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Real-world physical signals are continuous and high-dimensional, yet the statistical-mechanics machinery of associative memory operates on discrete Ising spins. We bridge this divide through a multilayer Ising framework that couples a…

Disordered Systems and Neural Networks · Physics 2026-05-15 Andrea Ladiana

We present an algorithm which calculates groundstates of Ising spin glasses approximately. It works by randomly selecting clusters of spins which exhibit no frustrations. The spins which were not selected, contribute to the local fields of…

Condensed Matter · Physics 2015-06-25 A. K. Hartmann

Fitting probabilistic models to data is often difficult, due to the general intractability of the partition function. We propose a new parameter fitting method, Minimum Probability Flow (MPF), which is applicable to any parametric model. We…

Machine Learning · Computer Science 2020-07-21 Jascha Sohl-Dickstein , Peter Battaglino , Michael R. DeWeese

Kinetically constrained spin models are known to exhibit dynamical behavior mimicking that of glass forming systems. They are often understood as coarse-grained models of glass formers, in terms of some "mobility" field. The identity of…

Disordered Systems and Neural Networks · Physics 2009-11-13 Matthew T. Downton , Malcolm P. Kennett

We introduce an algorithm to generate (not solve) spin-glass instances with planted solutions of arbitrary size and structure. First, a set of small problem patches with open boundaries is solved either exactly or with a heuristic, and then…

Disordered Systems and Neural Networks · Physics 2017-08-31 Wenlong Wang , Salvatore Mandrà , Helmut G. Katzgraber

We propose an optimisation method for the inverse structural design of self-assembly of anisotropic patchy particles. The anisotropic interaction can be expressed by the spherical harmonics of the surface pattern on a patchy particle, and…

Soft Condensed Matter · Physics 2025-02-21 Uyen Tu Lieu , Natsuhiko Yoshinaga

Low-frequency nonphononic modes and plastic rearrangements in glasses are spatially quasilocalized, i.e. feature a disorder-induced short-range core and known long-range decaying elastic fields. Extracting the unknown short-range core…

Soft Condensed Matter · Physics 2020-10-07 Avraham Moriel , Yuri Lubomirsky , Edan Lerner , Eran Bouchbinder

We consider two schematic models of glasses subjected to oscillatory shear deformation, motivated by the observations, in computer simulations of a model glass, of a nonequilibrium transition from a localized to a diffusive regime as the…

Statistical Mechanics · Physics 2015-05-20 Davide Fiocco , Giuseppe Foffi , Srikanth Sastry

In this work we study numerically the out of equilibrium dynamics of the Hopfield model for associative memory inside its spin-glass phase. Besides its interest as a neural network model it can also be considered as a prototype of fully…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. A. Montemurro , F. A. Tamarit , D. A. Stariolo , S. A. Cannas

Integrable systems in low dimensions, constructed through the symmetry reduction method, are studied using phase portrait and variable separation techniques. In particular, invariant quantities and explicit periodic solutions are…

solv-int · Physics 2009-10-31 J. A. Calzada , M. A. del Olmo , M. A. Rodriguez

We introduce a diluted version of the one dimensional spin-glass model with interactions decaying in probability as an inverse power of the distance. In this model varying the power corresponds to change the dimension in short-range models.…

Disordered Systems and Neural Networks · Physics 2009-11-13 L. Leuzzi , G. Parisi , F. Ricci-Tersenghi , J. J. Ruiz-Lorenzo

Plastic rearrangements play a crucial role in the characterization of soft-glassy materials, such as emulsions and foams. Based on numerical simulations of soft-glassy systems, we study the dynamics of plastic rearrangements at the…

Soft Condensed Matter · Physics 2014-10-27 R. Benzi , M. Sbragaglia , A. Scagliarini , P. Perlekar , M. Bernaschi , S. Succi , F. Toschi

We introduce Patchwork, a new general-purpose shape representation capable of modeling 2D and 3D geometry with a small number of parameters. Patchwork is grounded in a rigorous mathematical framework, providing provable complexity bounds…

Graphics · Computer Science 2026-05-19 Ruichen Zheng , Biao Zhang , Michael Birsak , Mikhail Skopenkov , Peter Wonka

Amorphous solids, such as glasses, have complex responses to deformations, with significant consequences in material design and applications. In this respect two intertwined aspects are important: stability and reversibility. It is crucial…

Soft Condensed Matter · Physics 2018-12-11 Yuliang Jin , Pierfrancesco Urbani , Francesco Zamponi , Hajime Yoshino

Critical slowing down dynamics of supercooled glass-forming liquids is usually understood at the mean-field level in the framework of Mode Coupling Theory, providing a two-time relaxation scenario and power-law behaviors of the time…

Disordered Systems and Neural Networks · Physics 2013-01-30 Ulisse Ferrari , Luca Leuzzi , Giorgio Parisi , Tommaso Rizzo

We investigate the two-dimensional frustrated quantum Heisenberg model with bond disorder on nearest-neighbor couplings using the recently introduced Foundation Neural-Network Quantum States framework, which enables accurate and efficient…

We present a comprehensive study of non-equilibrium phenomena in the low temperature phase of the Edwards-Anderson Gaussian spin glass in 3 and 4 spatial dimensions. Many effects can be understood in terms of a time dependent coherence…

Statistical Mechanics · Physics 2009-11-07 Ludovic Berthier , Jean-Philippe Bouchaud

Ground states of three-dimensional EA Ising spin glasses are calculated for sizes up to 14^3 using a combination of a genetic algorithm and cluster-exact approximation. For each realization several independent ground states are obtained.…

Disordered Systems and Neural Networks · Physics 2015-06-25 Alexander K. Hartmann

We study dynamical aspects of three--dimensional gonihedric spins by using Monte--Carlo methods. The interest of this family of models (parametrized by one self-avoidance parameter $\kappa$) lies in their capability to show remarkably slow…

Condensed Matter · Physics 2009-11-07 P. Dimopoulos , D. Espriu , E. Jané , A. Prats

We study two-dimensional Ising spins, evolving through reinforcement learning using their state, action, and reward. The state of a spin is defined as whether it is in the majority or minority with its nearest neighbours. The spin updates…

Statistical Mechanics · Physics 2022-11-22 Pranay Bimal Sampat , Ananya Verma , Riya Gupta , Shradha Mishra
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