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We study Bosonic representation of spin Ising model with the application of simulating two level systems using continuous variable quantum processors. We decompose the time evolution of spin systems into a sequence of continuous variable…

Quantum Physics · Physics 2020-09-29 Razieh Annabestani , Brajesh Gupt , Bhaskar Roy Bardhan

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

Spin glasses are paradigmatic models that deliver concepts relevant for a variety of systems. However, rigorous analytical results are difficult to obtain for spin-glass models, in particular for realistic short-range models. Therefore…

Disordered Systems and Neural Networks · Physics 2008-02-12 Helmut G. Katzgraber

Studying high-energy collisions of composite particles, such as hadrons and nuclei, is an outstanding goal for quantum simulators. However, preparation of hadronic wave packets has posed a significant challenge, due to the complexity of…

The Ising model provides a natural mapping for many computationally hard combinatorial optimization problems (COPs). Consequently, dynamical system-inspired computing models and hardware platforms that minimize the Ising Hamiltonian, have…

Dynamical Systems · Mathematics 2022-11-11 Mohammad Khairul Bashar , Nikhil Shukla

A linear-time algorithm is presented for the construction of the Gibbs distribution of configurations in the Ising model, on a quantum computer. The algorithm is designed so that each run provides one configuration with a quantum…

Quantum Physics · Physics 2009-10-30 Daniel A. Lidar , Ofer Biham

We study the complexity of classically sampling from the output distribution of an Ising spin model, which can be implemented naturally in a variety of atomic, molecular, and optical systems. In particular, we construct a specific example…

Quantum Physics · Physics 2017-09-20 Bill Fefferman , Michael Foss-Feig , Alexey V. Gorshkov

We study the role of Hamiltonian complexity in the performance of quantum annealers. We consider two general classes of annealing Hamiltonians: stoquastic ones, which can be simulated efficiently using the quantum Monte Carlo algorithm, and…

Quantum Physics · Physics 2017-05-16 L. Hormozi , E. W. Brown , G. Carleo , M. Troyer

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

The "folding algorithm"\cite{fold1} is a matrix product state algorithm for simulating quantum systems that involves a spatial evolution of a matrix product state. Hence, the computational effort of this algorithm is controlled by the…

Quantum Physics · Physics 2015-03-18 M. B. Hastings , R. Mahajan

We propose a general learning algorithm for solving optimization problems, based on a simple strategy of trial and adaptation. The algorithm maintains a probability distribution of possible solutions (configurations), which is updated…

adap-org · Physics 2009-10-30 Kan Chen

The challenge posted by modern science is to find a way to compute the NP-hard problem. Here we present a coherent computation model based on the whispering-gallery mode micro-resonators. We introduce the optically connected…

Optics · Physics 2022-06-28 Yong-Pan Gao , Peng-Fei Lu , Chuan Wang

Gain-dissipative systems of various physical origin have recently shown the ability to act as analogue minimisers of hard combinatorial optimisation problems. Whether or not these proposals will lead to any advantage in performance over the…

Mesoscale and Nanoscale Physics · Physics 2020-03-23 Kirill P. Kalinin , Alberto Amo , Jacqueline Bloch , Natalia G. Berloff

In this paper, we address two minimal controllability problems, where the goal is to determine a minimal subset of state variables in a linear time-invariant system to be actuated to ensure controllability under additional constraints.…

Optimization and Control · Mathematics 2016-04-20 Sergio Pequito , Guilherme Ramos , Soummya Kar , A. Pedro Aguiar , Jaime Ramos

Energy minimization of Ising spin-glasses has played a central role in statistical and solid-state physics, facilitating studies of phase transitions and magnetism. Recent proposals suggest using Ising spin-glasses for non-traditional…

Quantum Physics · Physics 2013-06-20 Hector J. Garcia , Igor L. Markov

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

Hierarchical spin-glasses are Ising spin models defined by recursively coupling together two equally-sized sub-systems. In this work a new hierarchical spin system is introduced wherein the sub-systems are recursively coupled together…

Disordered Systems and Neural Networks · Physics 2023-04-05 Gavin S Hartnett

Quantum or quantum-inspired Ising machines have recently shown promise in solving combinatorial optimization problems in a short time. Real-world applications, such as time division multiple access (TDMA) scheduling for wireless multi-hop…

Emerging Technologies · Computer Science 2025-04-03 Yohei Hamakawa , Tomoya Kashimata , Masaya Yamasaki , Kosuke Tatsumura

We introduce an exact algorithm for the computation of spin correlation functions for the two dimensional +/-J Ising spin glass in the ground state. Unlike with the transfer matrix method, there is no particular restriction on the shape of…

Disordered Systems and Neural Networks · Physics 2007-05-23 J. Poulter , J. A. Blackman

We introduce a novel framework for simulating spin models using differentiable programming, an approach that leverages the advancements in machine learning and computational efficiency. We focus on three distinct spin systems: the Ising…

Statistical Mechanics · Physics 2024-05-28 Tiago de Souza Farias , Vitor Vaz Schultz , José Carlos Merino Mombach , Jonas Maziero
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