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The frustrated Ising model in two dimensions is revisited. The frustration is quantified in terms of the number of non-trivial plaquettes which is invariant under the Nishimori gauge symmetry. The exact ground state energy is calculated…

High Energy Physics - Lattice · Physics 2007-05-23 K. Langfeld , M. Quandt , W. Lutz , H. Reinhardt

We show that the notion of critical droplets is central to an understanding of the nature of ground states in the Edwards-Anderson Ising model of a spin glass in arbitrary dimension. Given a specific ground state, suppose the coupling value…

Disordered Systems and Neural Networks · Physics 2024-11-25 C. M. Newman , D. L. Stein

In microfluidic systems, droplets undergo intricate deformations as they traverse flow-focusing junctions, posing a challenging task for accurate measurement, especially during short transit times. This study investigates the physical…

Using Monte Carlo simulations, we study in detail the overlap distribution for individual samples for several spin-glass models including the infinite-range Sherrington-Kirkpatrick model, short-range Edwards-Anderson models in three and…

Disordered Systems and Neural Networks · Physics 2014-10-29 Matthew Wittmann , B. Yucesoy , Helmut G. Katzgraber , J. Machta , A. P. Young

We theoretically investigate supersolidity in three-dimensional dipolar Bose-Einstein condensates. We focus on the role of trap geometry in determining the dimensionality of the resulting droplet arrays, which range from one-dimensional to…

We study universality in three-dimensional Ising spin glasses by large-scale Monte Carlo simulations of the Edwards-Anderson Ising spin glass for several choices of bond distributions, with particular emphasis on Gaussian and bimodal…

Disordered Systems and Neural Networks · Physics 2007-05-23 Helmut G. Katzgraber , Mathias Koerner , A. P. Young

We numerically study the finite-size droplet condensation-evaporation transition in two dimensions. We consider and compare two orthogonal approaches, namely at fixed temperature and at fixed density, making use of parallel multicanonical…

Statistical Mechanics · Physics 2017-01-13 Andreas Nußbaumer , Johannes Zierenberg , Elmar Bittner , Wolfhard Janke

Multicanonical ensemble simulations for the simulation of first-order phase transitions suffer from exponential slowing down. Monte Carlo autocorrelation times diverge exponentially with free energy barriers $\Delta F$, which in $L^d$ boxes…

Statistical Mechanics · Physics 2007-05-23 Thomas Neuhaus , Johannes S. Hager

We perform large scale simulations of the frustrated Ising lattice gas, a three-dimensional lattice model of a structural glass, using the parallel tempering technique. We evaluate the spin and density overlap distributions, and the…

Statistical Mechanics · Physics 2009-11-07 A. de Candia , A. Coniglio

We have argued in recent papers that Monte Carlo results for the equilibrium properties of the Edwards-Anderson spin glass in three dimensions, which had been interpreted earlier as providing evidence for replica symmetry breaking, can be…

Disordered Systems and Neural Networks · Physics 2009-10-31 Hemant Bokil , Barbara Drossel , Mike Moore

A new Monte Carlo algorithm for 2-dimensional spin glasses is presented. The use of clusters makes possible global updates and leads to a gain in speed of several orders of magnitude. As an example, we study the 2-dimensional +/-J…

Disordered Systems and Neural Networks · Physics 2009-11-07 J. Houdayer

By numerical simulations of the $3d$ Ising spin glass we find evidence that spontaneous replica symmetry breaking theory and not the droplet model describes with good accuracy the equilibrium behavior of the system.

Condensed Matter · Physics 2009-10-28 E. Marinari , G. Parisi , F. Ritort , J. Ruiz-Lorenzo

The growing demand for new microelectronic devices and pharmaceutical advancements has heightened interest in inkjet printing as a means of high-precision manufacturing technique. This study leverages data-driven analyses to optimize…

Fluid Dynamics · Physics 2025-01-24 Ali R. Hashemi , Angela M. Ares de Parga-Regalado , Pavel B. Ryzhakov

By means of extensive computer simulations we analyze in detail the two dimensional $\pm J$ Ising spin glass with ferromagnetic next-nearest-neighbor interactions. We found a crossover from ferromagnetic to ``spin glass'' like order both…

Statistical Mechanics · Physics 2009-10-31 G. Parisi , J. J. Ruiz-Lorenzo , D. Stariolo

Continuous phase transitions are catalogued into universality classes, families of systems having identical values of all the exponents governing the critical behaviour of their different physical properties. Numerical simulations have been…

Disordered Systems and Neural Networks · Physics 2007-05-23 P. O. Mari , I. A. Campbell

We use a sample-dependent analysis, based on medians and quantiles, to analyze the behavior of the overlap probability distribution of the Sherrington-Kirkpatrick and 3D Edwards-Anderson models of Ising spin glasses. We find that this…

Disordered Systems and Neural Networks · Physics 2014-09-16 A. Billoire , A. Maiorano , E. Marinari , V. Martin-Mayor , D. Yllanes

We study analytically the Ising model coupled to random lattices in dimension three and higher. The family of random lattices we use is generated by the large N limit of a colored tensor model generalizing the two-matrix model for Ising…

High Energy Physics - Theory · Physics 2012-08-27 Valentin Bonzom , Razvan Gurau , Vincent Rivasseau

This paper considers the interaction between two droplets placed on a substrate in immediate vicinity. We show here that when the two droplets are of different fluids and especially when one of the droplet is highly volatile, a wealth of…

Fluid Dynamics · Physics 2015-06-11 Mathieu Sellier , Volker Nock , Cécile Gaubert , Claude Verdier

Spin glasses featured by frustrated interactions and metastable states have important applications in chemistry, material sciences and artificial neural networks. However, the solution of the spin glass models is hindered by the…

Disordered Systems and Neural Networks · Physics 2023-10-24 Weiru Fan , Yuxuan Sun , Xingqi Xu , Da-Wei Wang , Shi-Yao Zhu , Hai-Qing Lin

Generative models based on flow matching have demonstrated remarkable success in various domains, yet they suffer from a fundamental limitation: the lack of interpretability in their intermediate generation steps. In fact these models learn…

Machine Learning · Computer Science 2025-10-27 Francesco Pivi , Simone Gazza , Davide Evangelista , Roberto Amadini , Maurizio Gabbrielli