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Networks of optical oscillators simulating coupled Ising spins have been recently proposed as a heuristic platform to solve hard optimization problems. These networks, called coherent Ising machines (CIMs), exploit the fact that the…

Emerging Technologies · Computer Science 2021-11-15 Marcello Calvanese Strinati , Davide Pierangeli , Claudio Conti

The physics of a closed quantum mechanical system is governed by its Hamiltonian. However, in most practical situations, this Hamiltonian is not precisely known, and ultimately all there is are data obtained from measurements on the system.…

We use machine learning to classify rational two-dimensional conformal field theories. We first use the energy spectra of these minimal models to train a supervised learning algorithm. We find that the machine is able to correctly predict…

Strongly Correlated Electrons · Physics 2021-07-13 En-Jui Kuo , Alireza Seif , Rex Lundgren , Seth Whitsitt , Mohammad Hafezi

Despite the extreme simplicity in their definition, spin glasses disclose a wide variety of non-trivial behaviors that are not yet fully understood. In this thesis we try to shed light on some of them, focusing on one hand on the search of…

Disordered Systems and Neural Networks · Physics 2018-05-16 Marco Baity-Jesi

We consider Glauber dynamics of classical spin systems of Ising type in the limit when the temperature tends to zero in finite volume. We show that information on the structure of the most profound minima and the connecting saddle points of…

Disordered Systems and Neural Networks · Physics 2015-06-24 Anton Bovier , Francesco Manzo

Spin models like the Heisenberg Hamiltonian effectively describe the interactions of open-shell transition-metal ions on a lattice and can account for various properties of magnetic solids and molecules. Numerical methods are usually…

Strongly Correlated Electrons · Physics 2025-06-24 Shadan Ghassemi Tabrizi , Thomas D. Kühne

We study the critical behavior of two-dimensional short-range quantum spin glasses by numerical simulations. Using a parallel tempering algorithm, we calculate the Binder cumulant for the Ising spin glass in a transverse magnetic field with…

Statistical Mechanics · Physics 2016-07-26 D. A. Matoz-Fernandez , F. Roma

We study a Hamiltonian system describing a three-spin-1/2 cluster-like interaction competing with an Ising-like anti-ferromagnetic interaction. We compute free energy, spin correlation functions and entanglement both in the ground and in…

We use finite size scaling to study Ising spin glasses in two spatial dimensions. The issue of universality is addressed by comparing discrete and continuous probability distributions for the quenched random couplings. The sophisticated…

Disordered Systems and Neural Networks · Physics 2016-07-06 L. A. Fernandez , E. Marinari , V. Martin-Mayor , G. Parisi , J. J. Ruiz-Lorenzo

The spin-glass phase in the $\LHx$ compound is considered. At zero transverse field this system is well described by the classical Ising model. At finite transverse field deviations from the transverse field quantum Ising model are…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. Schechter , P. C. E. Stamp , N. Laflorencie

We study the coupling between collective variables of atomic spin and light polarization in an ensemble of cold 87Rb probed with polarized light. The effects of multiple hyperfine levels manifest themselves as a rank-2 tensor…

Quantum Physics · Physics 2008-03-12 S. R. de Echaniz , M. Koschorreck , M. Napolitano , M. Kubasik , M. W. Mitchell

We provide a novel Neural Network architecture that can: i) output R-matrix for a given quantum integrable spin chain, ii) search for an integrable Hamiltonian and the corresponding R-matrix under assumptions of certain symmetries or other…

High Energy Physics - Theory · Physics 2023-04-17 Shailesh Lal , Suvajit Majumder , Evgeny Sobko

We analyze changes in the thermodynamic properties of a spin system when it passes from the classical two-dimensional Ising model to the spin glass model, where spin-spin interactions are random in their values and signs. Formally, the…

Disordered Systems and Neural Networks · Physics 2020-02-06 Boris Kryzhanovsky , Magomed Malsagov , Iakov Karandashev

We introduce an intermediate quantum computing model built from translation-invariant Ising-interacting spins. Despite being non-universal, the model cannot be classically efficiently simulated unless the polynomial hierarchy collapses.…

Quantum Physics · Physics 2017-02-01 Xun Gao , Sheng-Tao Wang , Lu-Ming Duan

In this paper we develop a method introduced by one of us to study metastable states in spin glasses. We consider a `potential function' defined as the free energy of a system at a given temperature $T$ constrained to have a fixed overlap…

Condensed Matter · Physics 2009-10-28 S. Franz , G. Parisi

Suppose a quantum system starts to evolve under a Hamiltonian from some initial state. When for the first time, will an observable attain a preassigned value? To answer this question, one method often adopted is to make instantaneous…

Quantum Physics · Physics 2016-06-01 Shrabanti Dhar , Subinay Dasgupta

Starting from preferences on N proposed policies obtained via questionnaires from a sample of the electorate, an Ising spin-glass model in a field can be constructed from which a political party could find the subset of the proposed…

Disordered Systems and Neural Networks · Physics 2014-10-13 M. A. Moore , Helmut G. Katzgraber

We develop a protocol for learning a class of interacting bosonic Hamiltonians from dynamics with Heisenberg-limited scaling. For Hamiltonians with an underlying bounded-degree graph structure, we can learn all parameters with root mean…

Quantum Physics · Physics 2023-07-11 Haoya Li , Yu Tong , Hongkang Ni , Tuvia Gefen , Lexing Ying

We consider a system realized with one spinless quantum particle and an array of $N$ spins 1/2 in dimension one and three. We characterize all the Hamiltonians obtained as point perturbations of an assigned free dynamics in terms of some…

Mathematical Physics · Physics 2007-05-23 Claudio Cacciapuoti , Raffaele Carlone , Rodolfo Figari

The solution of problems in physics is often facilitated by a change of variables. In this work we present neural transformations to learn symmetries of Hamiltonian mechanical systems. Maintaining the Hamiltonian structure requires novel…

Computational Physics · Physics 2019-06-12 Roberto Bondesan , Austen Lamacraft