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Here we study the dynamics of many-body quantum systems using time dependent quantum Monte Carlo method where the evolution is described by ensembles of particles and guide waves. The exponential-time scaling inherent to the quantum…

Atomic Physics · Physics 2025-01-28 Ivan P. Christov

We present near-term quantum algorithms for auxiliary-field quantum Monte Carlo (AFQMC), viewed as imaginary-time projection for ground-state calculation as an ensemble of one-body propagators driven by stochastic fields $\Omega$. Starting…

Quantum Physics · Physics 2026-03-31 Xiantao Li

We implement the phaseless auxiliary field quantum Monte Carlo method using the plane-wave based projector augmented wave method and explore the accuracy and the feasibility of applying our implementation to solids. We use a singular value…

We propose a general framework of quantum kinetic Monte Carlo algorithm, based on a stochastic representation of a series expansion of the quantum evolution. Two approaches have been developed in the context of quantum many-body spin…

Computational Physics · Physics 2018-01-17 Zhenning Cai , Jianfeng Lu

Perturbative schemes utilizing a spectral moment expansion are well known and extensively used for investigating the physics of model Hamiltonians and real material systems. The advantages they offer, in terms of being computationally…

Strongly Correlated Electrons · Physics 2016-11-09 Nagamalleswararao Dasari , Wasim Raja Mondal , Peng Zhang , Juana Moreno , Mark Jarrell , N. S. Vidhyadhiraja

The possibility to simulate the properties of many-body open quantum systems with a large number of degrees of freedom is the premise to the solution of several outstanding problems in quantum science and quantum information. The challenge…

Quantum Physics · Physics 2019-07-03 Alexandra Nagy , Vincenzo Savona

We investigate the attractive Fermi polaron problem in two dimensions using non-perturbative Monte Carlo simulations. We introduce a new Monte Carlo algorithm called the impurity lattice Monte Carlo method. This algorithm samples the path…

Quantum Gases · Physics 2015-10-29 Shahin Bour , Dean Lee , H. -W. Hammer , Ulf-G. Meißner

We introduce a novel Multi-Order Monte Carlo approach for uncertainty quantification in the context of multiscale time-dependent partial differential equations. The new framework leverages Implicit-Explicit Runge-Kutta time integrators to…

Numerical Analysis · Mathematics 2026-04-08 Giulia Bertaglia , Walter Boscheri , Lorenzo Pareschi

When a system undergoes a quantum phase transition, the ground-state wave-function shows a change of nature, which can be monitored using the fidelity concept. We introduce two Quantum Monte Carlo schemes that allow the computation of…

Strongly Correlated Electrons · Physics 2009-10-21 David Schwandt , Fabien Alet , Sylvain Capponi

We propose a fast multi-orbital impurity solver for the dynamical mean field theory (DMFT). Our DMFT solver is based on the equations of motion (EOM) for local Green's functions and constructed by generalizing from the single-orbital case…

Strongly Correlated Electrons · Physics 2015-05-30 Qingguo Feng , P. M. Oppeneer

The standard approach for path integral Monte Carlo simulations of open quantum systems is extended as an efficient tool to monitor the time evolution of coherences (off-diagonal elements of the reduced density matrix) also for strong…

Statistical Mechanics · Physics 2015-06-12 Denis Kast , Joachim Ankerhold

We present a non-destructive method to probe a complex quantum system using multiple impurity atoms as quantum probes. Our protocol provides access to different equilibrium properties of the system by changing its coupling to the probes. In…

Quantum Physics · Physics 2016-11-29 Michael Streif , Andreas Buchleitner , Dieter Jaksch , Jordi Mur-Petit

We present a hybrid method for time-dependent particle transport problems that combines Monte Carlo (MC) estimation with deterministic solutions based on discrete ordinates. For spatial discretizations, the MC algorithm computes a piecewise…

Numerical Analysis · Mathematics 2023-12-08 Johannes Krotz , Cory D. Hauck , Ryan G. McClarren

We present numerically exact continuous-time Quantum Monte Carlo algorithm for fermions with a general non-local in space-time interaction. The new determinantal grand-canonical scheme is based on a stochastic series expansion for the…

Strongly Correlated Electrons · Physics 2009-11-10 A. N. Rubtsov , V. V. Savkin , A. I. Lichtenstein

This Perspective focuses on the several overlaps between quantum algorithms and Monte Carlo methods in the domains of physics and chemistry. We will analyze the challenges and possibilities of integrating established quantum Monte Carlo…

Quantum Physics · Physics 2024-09-26 Guglielmo Mazzola

We introduce a Monte-Carlo algorithm for the simulation of charged particles moving in the continuum. Electrostatic interactions are not instantaneous as in conventional approaches, but are mediated by a constrained, diffusing electric…

Soft Condensed Matter · Physics 2009-11-10 Joerg Rottler , A. C. Maggs

We present a very efficient solver for the general Anderson impurity problem. It is based on the perturbation around a solution obtained from exact diagonalization using a small number of bath sites. We formulate a perturbation theory which…

We present a novel, generally applicable Monte Carlo algorithm for the simulation of fluid systems. Geometric transformations are used to identify clusters of particles in such a manner that every cluster move is accepted, irrespective of…

Statistical Mechanics · Physics 2016-08-31 Jiwen Liu , Erik Luijten

A detailed description is provided of a new Worm Algorithm, enabling the accurate computation of thermodynamic properties of quantum many-body systems in continuous space, at finite temperature. The algorithm is formulated within the…

Computational Physics · Physics 2009-11-11 M. Boninsegni , N. V. Prokof'ev , B. V. Svistunov

The Hamiltonian Monte Carlo (HMC) method allows sampling from continuous densities. Favorable scaling with dimension has led to wide adoption of HMC by the statistics community. Modern auto-differentiating software should allow more…

Computation · Statistics 2022-08-17 Ian Langmore , Michael Dikovsky , Scott Geraedts , Peter Norgaard , Rob von Behren