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We propose a method for simulating the stochastic dynamics of classical spin systems with long-range interactions. The method incorporates the stochastic cutoff (SCO) method, which is originally specialized for simulating equilibrium state,…

Statistical Mechanics · Physics 2019-12-09 Taichi Hinokihara , Yuta Okuyama , Munetaka Sasaki , Seiji Miyashita

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

A new diagrammatic quantum Monte Carlo approach is proposed to deal with the imaginary time propagator involving both dynamic disorder (i.e., electron-phonon interactions) and static disorder of local or nonlocal nature in a unified and…

Materials Science · Physics 2026-04-15 Yu-Chen Wang , Yi Zhao

We study the influence of short-range quantum correlations and classical spatial correlations on the phase diagram of the dissipative XYZ model by using a Gutzwiller Monte carlo method and a cluster Gutzwiller ansatz for the wave function.…

Statistical Mechanics · Physics 2019-05-08 Dolf Huybrechts , Michiel Wouters

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 Monte Carlo (QMC) methods represent a powerful family of computational techniques for tackling complex quantum many-body problems and performing calculations of stationary state properties. QMC is among the most accurate and…

Materials Science · Physics 2025-01-08 Alfonso Annarelli , Dario Alfè , Andrea Zen

Many-body approaches to open quantum systems have recently become powerful tools for investigating the detailed role of dissipative environments in diverse non-equilibrium molecular and condensed matter processes. Here, we report the…

Mesoscale and Nanoscale Physics · Physics 2016-02-15 Florian A. Y. N. Schröder , Alex W. Chin

We present an exact quantum Monte Carlo method for spin systems coupled to dissipative bosonic baths which makes use of nonlocal wormhole updates to simulate the retarded spin-flip interactions originating from an off-diagonal spin-boson…

Strongly Correlated Electrons · Physics 2022-05-17 Manuel Weber

We have developed a unified finite-size scaling method for quantum phase transitions that requires no prior knowledge of the dynamical exponent $z$. During a quantum Monte Carlo simulation, the temperature is automatically tuned by the…

Statistical Mechanics · Physics 2015-09-23 Shinya Yasuda , Hidemaro Suwa , Synge Todo

We describe a Monte Carlo simulation study of the magnetic phase diagram of diluted magnetic semiconductors doped with shallow impurities in the low concentration regime. We show that because of a wide distribution of interaction strengths,…

Disordered Systems and Neural Networks · Physics 2015-06-25 R. N. Bhatt , Xin Wan

To better understand the capture process by a nanopore, we introduce an efficient Kinetic Monte Carlo (KMC) algorithm that can simulate long times and large system sizes by mapping the dynamic of a point-like particle in a 3D spherically…

Biological Physics · Physics 2021-03-22 Le Qiao , Maxime Ignacio , Gary W. Slater

We put forward a simple procedure for extracting dynamical information from Monte Carlo simulations, by appropriate matching of the short-time diffusion tensor with its infinite-dilution limit counterpart, which is supposed to be known.…

Statistical Mechanics · Physics 2015-06-04 Sara Jabbari-Farouji , Emmanuel Trizac

A classical Monte Carlo algorithm based on the quasi-classical approximation is applied to the pseudospin Hamiltonian of the model cuprate. The model takes into account both local and non-local correlations, Heisenberg spin-exchange…

Computational Physics · Physics 2026-01-01 V. A. Ulitko , Yu. D. Panov , A. S. Moskvin

Quantum dimer model is a low-energy and efficient model to study quantum spin systems and strong-correlated physics. As a foreseeing step and without loss of generality, we study the classical dimers on square lattice by means of Monte…

Strongly Correlated Electrons · Physics 2022-04-28 Yao Hongxu , Li Jiaze , Hou Jintao

The discrete time path integral Monte Carlo (PIMC) with a one-particle density matrix approximation is applied to study the quantum phase transition in the coupled double-well chain. To improve the convergence properties, the exact action…

Statistical Mechanics · Physics 2015-06-25 Dong-Hee Kim , Yu-Cheng Lin , Heiko Rieger

We have developed an efficient Monte Carlo algorithm, which accelerates slow Monte Carlo dynamics in quasi-one-dimensional Ising spin systems. The loop algorithm of the quantum Monte Carlo method is applied to the classical spin models with…

Statistical Mechanics · Physics 2009-11-13 Tota Nakamura

Numerically exact continuous-time Quantum Monte Carlo algorithm for finite fermionic systems with non-local interactions is proposed. The scheme is particularly applicable for general multi-band time-dependent correlations since it does not…

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

Monte Carlo methods are widely used to estimate observables in many-body quantum systems. However, conventional sampling schemes often require a large number of samples to achieve sufficient accuracy. In this work we propose the…

Quantum Physics · Physics 2026-01-29 Wenxuan Zhang , Dingzu Wang , Dario Poletti

We present a numerically exact steady-state inchworm Monte Carlo method for nonequilibrium quantum impurity models. Rather than propagating an initial state to long times, the method is directly formulated in the steady-state. This…

Strongly Correlated Electrons · Physics 2023-05-17 André Erpenbeck , Emanuel Gull , Guy Cohen

The need to calibrate increasingly complex statistical models requires a persistent effort for further advances on available, computationally intensive Monte Carlo methods. We study here an advanced version of familiar Markov Chain Monte…

Methodology · Statistics 2015-03-20 Alexandros Beskos , Konstantinos Kalogeropoulos , Erik Pazos
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