kac--type formula involving Poisson stochastic processes, recently a Monte Carlo algorithm has been introduced, which describes exactly the real- or imaginary-time evolution of many-body lattice quantum systems. We…

Other Condensed Matter · Physics 2011-07-19 Massimo Ostilli , Carlo Presilla

We study an Ising spin system coupled to a fluctuating four-dimensional $Z_2$-Regge lattice and compare with the results of the four-dimensional Ising model on a regular lattice. Particular emphasis is placed on the phase transition of the…

High Energy Physics - Lattice · Physics 2008-11-26 Elmar Bittner , Wolfhard Janke , Harald Markum

Combinatorial optimization problems are ubiquitous in industrial applications. However, finding optimal or close-to-optimal solutions can often be extremely hard. Because some of these problems can be mapped to the ground-state search of…

Quantum Physics · Physics 2025-09-04 Junpeng Hou , Amin Barzegar , Helmut G. Katzgraber

We introduce a general class of mean-field-like spin systems with random couplings that comprises both the Ising model on inhomogeneous dense random graphs and the randomly diluted Hopfield model. We are interested in quantitative estimates…

Probability · Mathematics 2024-07-10 Anton Bovier , Frank den Hollander , Saeda Marello , Elena Pulvirenti , Martin Slowik

Dynamical properties of the elliptical stadium billiard, which is a generalization of the stadium billiard and a special case of the recently introduced mushroom billiards, are investigated analytically and numerically. In dependence on two…

Chaotic Dynamics · Physics 2007-05-23 V. Lopac , I. Mrkonjic , N. Pavin , D. Radic

Monte Carlo methods are widely used importance sampling techniques for studying complex physical systems. Integrating these methods with deep learning has significantly improved efficiency and accuracy in high-dimensional problems and…

Disordered Systems and Neural Networks · Physics 2024-12-24 Yixiong Ren , Jianhui Zhou

We study classical and quantum scattering properties in the ballistic regime of particles in two-dimensional chaotic billiards that are models of electron- or micro- waveguides. To this end we construct the purely classical counterparts of…

Disordered Systems and Neural Networks · Physics 2009-11-07 J. A. Méndez-Bermúdez , G. A. Luna-Acosta , P. Šeba , K. N. Pichugin

A variety of mesoscopic systems can be represented as a billiard with a random coupling to the exterior at the boundary. Examples include quantum dots with multiple leads, quantum corrals with different kinds of atoms forming the boundary,…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 Igor Rozhkov , Ganpathy Murthy

We study the coarsening dynamics of the three-dimensional random field Ising model using Monte Carlo numerical simulations. We test the dynamic scaling and super-scaling properties of global and local two-time observables. We treat in…

Disordered Systems and Neural Networks · Physics 2009-08-12 Camille Aron , Claudio Chamon , Leticia F. Cugliandolo , Marco Picco

A novel approach called Moate Simulation is presented to provide an accurate numerical evolution of probability distribution functions represented on grids arising from stochastic differential processes where initial conditions are…

Computational Finance · Quantitative Finance 2022-12-19 Michael E. Mura

The nature of the ordering of the three-dimensional isotropic Heisenberg spin glass with nearest-neighbor random Gaussian coupling is studied by extensive Monte Carlo simulations. Several independent physical quantities are measured both…

Disordered Systems and Neural Networks · Physics 2013-05-29 Dao Xuan Viet , Hikaru Kawamura

Random non-commutative geometries are introduced by integrating over the space of Dirac operators that form a spectral triple with a fixed algebra and Hilbert space. The cases with the simplest types of Clifford algebra are investigated…

General Relativity and Quantum Cosmology · Physics 2016-06-22 John W. Barrett , Lisa Glaser

In any valid Monte Carlo sampling that realizes microcanonical property we can collect statistics for a transition matrix in energy. This matrix is used to determine the density of states, from which most of the thermodynamical averages can…

Statistical Mechanics · Physics 2009-11-10 Jian-Sheng Wang

Dilute dipolar Ising magnets remain a notoriously hard problem to tackle both analytically and numerically because of long-ranged interactions between spins as well as rare region effects. We study a new type of anisotropic dilute dipolar…

Disordered Systems and Neural Networks · Physics 2019-08-28 Tushar Kanti Bose , Roderich Moessner , Arnab Sen

We review some connections between quantum information and statistical mechanics. We focus on three sets of results for classical spin models. First, we show that the partition function of all classical spin models (including models in…

Quantum Physics · Physics 2013-12-23 Gemma De las Cuevas

Spatially homogeneous cosmological models reduce to Hamiltonian systems in a low dimensional Minkowskian space moving on the total energy shell $H=0$. Close to the initial singularity some models (those of Bianchi type VIII and IX) can be…

General Relativity and Quantum Cosmology · Physics 2015-06-25 R. Graham

The analytical description of the dynamics in models with discrete variables (e.g. Ising spins) is a notoriously difficult problem, that can be tackled only under some approximation. Recently a novel variational approach to solve the…

Disordered Systems and Neural Networks · Physics 2017-04-27 Eduardo Dominguez , Gino Del Ferraro , Federico Ricci-Tersenghi

It is shown that superefficient Monte Carlo computations can be carried out by using chaotic dynamical systems as non-uniform random-number generators. Here superefficiency means that the expectation value of the square of the error…

chao-dyn · Physics 2007-05-23 Ken Umeno