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Related papers: Random walks near Rokhsar-Kivelson points

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We develop a quantum Monte Carlo method for many fermions that allows the use of any one-particle basis. It projects out the ground state by random walks in the space of Slater determinants. An approximate approach is formulated to control…

Condensed Matter · Physics 2009-02-20 Shiwei Zhang , Henry Krakauer

We show how recent state-reconstruction techniques can be used to determine the Hamiltonian of an optical device that evolves the quantum state of radiation. A simple experimental setup is proposed for measuring the Liouvillian of…

Quantum Physics · Physics 2009-10-31 G. M. D'Ariano , L. Maccone

Quantum computers can be used to simulate nonlinear non-Hamiltonian classical dynamics on phase space by using the generalized Koopman-von Neumann formulation of classical mechanics. The Koopman-von Neumann formulation implies that the…

Quantum Physics · Physics 2020-10-27 Ilon Joseph

In order to solve quantum field theory in a non-perturbative way, Lagrangian lattice simulations have been very successful. Here we discuss a recently proposed alternative Hamiltonian lattice formulation - the Monte Carlo Hamiltonian. In…

High Energy Physics - Lattice · Physics 2007-05-23 H. Kröger , X. Q. Luo , K. J. M. Moriarty

Local Hamiltonians, $H_k$, describe non-trivial $k$-body interactions in quantum many-body systems. Here, we address the dynamical simulatability of a $k$-local Hamiltonian by a simpler one, $H_{k'}$, with $k'<k$, under the realistic…

Quantum Physics · Physics 2024-06-06 Ayaka Usui , Anna Sanpera , María García Díaz

Drawing independent samples from a probability distribution is an important computational problem with applications in Monte Carlo algorithms, machine learning, and statistical physics. The problem can in principle be solved on a quantum…

Quantum Physics · Physics 2021-09-08 Dominik S. Wild , Dries Sels , Hannes Pichler , Cristian Zanoci , Mikhail D. Lukin

In this article we study examples of systematic biases that can occur in quantum Monte Carlo methods due to the accumulation of non-linear expectation values, and approaches by which these errors can be corrected. We begin with a study of…

Strongly Correlated Electrons · Physics 2018-08-15 Nick S. Blunt , Ali Alavi , George H. Booth

Simulating quantum dynamics is one of the most important applications of quantum computers. Traditional approaches for quantum simulation involve preparing the full evolved state of the system and then measuring some physical quantity.…

Quantum Physics · Physics 2025-02-24 Rolando D. Somma , Robbie King , Robin Kothari , Thomas O'Brien , Ryan Babbush

We introduce a quantum Monte Carlo method to simulate the reversible dynamics of correlated many-body systems. Our method is based on the Laplace transform of the time-evolution operator which, as opposed to most quantum Monte Carlo…

Quantum Physics · Physics 2022-09-14 Romain Chessex , Massimo Borrelli , Hans Christian Öttinger

Identifying the real and imaginary parts of wave functions with coordinates and momenta, quantum evolution may be mapped onto a classical Hamiltonian system. In addition to the symplectic form, quantum mechanics also has a positive-definite…

Quantum Physics · Physics 2009-11-07 R. Vilela Mendes , V. I. Man'ko

Variational representations of quantum states abound and have successfully been used to guess ground-state properties of quantum many-body systems. Some are based on partial physical insight (Jastrow, Gutzwiller projected, and fractional…

Quantum Physics · Physics 2019-12-18 Douglas Hendry , Adrian E. Feiguin

We study a soliton in an optical lattice holding bosonic atoms quantum mechanically using both an exact numerical solution and quantum Monte Carlo simulations. The computation of the state is combined with an explicit account of the…

Quantum Physics · Physics 2009-11-13 Juha Javanainen , Uttam Shrestha

Hamiltonian Monte Carlo (HMC) improves the computational efficiency of the Metropolis algorithm by reducing its random walk behavior. Riemannian Manifold HMC (RMHMC) further improves HMC's performance by exploiting the geometric properties…

Computation · Statistics 2015-06-22 Shiwei Lan , Vassilios Stathopoulos , Babak Shahbaba , Mark Girolami

Recently, the use of neural quantum states for describing the ground state of many- and few-body problems has been gaining popularity because of their high expressivity and ability to handle intractably large Hilbert spaces. In particular,…

Disordered Systems and Neural Networks · Physics 2020-11-09 Vladimir Vargas-Calderón , Herbert Vinck-Posada , Fabio A. González

The kinetic Monte Carlo method is a standard approach for simulating physical systems whose dynamics are stochastic or that evolve in a probabilistic manner. Here we show how to calculate the system time for such simulations.

Computational Physics · Physics 2008-01-14 Clinton DeW. Van Siclen

We investigate the relationship between ground-state (zero-temperature) quantum phase transitions in systems with variable Hamiltonian parameters and classical (temperature-driven) phase transitions in standard thermodynamics. An analogy is…

Nuclear Theory · Physics 2009-11-11 Pavel Cejnar , Stefan Heinze , Jan Dobes

This is the documentation for generating random samples from the quantum state space in accordance with a specified distribution, associated with this webpage: http://tinyurl.com/QSampling . Ready-made samples (each with at least a million…

In this work we develop tools that enable the study of non-adiabatic effects with variational and diffusion Monte Carlo methods. We introduce a highly accurate wave function ansatz for electron-ion systems that can involve a combination of…

Chemical Physics · Physics 2014-10-29 Norm M. Tubman , Ilkka Kylänpää , Sharon Hammes-Schiffer , David M. Ceperley

Classical simulation of quantum systems plays an important role in the study of many-body phenomena and in the benchmarking and verification of quantum technologies. Exact simulation is often limited to small systems because the dimension…

Quantum Physics · Physics 2024-06-04 Dominik S. Wild , Sabina Drăgoi , Corbin McElhanney , Jonathan Wurtz , Sheng-Tao Wang

Neural-network quantum states (NQS) offer a versatile and expressive alternative to traditional variational ans\"atze for simulating physical systems. Energy-based frameworks, like Hopfield networks and Restricted Boltzmann Machines,…

Quantum Physics · Physics 2024-12-18 Manas Sajjan , Vinit Singh , Sabre Kais