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The Fermi gas at unitarity is a particularly interesting system of cold atoms, being dilute and strongly interacting at the same time. It can be studied non-perturbatively with Monte Carlo methods, like the recently developed worm…

Quantum Gases · Physics 2010-11-05 Olga Goulko , Matthew Wingate

We present a quantum Monte Carlo method which allows calculations on many-fermion systems at finite temperatures without any sign decay. This enables simulations of the grand-canonical ensemble at large system sizes and low temperatures.…

Condensed Matter · Physics 2009-10-31 Shiwei Zhang

A continuous-time path integral Quantum Monte Carlo method using the directed-loop algorithm is developed to simulate the Anderson single-impurity model in the occupation number basis. Although the method suffers from a sign problem at low…

Strongly Correlated Electrons · Physics 2009-11-10 Jaebeom Yoo , Shailesh Chandrasekharan , Harold U. Baranger

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a novel…

Statistical Mechanics · Physics 2017-12-27 Tameem Albash , Gene Wagenbreth , Itay Hen

We derive exact, universal, closed-form quantum Monte Carlo estimators for finite-temperature energy susceptibility and fidelity susceptibility, applicable to essentially arbitrary Hamiltonians. Combined with recent advancements in Monte…

Statistical Mechanics · Physics 2026-01-30 Nic Ezzell , Lev Barash , Itay Hen

Quantum Monte Carlo (QMC) methods are one of the most important tools for studying interacting quantum many-body systems. The vast majority of QMC calculations in interacting fermion systems require a constraint to control the sign problem.…

Strongly Correlated Electrons · Physics 2016-12-08 Mingpu Qin , Hao Shi , Shiwei Zhang

We develop a nonequilibrium increment method in quantum Monte Carlo simulations to obtain the R\'enyi entanglement entropy of various quantum many-body systems with high efficiency and precision. To demonstrate its power, we show the…

Strongly Correlated Electrons · Physics 2022-07-01 Jiarui Zhao , Bin-Bin Chen , Yan-Cheng Wang , Zheng Yan , Meng Cheng , Zi Yang Meng

Recent Monte Carlo simulations of the critical point of the restricted primitive model for ionic solutions are reported. Only the continuum version of the model is considered. A finite size scaling analysis based in the Bruce-Wilding…

Statistical Mechanics · Physics 2007-05-23 Jean-Michel Caillol

An efficient Quantum Monte Carlo algorithm for the simulation of bosonic systems on a lattice in a grand canonical ensemble is proposed. It is based on the mapping of bosonic models to the spin models in the limit of the infinite total spin…

Statistical Mechanics · Physics 2007-05-23 Jurij Smakov , Kenji Harada , Naoki Kawashima

We propose an efficient method for Monte Carlo simulation of quantum lattice models. Unlike most other quantum Monte Carlo methods, a single run of the proposed method yields the free energy and the entropy with high precision for the whole…

Statistical Mechanics · Physics 2009-11-10 Chiaki Yamaguchi , Naoki Kawashima , Yutaka Okabe

Using the quantum Monte Carlo Loop algorithm, we calculate the temperature dependence of the uniform susceptibility, the specific heat, the correlation length, the generalized staggered susceptibility and magnetization of a spin-1/2 chain…

Condensed Matter · Physics 2007-05-23 Beat Frischmuth , Manfred Sigrist , Beat Ammon , Matthias Troyer

Using single cluster flip Monte Carlo simulations we accurately determine new finite size scaling functions which are expressed only in terms the variable $x = \xi_L / L$, where $\xi_L$ is the correlation length in a finite system of size…

Condensed Matter · Physics 2009-10-28 Jae-Kwon Kim , Adauto J. F. de Souza\cite{addr} , D. P. Landau

In finite-size scaling analyses of Monte Carlo simulations of second-order phase transitions one often needs an extended temperature range around the critical point. By combining the parallel tempering algorithm with cluster updates and an…

Statistical Mechanics · Physics 2015-05-28 Elmar Bittner , Wolfhard Janke

We consider the problem of estimating the expected outcomes of Monte Carlo processes whose outputs are described by multidimensional random variables. We tightly characterize the quantum query complexity of this problem for various choices…

Quantum Physics · Physics 2021-07-09 Arjan Cornelissen , Sofiene Jerbi

The power of machine learning algorithms to automatically classify different phases of matter and detect quantum phase transitions without necessity to characterize phases by various quantities like local order parameters or topological…

Strongly Correlated Electrons · Physics 2021-03-15 Tanja Duric

We describe an approach for many-body calculations with a finite-temperature, grand canonical ensemble formalism using auxiliary-field quantum Monte Carlo (AFQMC) with a self-consistent constraint to control the sign problem. The usual…

Strongly Correlated Electrons · Physics 2019-06-18 Yuan-Yao He , Mingpu Qin , Hao Shi , Zhong-Yi Lu , Shiwei Zhang

A continuous-time projection quantum Monte Carlo algorithm is employed to simulate the ground state of a short-range quantum spin-glass model, namely, the two-dimensional Edwards-Anderson Hamiltonian with transverse field, featuring…

Disordered Systems and Neural Networks · Physics 2024-12-24 L. Brodoloni , S. Pilati

Finite temperature quantum Monte Carlo simulations are performed on the anisotropic t-J model and in particular on its Ising limit. Straight site-centered stripes are imposed by an on-site potential representing external mechanisms of…

Superconductivity · Physics 2009-11-07 Jose A. Riera

Monte Carlo methods play a central role in particle physics, where they are indispensable for simulating scattering processes, modeling detector responses, and performing multi-dimensional integrals. However, traditional Monte Carlo methods…

Quantum Physics · Physics 2025-10-14 Heechan Yi , Kayoung Ban , Myeonghun Park , Kyoungchul Kong

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition…

Quantum Physics · Physics 2017-07-12 Ashley Montanaro