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Unbiased stochastic sampling of the one- and two-body reduced density matrices is achieved in full configuration interaction quantum Monte Carlo with the introduction of a second, "replica" ensemble of walkers, whose population evolves in…

Computational Physics · Physics 2015-09-02 Robert E. Thomas , Daniel Opalka , Catherine Overy , Peter J. Knowles , Ali Alavi , George H. Booth

Ultracold atomic systems have been of great research interest in the past, with more recent attention being paid to systems of mixed species. In this work we carry out non-perturbative Path Integral Monte Carlo (PIMC) simulations of N…

Quantum Gases · Physics 2017-10-19 William G. Dawkins , Alexandros Gezerlis

The diffusion quantum Monte Carlo method is extended to solve the old theoretical physics problem of many-electron atoms and ions in intense magnetic fields. The feature of our approach is the use of adiabatic approximation wave functions…

Quantum Physics · Physics 2009-11-13 S. Bucheler , D. Engel , J. Main , G. Wunner

We discuss the implications of recent experimental evidence of nuclear Short Range Correlations (SRCs) on the modeling of the wave function of complex nuclei. We perform a calculation of potential energy contributions of pp and pn pairs in…

Nuclear Theory · Physics 2009-12-31 M. Alvioli , C. Ciofi degli Atti , M. Strikman

The recently developed auxiliary field diffusion Monte Carlo method is applied to compute the equation of state and the compressibility of neutron matter. By combining diffusion Monte Carlo for the spatial degrees of freedom and auxiliary…

Nuclear Theory · Physics 2009-11-10 A. Sarsa , S. Fantoni , K. E. Schmidt , F. Pederiva

The variational multiparticle-multihole configuration mixing approach (MPMH) to nuclei has been proposed about a decade ago. While the first applications followed rapidly, the implementation of the full formalism of this method has only…

Nuclear Theory · Physics 2017-04-26 C. Robin , N. Pillet , M. Dupuis , J. Le Bloas , D. Peña Arteaga , J. -F. Berger

The many-body states in an extended Fermionic Molecular Dynamics approach are flexible enough to allow the description of nuclei with shell model nature as well as nuclei with cluster and halo structures. Different many-body configurations…

Nuclear Theory · Physics 2009-11-10 T. Neff , H. Feldmeier

We calculate the equation of state of neutron matter at zero temperature by means of the auxiliary field diffusion Monte Carlo method (AFDMC) combined with a fixed-phase approximation. The calculation of the energy is carried out by…

Nuclear Theory · Physics 2009-06-30 S. Gandolfi , A. Yu. Illarionov , K. E. Schmidt , F. Pederiva , S. Fantoni

Sequential Monte Carlo (SMC), or particle filtering, is widely used in nonlinear state-space systems, but its performance often suffers from poorly approximated proposal and state-transition distributions. This work introduces a…

Machine Learning · Computer Science 2026-05-14 Wessel L. van Nierop , Nir Shlezinger , Ruud J. G. van Sloun

Lanthanide element signatures are key to understanding many astrophysical observables, from merger kilonova light curves to stellar and solar abundances. To learn about the lanthanide element synthesis that enriched our solar system, we…

Nuclear Theory · Physics 2021-02-12 Nicole Vassh , Gail C. McLaughlin , Matthew R. Mumpower , Rebecca Surman

The nuclear shell model has been perhaps the most important conceptual and computational paradigm for the understanding of the structure of atomic nuclei. While the shell model has been predominantly used in a phenomenological context,…

Nuclear Theory · Physics 2019-10-25 S. Ragnar Stroberg , Scott K. Bogner , Heiko Hergert , Jason D. Holt

We computed ground-state energies of calcium isotopes from 42Ca to 48Ca by means of the Auxiliary Field Diffusion Monte Carlo (AFDMC) method. Calculations were performed by replacing the 40Ca core with a mean-field self consistent potential…

Nuclear Theory · Physics 2008-03-19 S. Gandolfi , F. Pederiva , S. a Beccara

Neural Network-based Quantum Monte Carlo (NNQMC), an emerging method for solving many-body quantum systems with high accuracy, has been limitedly applied to small systems due to demanding computation requirements. In this work, we introduce…

Nonlinear non-Gaussian state-space models are ubiquitous in statistics, econometrics, information engineering and signal processing. Particle methods, also known as Sequential Monte Carlo (SMC) methods, provide reliable numerical…

Computation · Statistics 2015-09-11 Nikolas Kantas , Arnaud Doucet , Sumeetpal S. Singh , Jan Maciejowski , Nicolas Chopin

We consider Bayesian inference in sequential latent variable models in general, and in nonlinear state space models in particular (i.e., state smoothing). We work with sequential Monte Carlo (SMC) algorithms, which provide a powerful…

Computation · Statistics 2015-05-26 Fredrik Lindsten , Pete Bunch , Sumeetpal S. Singh , Thomas B. Schön

The work presents the recent developments in Quantum Monte Carlo calculations for nuclear systems including strange degrees of freedom. The Auxiliary Field Diffusion Monte Carlo algorithm has been extended to the strange sector by the…

Nuclear Theory · Physics 2013-11-27 Diego Lonardoni

A novel machine learning approach is used to provide further insight into atomic nuclei and to detect orderly patterns amidst a vast data of large-scale calculations. The method utilizes a neural network that is trained on ab initio results…

Nuclear Theory · Physics 2022-03-14 O. M. Molchanov , K. D. Launey , A. Mercenne , G. H. Sargsyan , T. Dytrych , J. P. Draayer

Nuclear short-range correlations (SRC) typically manifest themselves in the tail parts of the single-nucleon momentum distributions. We propose an approximate practical method for computing those SRC contributions to the high-momentum…

Nuclear Theory · Physics 2015-08-13 Jan Ryckebusch , Maarten Vanhalst , Wim Cosyn

We perform Shell Model Monte Carlo calculations of selected N=Z pf-shell nuclei with a schematic hamiltonian containing isovector pairing and quadrupole-quadrupole interactions. Compared to realistic interactions, this hamiltonian does not…

Nuclear Theory · Physics 2009-10-30 K. Langanke , P. Vogel , Dao-Chen Zheng

Optimizing highly complex cost/energy functions over discrete variables is at the heart of many open problems across different scientific disciplines and industries. A major obstacle is the emergence of many-body effects among certain…