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Quantum Monte Carlo is one of the most promising approaches for dealing with large-scale quantum many-body systems. It has played an extremely important role in understanding strongly correlated physics. However, two fundamental problems,…

Strongly Correlated Electrons · Physics 2026-03-03 Zhiyan Wang , Zenan Liu , Bin-Bin Mao , Zhe Wang , Zheng Yan

Monte Carlo simulations, in which the Schrodinger equation is solved at each Monte Carlo sweep, are employed to assess the influence of magnetization fluctuations,short-range antiferromagnetic interactions, disorder, magnetic polaron…

Materials Science · Physics 2007-05-23 D. Kechrakos , N. Papanikolaou , K. N. Trohidou , T. Dietl

Starting with the Fourier integral theorem, we present natural Monte Carlo estimators of multivariate functions including densities, mixing densities, transition densities, regression functions, and the search for modes of multivariate…

Statistics Theory · Mathematics 2021-01-01 Nhat Ho , Stephen G. Walker

We present a Hamiltonian Monte Carlo algorithm to sample from multivariate Gaussian distributions in which the target space is constrained by linear and quadratic inequalities or products thereof. The Hamiltonian equations of motion can be…

Computation · Statistics 2013-06-06 Ari Pakman , Liam Paninski

The paper proposes Monte Carlo algorithms for the computation of the information rate of two-dimensional source/channel models. The focus of the paper is on binary-input channels with constraints on the allowed input configurations. The…

Information Theory · Computer Science 2012-12-27 Mehdi Molkaraie , Hans-Andrea Loeliger

Nuclear physics seeks to describe both bound and unbound states within a unified predictive framework. While coordinate-space Quantum Monte Carlo (QMC) methods have successfully computed bound states for systems with $A \leq 12$, their…

Nuclear Theory · Physics 2025-02-27 Abraham R. Flores , Kenneth M. Nollett , Maria Piarulli

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

We present a quantum Monte-Carlo algorithm for computing the perturbative expansion in power of the coupling constant $U$ of the out-of-equilibrium Green's functions of interacting Hamiltonians of fermions. The algorithm extends the one…

Strongly Correlated Electrons · Physics 2019-09-23 Corentin Bertrand , Olivier Parcollet , Antoine Maillard , Xavier Waintal

We report quantum Monte Carlo calculations of ground and low-lying excited states for nuclei with A \leq 7 using a realistic Hamiltonian containing the Argonne v18 two-nucleon and Urbana IX three-nucleon potentials. A detailed description…

Nuclear Theory · Physics 2008-11-26 B. S. Pudliner , V. R. Pandharipande , J. Carlson , Steven C. Pieper , R. B. Wiringa

We describe and analyze some Monte Carlo methods for manifolds in Euclidean space defined by equality and inequality constraints. First, we give an MCMC sampler for probability distributions defined by un-normalized densities on such…

Numerical Analysis · Mathematics 2017-09-21 Emilio Zappa , Miranda Holmes-Cerfon , Jonathan Goodman

Sampling from complicated probability distributions is a hard computational problem arising in many fields, including statistical physics, optimization, and machine learning. Quantum computers have recently been used to sample from…

We propose a new Monte Carlo technique in which the degeneracy of energy states is obtained with a Markovian process analogous to that of Metropolis used currently in canonical simulations. The obtained histograms are much broader than…

Statistical Mechanics · Physics 2009-10-30 P. M. C. de Oliveira , T. J. P. Penna , H. J. Herrmann

This paper considers the challenging computational task of estimating nested expectations. Existing algorithms, such as nested Monte Carlo or multilevel Monte Carlo, are known to be consistent but require a large number of samples at both…

Machine Learning · Statistics 2025-06-05 Zonghao Chen , Masha Naslidnyk , François-Xavier Briol

In particle-based algorithms, the effect of binary collisions is commonly described in a statistical way, using Monte Carlo techniques. It is shown that, in the relativistic regime, stringent constraints should be considered on the sampling…

Plasma Physics · Physics 2009-11-13 F. Peano , M. Marti , L. O. Silva , G. Coppa

Using a random-matrix approach and Monte-Carlo simulations, we generate scattering matrices and cross sections for compound-nucleus reactions. In the absence of direct reactions we compare the average cross sections with the analytic…

Nuclear Theory · Physics 2015-09-03 T. Kawano , P. Talou , H. A. Weidenmüller

We introduce and develop a novel particle exchange Monte Carlo method. Whereas existing methods apply to eigenfunction problems where the eigenvalue is known (e.g., integrals with respect to a Gibbs measure, which can be interpreted as…

Numerical Analysis · Mathematics 2025-08-26 Paul Dupuis , Benjamin J. Zhang

We report variational and diffusion Quantum Monte Carlo ground-state energies of the three-dimensional electron gas using a model periodic Coulomb interaction and backflow corrections for N=54, 102, 178, and 226 electrons. We remove…

Materials Science · Physics 2010-01-28 I. G. Gurtubay , R. Gaudoin , J. M. Pitarke

We present a hybrid method for time-dependent particle transport problems that combines Monte Carlo (MC) estimation with deterministic solutions based on discrete ordinates. For spatial discretizations, the MC algorithm computes a piecewise…

Numerical Analysis · Mathematics 2023-12-08 Johannes Krotz , Cory D. Hauck , Ryan G. McClarren

Green's function Monte Carlo calculations of magnetic moments and M1 transitions including two-body meson-exchange current (MEC) contributions are reported for A<=7 nuclei. The realistic Argonne v18 two-nucleon and Illinois-2 three-nucleon…

Nuclear Theory · Physics 2013-05-22 L. E. Marcucci , Muslema Pervin , Steven C. Pieper , R. Schiavilla , R. B. Wiringa

We describe an efficient algorithm to compute forces in quantum Monte Carlo using adjoint algorithmic differentiation. This allows us to apply the space warp coordinate transformation in differential form, and compute all the 3M force…

Other Condensed Matter · Physics 2015-05-20 Sandro Sorella , Luca Capriotti
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