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The equivalence between the natural minimization of energy in a dynamical system and the minimization of an objective function characterizing a combinatorial optimization problem offers a promising approach to designing dynamical…

Optimization and Control · Mathematics 2022-06-14 Antik Mallick , Mohammad Khairul Bashar , Zongli Lin , Nikhil Shukla

The Gottesman-Knill theorem says that a stabilizer circuit -- that is, a quantum circuit consisting solely of CNOT, Hadamard, and phase gates -- can be simulated efficiently on a classical computer. This paper improves that theorem in…

Quantum Physics · Physics 2009-11-10 Scott Aaronson , Daniel Gottesman

We present a methodology for generating Ising Hamiltonians of tunable complexity and with a priori known ground states based on a decomposition of the model graph into edge-disjoint subgraphs. The idea is illustrated with a spin-glass model…

Disordered Systems and Neural Networks · Physics 2018-04-17 Firas Hamze , Darryl C. Jacob , Andrew J. Ochoa , Dilina Perera , Wenlong Wang , Helmut G. Katzgraber

We consider quantum Hamiltonians of the form $H = H_0 - U \sum_j \cos(C_j)$ where $H_0$ is a quadratic function of position and momentum variables $\{x_1, p_1, x_2, p_2,...\}$ and the $C_j$'s are linear in these variables. We allow $H_0$…

Strongly Correlated Electrons · Physics 2016-02-17 Sriram Ganeshan , Michael Levin

We investigate the use of programmable optical lattices for quantum simulation of Hubbard models, determining analytic expressions for the hopping and Hubbard U, finding that they are suitable for emulating strongly correlated systems with…

Strongly Correlated Electrons · Physics 2021-12-01 J. P. Hague , L. Petit , C. MacCormick

Many combinatorial optimization problems can be mapped to finding the ground states of the corresponding Ising Hamiltonians. The physical systems that can solve optimization problems in this way, namely Ising machines, have been attracting…

Emerging Technologies · Computer Science 2017-10-16 Tianshi Wang , Jaijeet Roychowdhury

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

Many areas of chemistry are devoted to the challenge of understanding, predicting, and controlling the behavior of strongly localized electrons. Examples include molecular magnetism and luminescence, color centers in crystals,…

Chemical Physics · Physics 2022-09-08 R. Matthias Geilhufe , Jeffrey D. Rinehart

This paper investigated the problem of embedding a simple Hamiltonian Cycle with n vertices on n points inside a simple polygon. This problem seeks to embed a straight-line cycle (without bends), which does not intersect either itself or…

Computational Geometry · Computer Science 2022-08-22 Maryam Fadavian , Heidar Fadavian

Over the last couple of decades, quantum simulators have been probing quantum many-body physics with unprecedented levels of control. So far, the main focus has been on the access to novel observables and dynamical conditions related to…

Computing the ground state of Ising spin-glass models with p-spin interactions is, in general, an NP-hard problem. In this work we show that unlike in the case of the standard Ising spin glass with two-spin interactions, computing ground…

Disordered Systems and Neural Networks · Physics 2015-03-17 Creighton K. Thomas , Helmut G. Katzgraber

It has been established that local lattice spin Hamiltonians can be used for universal adiabatic quantum computation. However, the 2-local model Hamiltonians used in these proofs are general and hence do not limit the types of interactions…

Quantum Physics · Physics 2008-07-29 Jacob D. Biamonte , Peter J. Love

We study a large class of models with an arbitrary (finite) number of degrees of freedom, described by Hamiltonians which are polynomial in bosonic creation and annihilation operators, and including as particular cases n-th harmonic…

Mathematical Physics · Physics 2010-05-21 G Alvarez , F Finkel , A Gonzalez-Lopez , M A Rodriguez

Spin models are widely studied in the natural sciences, from investigating magnetic materials in condensed matter physics to studying neural networks. Previous work has demonstrated that there exist simple classical spin models that are…

Statistical Mechanics · Physics 2019-05-22 Tamara Kohler , Toby Cubitt

Many tasks in our modern life, such as planning an efficient travel, image processing and optimizing integrated circuit design, are modeled as complex combinatorial optimization problems with binary variables. Such problems can be mapped to…

We present a remarkable finding that a recently discovered [G. S. Uhrig, Phys. Rev. Lett. 98, 100504 (2007)] series of pulse sequences, designed to optimally restore coherence to a qubit in the spin-boson model of decoherence, is in fact…

Quantum Physics · Physics 2009-11-13 B. Lee , W. M. Witzel , S. Das Sarma

Learning to simulate complex physical systems from data has emerged as a promising way to overcome the limitations of traditional numerical solvers, which often require prohibitive computational costs for high-fidelity solutions. Recent…

Machine Learning · Computer Science 2026-02-12 Tai Hoang , Alessandro Trenta , Alessio Gravina , Niklas Freymuth , Philipp Becker , Davide Bacciu , Gerhard Neumann

We present different techniques to numerically solve the equations of motion for the widely studied Discrete Nonlinear Schroedinger equation (DNLS). Being a Hamiltonian system, the DNLS requires symplectic routines for an efficient…

Computational Physics · Physics 2013-04-08 Mario Mulansky

The theory of feedback integrators is extended to handle mechanical systems with nonholonomic constraints with or without symmetry, so as to produce numerical integrators that preserve the nonholonomic constraints as well as other conserved…

Dynamical Systems · Mathematics 2018-12-05 Dong Eui Chang , Matthew Perlmutter

We consider the Hamiltonians of mean-field spin glasses, which are certain random functions $H_N$ defined on high-dimensional cubes or spheres in $\mathbb R^N$. The asymptotic maximum values of these functions were famously obtained by…

Disordered Systems and Neural Networks · Physics 2024-01-23 Mark Sellke
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