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Simulating a network of Ising spins with physical systems is now emerging as a promising approach for solving mathematically intractable problems. Here we report a large-scale network of artificial spins based on degenerate optical…

The resolution of geometric frustration in systems with continuous degrees of freedom often involves a cooperative inhomogeneous response and super-extensive energy scaling. In contrast, the frustration in frustrated Ising-like spin systems…

Soft Condensed Matter · Physics 2022-06-29 Snir Meiri , Efi Efrati

The frustration properties of the Ising model on a one-dimensional monoatomic equidistant lattice are investigated taking into account the exchange interactions of atomic spins at the sites of the first (nearest), second (next-nearest) and…

Statistical Mechanics · Physics 2022-06-22 A. V. Zarubin , F. A. Kassan-Ogly , A. I. Proshkin

The Ising machine is an unconventional computing architecture that can be used to solve NP-hard combinatorial optimization problems more efficiently than traditional von Neumann architectures. Fast, compact oscillator networks which provide…

Computational Physics · Physics 2021-10-20 Brooke C. McGoldrick , Jonathan Z. Sun , Luqiao Liu

The study of quantum frustrated systems remains one of the most challenging subjects of quantum magnetism, as they can hold quantum spin liquids, whose characterization is quite elusive. The presence of gapped quantum spin liquids…

Strongly Correlated Electrons · Physics 2019-10-16 D. Castells-Graells , A. Yuste , A. Sanpera

Ising machines (IM) are physics-inspired alternatives to von Neumann architectures for solving hard optimization tasks. By mapping binary variables to coupled Ising spins, IMs can naturally solve unconstrained combinatorial optimization…

Emerging Technologies · Computer Science 2025-08-01 Corentin Delacour

A network of optical parametric oscillators is used to simulate classical Ising and XY spin chains. The collective nonlinear dynamics of this network, driven by quantum noise rather than thermal fluctuations, seeks out the Ising / XY ground…

The Ising model is an equilibrium stochastic process used as a model in several branches of science including magnetic materials, geophysics, neuroscience, sociology and finance. Real systems of interest have finite size and a fixed…

Statistical Mechanics · Physics 2021-11-10 Konstantin Klemm

Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering ferromagnetism, combinatorial optimization, protein folding, stock market dynamics, and social dynamics.…

Disordered Systems and Neural Networks · Physics 2016-08-24 David Dahmen , Hannah Bos , Moritz Helias

Realizing compact and scalable Ising machines that are compatible with CMOS-process technology is crucial to the effectiveness and practicality of using such hardware platforms for accelerating computationally intractable problems. Besides…

Small-world networks provide an interesting framework for studying the interplay between regular and random graphs, where links are located in a regular and random way, respectively. On one hand, the random links make the model to obey some…

Statistical Mechanics · Physics 2024-04-12 M. Ostilli

We explore a case example of networks of classical electronic oscillators evolving towards the solution of complex optimization problems. We show that when driven into subharmonic response, a network of such nonlinear electrical resonators…

Pattern Formation and Solitons · Physics 2022-04-04 L. Q. English , A. V. Zampetaki , K. P. Kalinin , N. G. Berloff , P. G. Kevrekidis

We present a method to analyze magnetic properties of frustrated Ising spin models on specific hierarchical lattices with random dilution. Disorder is induced by dilution and geometrical frustration rather than randomness in the internal…

Disordered Systems and Neural Networks · Physics 2013-08-13 Jean-Yves Fortin

It was recently proposed that neural networks could be used to approximate many-dimensional probability distributions that appear e.g. in lattice field theories or statistical mechanics. Subsequently they can be used as variational…

Statistical Mechanics · Physics 2022-11-17 Piotr Białas , Piotr Korcyl , Tomasz Stebel

Standard Monte Carlo cluster algorithms have proven to be very effective for many different spin models, however they fail for frustrated spin systems. Recently a generalized cluster algorithm was introduced that works extremely well for…

Condensed Matter · Physics 2009-10-22 P. D. Coddington , L. Han

In 1977, G\'erard Toulouse has proposed a new concept termed as "frustration" in spin systems. Using this definition, several frustrated models have been created and studied, among them we can mention the Villain's model, the fully…

Statistical Mechanics · Physics 2025-01-22 Hung T. Diep

The Ising model, often seen as the paradigmatic spin model, has been heavily studied for its mathematical description of ferromagnetism in statistical mechanics. We explore a quantum version of this model, the transverse field Ising model,…

Statistical Mechanics · Physics 2023-11-09 Abhiraj Jalagekar

We report on a systematic study of two dimensional, periodic, frustrated Ising models with a quantum dynamics introduced via a transverse magnetic field. The systems studied are the triangular and kagome lattice antiferromagnets, fully…

Statistical Mechanics · Physics 2009-10-31 R. Moessner , S. L. Sondhi

We map a geometrically frustrated Ising system with transversal field generated quantum dynamics to a strongly anisotropic lattice of non-crossing elastic strings. The combined effect of frustration, quantum and thermal spin fluctuations is…

Statistical Mechanics · Physics 2007-05-23 Ying Jiang , Thorsten Emig

Antiferromagnetic Ising models on frustrated lattices can realize classical spin liquids, with highly degenerate ground states and, possibly, fractionalized excitations and emergent gauge fields. Motivated by the recent interest in…

Strongly Correlated Electrons · Physics 2025-11-05 Fabian Köhler , Johanna Erdmenger , Roderich Moessner , Matthias Vojta