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Related papers: Quantum Monte Carlo in the steady-state

200 papers

Polaron tunneling is a prominent example of a problem characterized by different energy scales, for which the standard quantum Monte Carlo methods face a slowdown problem. We propose a new quantum-tunneling Monte Carlo (QTMC) method which…

Quantum Gases · Physics 2021-04-14 A. S. Popova , V. V. Tiunova , A. N. Rubtsov

We examine applicability of the valence bond basis correlator product state ansatz, equivalent to the restricted Boltzmann machine quantum artificial neural network ansatz, and variational Monte Carlo method for direct optimization of…

Strongly Correlated Electrons · Physics 2020-08-12 Tanja Duric , Tomislav Seva

We present a numerically efficient method for the characterisation of a quantum process subject to dissipation and noise. The master equation evolution of a maximally entangled state of the quantum system and a non-evolving ancilla system…

Quantum Physics · Physics 2013-12-04 Jake Gulliksen , D. D. Bhaktavatsala Rao , Klaus Mølmer

We introduce a novel frequency-dependent incoherent pump scheme with a square-shaped spectrum as a way to study strongly correlated photons in arrays of coupled nonlinear resonators. This scheme can be implemented via a reservoir of…

We present a new quantum Monte Carlo algorithm suitable for generically complex problems, such as systems coupled to external magnetic fields or anyons in two spatial dimensions. We find that the choice of gauge plays a nontrivial role, and…

Condensed Matter · Physics 2009-10-22 Lizeng Zhang , Geoff Canright , Ted Barnes

Recently the general form of a translation-covariant quantum Boltzmann equation has been derived which describes the dynamics of a tracer particle in a quantum gas. We develop a stochastic wave function algorithm that enables full…

Quantum Physics · Physics 2007-09-24 Heinz-Peter Breuer , Bassano Vacchini

In this work we investigate the ground state and the dissipative quantum dynamics of interacting charged particles in an external potential at finite temperature. The recently devised time-dependent quantum Monte Carlo (TDQMC) method allows…

Quantum Physics · Physics 2025-01-29 Ivan P. Christov

We propose a highly efficient "worm" like cluster Monte Carlo algorithm for the quantum rotor model in the link-current representation. We explicitly prove detailed balance for the new algorithm even in the presence of disorder. For the…

Strongly Correlated Electrons · Physics 2009-11-07 Fabien Alet , Erik S. Sorensen

We introduce a versatile method to compute electronic steady state properties of strongly correlated extended quantum systems out of equilibrium. The approach is based on dynamical mean-field theory (DMFT), in which the original system is…

Strongly Correlated Electrons · Physics 2013-03-05 Enrico Arrigoni , Michael Knap , Wolfgang von der Linden

We develop a hybrid Monte Carlo method to efficiently compute the physical observables from the samplings of the Laughlin and the Moore-Read wave functions of fractional quantum Hall (FQH) systems. With the advancements in methodology,…

Strongly Correlated Electrons · Physics 2026-02-20 Ting-Tung Wang , Ha Quang Trung , Qianhui Xu , Min Long , Bo Yang , Zi Yang Meng

We apply diffusion quantum Monte Carlo (DMC) to a broad set of solids, benchmarking the method by comparing bulk structural properties (equilibrium volume and bulk modulus) to experiment and DFT based theories. The test set includes…

Materials Science · Physics 2015-06-17 Luke Shulenburger , Thomas R. Mattsson

Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying…

The directed-loop quantum Monte Carlo method is generalized to the case of retarded interactions. Using the path integral, fermion-boson or spin-boson models are mapped to actions with retarded interactions by analytically integrating out…

Strongly Correlated Electrons · Physics 2017-09-06 Manuel Weber , Fakher F. Assaad , Martin Hohenadler

Quantum metrology exploits quantum mechanical laws to improve the precision in estimating technologically relevant parameters such as phase, frequency, or magnetic fields. Probe states are usually tailored on the particular dynamics whose…

Ab initio quantum Monte Carlo (QMC) is a state-of-the-art numerical approach for evaluating accurate expectation values of many-body wavefunctions. However, one of the major drawbacks that still hinders widespread QMC applications is the…

Materials Science · Physics 2024-07-17 Kousuke Nakano , Michele Casula , Giacomo Tenti

These lecture notes introduce quantum spin systems and several computational methods for studying their ground-state and finite-temperature properties. Symmetry-breaking and critical phenomena are first discussed in the simpler setting of…

Strongly Correlated Electrons · Physics 2015-03-17 Anders W. Sandvik

For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties, without the sign problem. The list spans condensed matter, nuclear physics, and…

Computational Physics · Physics 2016-03-23 Hao Shi , Shiwei Zhang

We examine the recently proposed imaginary-time formulation for strongly correlated steady-state nonequilibrium for its range of validity and discuss significant improvements in the analytic continuation of the Matsubara voltage as well as…

Strongly Correlated Electrons · Physics 2013-05-29 J. E. Han

The study of quantum quenches in integrable systems has significantly advanced with the introduction of the Quench Action method, a versatile analytical approach to non-equilibrium dynamics. However, its application is limited to those…

Statistical Mechanics · Physics 2016-08-24 Lorenzo Piroli , Eric Vernier , Pasquale Calabrese

Quantum impurity solvers are the computational bottleneck of quantum embedding approaches to correlated materials, such as dynamical mean-field theory (DMFT). We show that neural networks trained on synthetic, material-agnostic data learn…

Strongly Correlated Electrons · Physics 2026-03-25 Agnes Valenti , Ina Park , Antoine Georges , Andrew J. Millis , Olivier Parcollet
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