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We simulate the dynamical spin structure factor (DSSF) $\mathcal{S}({q},\omega)$ of the spin-1/2 Heisenberg antiferromagnetic chain using classical simulations. By employing Landau-Lifshitz Dynamics, we emulate quantum correlations through…

Strongly Correlated Electrons · Physics 2026-01-15 Chaebin Kim , Martin Mourigal

We present a realistic study for electronic and magnetic properties in dilute magnetic semiconductor (Ga,Mn)As. A multi-orbital Haldane-Anderson model parameterized by density-functional calculations is presented and solved with the…

We propose that a combination of the semiclassical approximation with Monte Carlo simulations can be an efficient and reliable impurity solver for dynamical mean field theory equations and their cluster extensions with large cluster sizes.…

Strongly Correlated Electrons · Physics 2015-06-15 Hunpyo Lee , Yu-Zhong Zhang , Hoonkyung Lee , Yongkyung Kwon , Harald O. Jeschke , Roser Valenti

Hamiltonian simulation is one of the most promising paths toward quantum advantage. Most prior approaches to Hamiltonian simulation circuit synthesis focus on local rewrite rules and low-level optimizations, and give limited attention to…

Quantum Physics · Physics 2026-04-22 Mulundano Machiya , Matt Menickelly , Paul Hovland , Ji Liu

We present a systematic study of the anisotropic spin-1/2 Heisenberg model in staggered magnetic fields in two dimensions (2D). To mimic real materials, we consider a system of coupled, antiferromagnetic chains, whose interchain interaction…

Statistical Mechanics · Physics 2011-10-17 Bin Xi , Shijie Hu , Jize Zhao , Gang Su , B. Normand , Xiaoqun Wang

The classical, square lattice, uniaxially anisotropic Heisenberg antiferromagnet in a magnetic field parallel to the easy axis is studied using Monte Carlo techniques. The model displays a long-range ordered antiferromagnetic, an…

Statistical Mechanics · Physics 2007-05-23 M. Holtschneider , W. Selke , R. Leidl

We propose a sampling-based framework for finite-horizon trajectory and policy optimization under differentiable dynamics by casting controller design as inference. Specifically, we minimize a KL-regularized expected trajectory cost, which…

Machine Learning · Computer Science 2026-05-12 Heng Yang

Quantum Monte Carlo is used to investigate the possibility of d_{x^2-y^2} superconductivity in the two-dimensional repulsive Hubbard model. A small energy scale relevant to possible pairing requires a care (i.e., sufficiently small level…

Strongly Correlated Electrons · Physics 2009-10-30 Kazuhiko Kuroki , Hideo Aoki

Standard quantum amplitude estimation algorithms provide quadratic speedup to Monte-Carlo simulations but require a circuit depth that scales as inverse of the estimation error. In view of the shallow depth in near-term devices, the…

Quantum Physics · Physics 2024-10-03 Dinh-Long Vu , Bin Cheng , Patrick Rebentrost

Stochastic quantization is applied to derivation of the equations for the Wilson loops and generating functionals of the Wilson loops in the large-N limit. These equations are treated both in the coordinate and momentum representations. In…

High Energy Physics - Theory · Physics 2009-10-30 D. V. Antonov

We use quantum Monte Carlo methods to demonstrate that the quantum phase diagram of the S=1 Heisenberg model with uniaxial anisotropy contains an extended supersolid phase. We also show that this Hamiltonian is a particular case of a more…

Strongly Correlated Electrons · Physics 2009-11-13 P. Sengupta , C. D. Batista

Quantum Tunneling is ubiquitous across different fields, from quantum chemical reactions, and magnetic materials to quantum simulators and quantum computers. While simulating the real-time quantum dynamics of tunneling is infeasible for…

Quantum Physics · Physics 2017-10-17 Guglielmo Mazzola , Vadim N. Smelyanskiy , Matthias Troyer

A treatment of direct simulation Monte Carlo method (DSMC) as a Markov process with a master equation is given and the corresponding master equation is derived. A hierarchy of equations for the reduced probability distributions is derived…

Statistical Mechanics · Physics 2007-09-21 Hasan Karabulut , Huriye Ariman Karabulut

An efficient Path Integral Monte Carlo procedure is proposed to simulate the behavior of quantum many-body dissipative systems described within the framework of the influence functional. Thermodynamic observables are obtained by Monte Carlo…

Statistical Mechanics · Physics 2009-11-07 Luca Capriotti , Alessandro Cuccoli , Andrea Fubini , Valerio Tognetti , Ruggero Vaia

Random-walk Monte Carlo simulations are widely used to predict the optical properties of complex, disordered materials. In presence of large heterogeneities (e.g., spatially-extended nonscattering regions in a turbid environment), an…

Optics · Physics 2025-04-10 Loïc Tran , Benjamin Askenazi , Kevin Vynck

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial…

Computational Physics · Physics 2010-11-22 John Robert Trail , Ryo Maezono

High order perturbation theory has seen an unexpected recent revival for controlled calculations of quantum many-body systems, even at strong coupling. We adapt integration methods using low-discrepancy sequences to this problem. They…

Strongly Correlated Electrons · Physics 2020-08-27 Marjan Maček , Philipp T. Dumitrescu , Corentin Bertrand , Bill Triggs , Olivier Parcollet , Xavier Waintal

We introduce a theoretical approach to study the quantum-dissipative dynamics of electronic excitations in macromolecules, which enables to perform calculations in large systems and cover long time intervals. All the parameters of the…

Mesoscale and Nanoscale Physics · Physics 2016-07-20 S. A Beccara , F. Mascherpa , E. Schneider , P. Faccioli

Recent discovery of several van der waals magnetic material and moire magnet introduce to us an extremely challenging and revolutionary era of 2D magnetism and correlated phenomena for low dimensional material.More often the simplest spin…

Statistical Mechanics · Physics 2023-06-06 Nepal Banerjee

With the goal to provide absolute lower bounds for the best possible running times that can be achieved by $(1+\lambda)$-type search heuristics on common benchmark problems, we recently suggested a dynamic programming approach that computes…

Neural and Evolutionary Computing · Computer Science 2021-02-24 Kirill Antonov , Maxim Buzdalov , Arina Buzdalova , Carola Doerr
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