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Ionic liquids form intricate microstructures, both in the bulk and near charged surfaces. In this Letter, we show that, given the ionic positions from molecular simulations, the ionic charges minimize a "spin-glass" Hamiltonian for…

Chemical Physics · Physics 2019-05-29 Amir Levy , Michael McEldrew , Martin Z. Bazant

In the spirit of multi-scale modeling, we develop a theoretical framework for spin-lattice coupling that connects, on the one hand, to ab initio calculations of spin-lattice coupling parameters and, on the other hand, to the magneto-elastic…

Learning a many-body Hamiltonian from its dynamics is a fundamental problem in physics. In this work, we propose the first algorithm to achieve the Heisenberg limit for learning an interacting $N$-qubit local Hamiltonian. After a total…

Quantum Physics · Physics 2023-05-31 Hsin-Yuan Huang , Yu Tong , Di Fang , Yuan Su

Replica symmetry breaking postulates that near optima of spin glass Hamiltonians have an ultrametric structure. Namely, near optima can be associated to leaves of a tree, and the Euclidean distance between them corresponds to the distance…

Probability · Mathematics 2022-06-22 Antonio Auffinger , Andrea Montanari , Eliran Subag

Determining properties of ground states of spin Hamiltonians remains a topic of central relevance connecting disciplines of mathematical, theoretical and applied physics. In the last few decades, ground state properties of physical systems…

Quantum Physics · Physics 2021-12-28 Jacob Biamonte

We propose a scheme to engineer an effective spin Hamiltonian starting from a system of electrons confined in micro-Penning traps. By means of appropriate sequences of electromagnetic pulses, alternated to periods of free evolution, we…

Quantum Physics · Physics 2009-11-13 G. Ciaramicoli , I. Marzoli , P. Tombesi

We discuss the metastate, a probability measure on thermodynamic states, and its usefulness in addressing difficult questions pertaining to the statistical mechanics of systems with quenched disorder, in particular short-range spin glasses.…

Disordered Systems and Neural Networks · Physics 2007-05-23 C. M. Newman , D. L. Stein

A collective spin model is used to describe two species of mutually interacting ultracold bosonic atoms confined to a toroidal trap. The system is modeled by a Hamiltonian that can be split into two components, a linear part and a quadratic…

Quantum Gases · Physics 2024-06-05 Allison Brattley , Tomáš Opatrný , Kunal K. Das

Photonic Ising Machines constitute an emergent new paradigm of computation, geared towards tackling combinatorial optimization problems that can be reduced to the problem of finding the ground state of an Ising model. Spatial Photonic Ising…

It is natural to measure the observables from the Hamiltonian-based quantum dynamics, and its inverse process that Hamiltonians are estimated from the measured data also is a vital topic. In this work, we propose a recurrent neural network…

Quantum Physics · Physics 2021-06-30 Liangyu Che , Chao Wei , Yulei Huang , Dafa Zhao , Shunzhong Xue , Xinfang Nie , Jun Li , Dawei Lu , Tao Xin

We analyze a microscopic decoherence model in which the total system is described as a spin gas. A spin gas consists of N classically moving particles with additional, interacting quantum degrees of freedom (e.g. spins). For various…

Quantum Physics · Physics 2007-05-23 L. Hartmann , J. Calsamiglia , W. Dür , H. J. Briegel

We investigate the performance of neural networks in identifying critical behaviour in the 2D Ising model with next-to-nearest neighbour interactions. We train DNN and CNN based classifiers on the Ising model configurations with nearest…

We study the large $N$-dimensional limit of the Hessian spectrum at the global minimum of some subclasses of the spherical mixed $p$-spin models. Specifically, we show that its empirical spectral measure converges in probability to a…

Mathematical Physics · Physics 2025-07-29 Hao Xu , Haoran Yang

Quantum materials research requires co-design of theory with experiments and involves demanding simulations and the analysis of vast quantities of data, usually including pattern recognition and clustering. Artificial intelligence is a…

Other Condensed Matter · Physics 2021-11-01 A. M. Samarakoon , D. Alan Tennant , Feng Ye , Qiang Zhang , S. A. Grigera

The nature of the ordering of the three-dimensional isotropic Heisenberg spin glass with nearest-neighbor random Gaussian coupling is studied by extensive Monte Carlo simulations. Several independent physical quantities are measured both…

Disordered Systems and Neural Networks · Physics 2013-05-29 Dao Xuan Viet , Hikaru Kawamura

In this work, we study the problems of certifying and learning quantum Ising Hamiltonians. Our main contributions are as follows: Certification of Ising Hamiltonians. We show that certifying an Ising Hamiltonian in normalized Frobenius norm…

Reconstructing a quantum system's Hamiltonian from limited yet experimentally observable information is interesting both as a practical task and from a fundamental standpoint. We pose and investigate the inverse problem of reconstructing a…

Disordered Systems and Neural Networks · Physics 2025-09-12 Nisarga Paul , Andrew Ma , Kevin P. Nuckolls

We derive an explicit Hamiltonian for copying the basis up and down states of a quantum two-state system - a qubit - onto n "copy" qubits initially all prepared in the down state. In terms of spin components, for spin-1/2 particle spin…

Quantum Physics · Physics 2014-11-18 Dima Mozyrsky , Vladimir Privman , Mark Hillery

Satisfying spin-assignments in triangulations of a surface are states of minimum energy of the antiferromagnetic Ising model on triangulations which correspond (via geometric duality) to perfect matchings in cubic bridgeless graphs. In this…

Computational Complexity · Computer Science 2011-07-20 Andrea Jiménez , Marcos Kiwi

A new method to numerically calculate the $n$th moment of the spin overlap of the two-dimensional $\pm J$ Ising model is developed using the identity derived by one of the authors (HK) several years ago. By using the method, the $n$th…

Disordered Systems and Neural Networks · Physics 2009-10-31 H. Kitatani , A. Sinada
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