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Complex soft matter systems can be efficiently studied with the help of adaptive resolution simulation methods, concurrently employing two levels of resolution in different regions of the simulation domain. The non-matching properties of…

The wavelength of a periodic spatial structure of Turing type is an intrinsic property of the considered reaction-diffusion dynamics and we address the question of its control at the microscopic scale for given dynamical parameters. The…

Pattern Formation and Solitons · Physics 2018-09-26 Gabriel Morgado , Bogdan Nowakowski , Annie Lemarchand

We reformulate the projected imaginary-time evolution of Full Configuration Interaction Quantum Monte Carlo in terms of a Lagrangian minimization. This naturally leads to the admission of polynomial complex wavefunction parameterizations,…

Strongly Correlated Electrons · Physics 2017-05-03 Lauretta R. Schwarz , A. Alavi , George H. Booth

The correlated projection superoperator techniques provide a better understanding about how correlations lead to strong non-Markovian effects in open quantum systems. Their superoperators are independent of initial state, which may not be…

Quantum Physics · Physics 2020-09-11 Zhiqiang Huang

Markov chain Monte Carlo methods are a powerful tool for sampling equilibrium configurations in complex systems. One problem these methods often face is slow convergence over large energy barriers. In this work, we propose a novel method…

Computational Physics · Physics 2024-05-29 Luigi Sbailò , Manuel Dibak , Frank Noé

A general method is developed which enables the exact treatment of the non-Markovian quantum dynamics of open systems through a Monte Carlo simulation technique. The method is based on a stochastic formulation of the von Neumann equation of…

Quantum Physics · Physics 2007-05-23 Heinz-Peter Breuer

We describe a Monte Carlo procedure which allows sampling of the disjoint configuration spaces associated with crystalline and fluid phases, within a single simulation. The method utilises biased sampling techniques to enhance the…

Statistical Mechanics · Physics 2009-10-31 N. B. Wilding , A. D. Bruce

Sequential Monte Carlo methods, also known as particle methods, are a popular set of techniques for approximating high-dimensional probability distributions and their normalizing constants. These methods have found numerous applications in…

Computation · Statistics 2021-06-23 Jeremy Heng , Adrian N. Bishop , George Deligiannidis , Arnaud Doucet

We generalize the recently developed diagrammatic Monte Carlo techniques for quantum impurity models from an imaginary time to a Keldysh formalism suitable for real-time and nonequilibrium calculations. Both weak-coupling and…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Philipp Werner , Takashi Oka , Andrew J. Millis

Non-Markovian open quantum systems represent the most general dynamics when the quantum system is coupled with a bath environment. The quantum dynamics arising from many important applications are non-Markovian. Although for special cases,…

Quantum Physics · Physics 2023-03-01 Xiantao Li , Chunhao Wang

Non-Hermitian quantum systems exhibit unique properties and hold significant promise for diverse applications, yet their dynamical simulation poses a particular challenge due to intrinsic openness and non-unitary evolution. Here, we…

Quantum Physics · Physics 2025-10-21 Xiaogang Li , Kecheng Liu , Qiming Ding

The accuracy and efficiency of ab-initio quantum Monte Carlo (QMC) algorithms benefits greatly from compact variational trial wave functions that accurately reproduce ground state properties of a system. We investigate the possibility of…

Materials Science · Physics 2019-01-30 Shivesh Pathak , Lucas K. Wagner

We present a new approach to determine numerically the statistical behavior of small-scale structures in hydrodynamic turbulence. Starting from the functional integral representation of the random-force-driven Burgers equation we show that…

Chaotic Dynamics · Physics 2015-05-27 David Mesterhazy , Karl Jansen

Boson sampling is a promising candidate for quantum supremacy. It requires to sample from a complicated distribution, and is trusted to be intractable on classical computers. Among the various classical sampling methods, the Markov chain…

We introduce a `virtual-move' Monte Carlo (VMMC) algorithm for systems of pairwise-interacting particles. This algorithm facilitates the simulation of particles possessing attractions of short range and arbitrary strength and geometry, an…

Statistical Mechanics · Physics 2009-11-11 Stephen Whitelam , Phillip L. Geissler

Monte Carlo (MC) simulations of many systems, in particular those with conflicting constraints, can be considerably speeded up by using multicanonical or related methods. Some of these approaches sample with a-priori unknown weight factors.…

High Energy Physics - Lattice · Physics 2009-10-30 Bernd A. Berg

We develop a classical Monte Carlo algorithm based on a quasi-classical approximation for a pseudospin S=1 Hamiltonian in real space to construct a phase diagram of a model cuprate with a high Tc. A model description takes into account both…

Strongly Correlated Electrons · Physics 2021-10-25 Yu. D. Panov , A. S. Moskvin , A. A. Chikov , V. A. Ulitko

The process tensor framework to open quantum systems provides the most general description of multi-time correlations in non-Markovian quantum dynamics. A compressed representation of a process tensor in terms of matrix product operators…

Many spin systems affected by critical slowing down can be efficiently simulated using cluster algorithms. Where such systems have long-range interactions, suitable formulations can additionally bring down the computational effort for each…

Statistical Mechanics · Physics 2017-04-07 Emilio Flores-Sola , Martin Weigel , Ralph Kenna , Bertrand Berche

The main idea of this work is that the quantum-classical isomorphism is a suitable framework for a generalization of the notion of detailed balance. The quantum-classical isomorphism is used in order to develop a Monte Carlo simulation with…

Probability · Mathematics 2007-10-29 Yefim I. Leifman
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