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We extend correlated sampling from classical auxiliary-field quantum Monte Carlo to the quantum-classical (QC-AFQMC) framework, enabling accurate nuclear force computations crucial for geometry optimization and reaction dynamics. Stochastic…

We numerically study the Euclidean quantum cosmology of a closed, homogeneous and isotropic universe with a cosmological constant. A dust field acts as a clock, and we compute the ground state wavefunction, correlation function, and mean…

General Relativity and Quantum Cosmology · Physics 2025-09-30 Malaik Kabir , Syed Moeez Hassan

This article contains lecture notes on the constrained path Monte Carlo method and its applications to study the Hubbard model. The lectures were given at the NATO Advanced Summer Institute held in Ithaca NY (1998). The article is published…

Condensed Matter · Physics 2007-06-25 Shiwei Zhang

A symplectic no-core shell model (Sp-NCSM) is constructed with the goal of extending the {\it ab-initio} NCSM to include strongly deformed higher-oscillator-shell configurations and to reach heavier nuclei that cannot be studied currently…

The interacting shell model, a configuration-interaction method, is a venerable approach for low-lying nuclear structure calculations; but it is hampered by the exponential growth of its basis dimension as one increases the single-particle…

Nuclear Theory · Physics 2024-09-05 Oliver C. Gorton , Calvin W. Johnson

The ability of fully reconstructing quantum maps is a fundamental task of quantum information, in particular when coupling with the environment and experimental imperfections of devices are taken into account. In this context we carry out a…

Quantum Physics · Physics 2010-11-04 I. Bongioanni , L. Sansoni , F. Sciarrino , G. Vallone , P. Mataloni

These lectures are intended for graduate students who want to acquire a working knowledge of path integral methods in a wide variety of fields in physics. In general the presentation is elementary and path integrals are developed in the…

Nuclear Theory · Physics 2017-08-01 R. Rosenfelder

Monte Carlo simulations are useful tools for modeling quantum systems, but in some cases they suffer from a sign problem, leading to an exponential slow down in their convergence to a value. While solving the sign problem is generically…

Quantum Physics · Physics 2022-12-21 T. C. Mooney , Jacob Bringewatt , Neill C. Warrington , Lucas T. Brady

We introduce an iterative importance truncation scheme which aims at reducing the dimension of the model space of configuration interaction approaches by an a priori selection of the physically most relevant basis states. Using an…

Nuclear Theory · Physics 2009-07-09 Robert Roth

Rydberg atom arrays have emerged as a powerful platform to simulate a number of exotic quantum ground states and phase transitions. To verify these capabilities numerically, we develop a versatile quantum Monte Carlo sampling technique…

Strongly Correlated Electrons · Physics 2026-01-28 Pranay Patil

In this work, we introduce a simple modification of the Monte Carlo algorithm, which we call step Monte Carlo (sMC). The sMC approach allows to simulate processes far from equilibrium and obtain information about the dynamic properties of…

Other Condensed Matter · Physics 2023-12-15 Dariusz Sztenkiel

While the shell model Monte Carlo approach has been successful in the microscopic calculation of nuclear state densities, it has been difficult to calculate accurately state densities of odd-even heavy nuclei. This is because the projection…

Nuclear Theory · Physics 2013-04-30 C. Özen , Y. Alhassid , H. Nakada

Neural networks (NNs) representing quantum states are typically trained using Markov chain Monte Carlo based methods. However, unless specifically designed, such samplers only consist of local moves, making the slow-mixing problem prominent…

Quantum Physics · Physics 2022-09-28 Yuan-Hang Zhang , Massimiliano Di Ventra

We propose a new type of Monte Carlo approach in numerical studies of quantum systems. Introducing a probability function which determines whether a state in the vector space survives or not, we can evaluate expectation values of powers of…

Strongly Correlated Electrons · Physics 2009-11-10 Tomo Munehisa , Yasuko Munehisa

Quantum Monte Carlo methods are first-principle approaches that approximately solve the Schr\"odinger equation stochastically. As compared to traditional quantum chemistry methods, they offer important advantages such as the ability to…

Chemical Physics · Physics 2020-02-11 Jonas Feldt , Claudia Filippi

We apply a Bayesian data analysis scheme known as the Markov Chain Monte Carlo (MCMC) to the tomographic reconstruction of quantum states. This method yields a vector, known as the Markov chain, which contains the full statistical…

We study several aspects of the recently introduced fixed-phase spin-orbit diffusion Monte Carlo (FPSODMC) method, in particular, its relation to the fixed-node method and its potential use as a general approach for electronic structure…

Computational Physics · Physics 2017-10-18 Cody A. Melton , Lubos Mitas

The absorbing-state transition in the three-dimensional contact process with and without quenched randomness is investigated by means of Monte-Carlo simulations. In the clean case, a reweighting technique is combined with a careful…

Statistical Mechanics · Physics 2012-12-03 Thomas Vojta

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

We introduce a particle-number reprojection method in the shell model Monte Carlo that enables the calculation of observables for a series of nuclei using a Monte Carlo sampling for a single nucleus. The method is used to calculate nuclear…

Nuclear Theory · Physics 2009-10-31 Y. Alhassid , S. Liu , H. Nakada