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The Curie-Weiss model is an exactly soluble model of ferromagnetism that allows one to study in detail the thermodynamic functions, in particular their properties in the neighbourhood of the critical temperature. In this model every…

Statistical Mechanics · Physics 2021-10-15 Martin Kochmański , Tadeusz Paszkiewicz , Sławomir Wolski

Ising machines are a form of quantum-inspired processing-in-memory computer which has shown great promise for overcoming the limitations of traditional computing paradigms while operating at a fraction of the energy use. The process of…

Optimization and Control · Mathematics 2025-07-18 Isaac K. Martin , Andrew G. Moore , John T. Daly , Jess J. Meyer , Teresa M. Ranadive

We study the asymptotic scaling of the entanglement of a block of spins for the ground state of the one-dimensional quantum Ising model with transverse field. When the field is sufficiently strong, the entanglement grows at most…

Quantum Physics · Physics 2009-11-13 Geoffrey Grimmett , Tobias Osborne , Petra Scudo

We propose a new class of models for variable clustering called Asymptotic Independent block (AI-block) models, which defines population-level clusters based on the independence of the maxima of a multivariate stationary mixing random…

Statistics Theory · Mathematics 2024-07-08 Alexis Boulin , Elena Di Bernardino , Thomas Laloë , Gwladys Toulemonde

Among the Renormalization Group Theory scaling rules relating critical exponents, there are hyperscaling rules involving the dimension of the system. It is well known that in Ising models hyperscaling breaks down above the upper critical…

Disordered Systems and Neural Networks · Physics 2018-01-24 P. H. Lundow , I. A. Campbell

We investigate the Ising and Heisenberg models using the Block Renormalization Group Method (BRGM), focusing on its behavior across different system sizes. The BRGM reduces the number of spins by a factor of 1/2 (1/3) for the Ising…

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical…

Disordered Systems and Neural Networks · Physics 2017-04-12 Nikolaos G. Fytas , Victor Martin-Mayor , Marco Picco , Nicolas Sourlas

In the literature, there are five distinct, fragmented sets of analytic predictions for the scaling behaviour at the phase transition in the random-site Ising model in four dimensions. Here, the scaling relations for logarithmic corrections…

Statistical Mechanics · Physics 2015-05-14 A. Gordillo-Guerrero , R. Kenna , J. J. Ruiz-Lorenzo

Theoretical and computational tools that can be used in the clinic to predict neoplastic progression and propose individualized optimal treatment strategies to control cancer growth is desired. To develop such a predictive model, one must…

Cell Behavior · Quantitative Biology 2015-05-20 Salvatore Torquato

We implement a two-stage approach of the Wang-Landau algorithm to investigate the critical properties of the 3D Ising model with quenched bond randomness. In particular, we consider the case where disorder couples to the nearest-neighbor…

Statistical Mechanics · Physics 2011-06-03 P. E. Theodorakis , N. G. Fytas

We study the ground-state properties of a quantum "sunburst model", composed of a quantum Ising spin-ring in a transverse field, symmetrically coupled to a set of ancillary isolated qubits, to maintain a residual translation invariance and…

Statistical Mechanics · Physics 2022-05-11 Alessio Franchi , Davide Rossini , Ettore Vicari

We study the d-dimensional random Ising model using a Bethe-Peierls approximation in the framework of the replica method. We take into account the correct interaction only inside replicated clusters of spins. Our ansatz is that the…

Condensed Matter · Physics 2009-10-28 M. Serva , G. Paladin

We address the inverse problem for the mean-field Ising model with two- and three-body interactions using a Bayesian framework. Parameter recovery in this setting is notoriously difficult, particularly near phase transitions, at…

Methodology · Statistics 2025-11-03 Godwin Osabutey , Robert Richardson , Garritt L. Page

We propose a hybrid quantum-classical algorithm to compute approximate solutions of binary combinatorial problems. We employ a shallow-depth quantum circuit to implement a unitary and Hermitian operator that block-encodes the weighted…

Quantum Physics · Physics 2023-06-16 Natacha Kuete Meli , Florian Mannel , Jan Lellmann

We consider the problem of clustering (or reconstruction) in the stochastic block model, in the regime where the average degree is constant. For the case of two clusters with equal sizes, recent results by Mossel, Neeman and Sly, and by…

Probability · Mathematics 2014-04-28 Joe Neeman , Praneeth Netrapalli

We reconsider Ising spins in a Gaussian random field within the replica formalism. The corresponding continuum model involves several coupling constants beyond the single one which was considered in the standard $\phi^4$ theory approach.…

Condensed Matter · Physics 2009-10-31 E. Brézin , C. De Dominicis

We introduce a class of damage models on regular lattices with isotropic interactions, as e.g. quasistatic fiber bundles. The system starts intact with a surface-energy threshold required to break any cell sampled from an uncorrelated…

Statistical Mechanics · Physics 2009-11-10 Renaud Toussaint , Steven R. Pride

The inverse Ising problem seeks to reconstruct the parameters of an Ising Hamiltonian on the basis of spin configurations sampled from the Boltzmann measure. Over the last decade, many applications of the inverse Ising problem have arisen,…

Disordered Systems and Neural Networks · Physics 2017-09-13 Johannes Berg

We study nucleation dynamics of Ising model in a topology that consists of two coupled random networks, thereby mimicking the modular structure observed in real-world networks. By introducing a variant of a recently developed forward flux…

Statistical Mechanics · Physics 2015-05-27 Hanshuang Chen , Zhonghuai Hou

Inverse problems in statistical physics are motivated by the challenges of `big data' in different fields, in particular high-throughput experiments in biology. In inverse problems, the usual procedure of statistical physics needs to be…

Disordered Systems and Neural Networks · Physics 2017-11-07 H. Chau Nguyen , Riccardo Zecchina , Johannes Berg