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Quantum Monte Carlo (QMC) algorithms have long relied on Jastrow factors to incorporate dynamic correlation into trial wave functions. While Jastrow-type wave functions have been widely employed in real-space algorithms, they have seen…

Strongly Correlated Electrons · Physics 2016-12-28 Chia-Chen Chang , Brenda M. Rubenstein , Miguel A. Morales

A functional theory based on single-particle occupation numbers is developed for pairing. This functional, that generalizes the BCS approach, directly incorporates corrections due to particle number conservation. The functional is…

Nuclear Theory · Physics 2015-05-18 Denis Lacroix , Guillaume Hupin

We present theoretical prospects for creating p-wave paired BCS states of magnetic trapped fermionic atoms. Based on our earlier proposal of using dc electric fields to control both the strength and anisotropic characteristic of atom-atom…

Statistical Mechanics · Physics 2009-10-31 L. You , M. Marinescu

Using trial wavefunctions prepared on quantum devices to reduce the bias of auxiliary-field quantum Monte Carlo (QC-AFQMC) has established itself as a promising hybrid approach to the simulation of strongly correlated many body systems.…

Quantum Physics · Physics 2024-09-16 Matthew Kiser , Matthias Beuerle , Fedor Simkovic

In recent decades, there have been increasing interests in quantum statistics beyond the standard Fermi-Dirac and Bose-Einstein statistics, such as the fractional statistics, quon statistics, anyon statistics and quantum groups, since they…

Statistical Mechanics · Physics 2018-12-26 Xu-Yang Hou , Xun Huang , Yan He , Hao Guo

In the present work, we start from a minimal Hamiltonian for Fermi systems where the s-wave scattering is the only low energy constant at play. Many-Body Perturbative approach that is usually valid at rather low density is first discussed.…

Nuclear Theory · Physics 2020-01-08 Antoine Boulet , Denis Lacroix

The BCS-to-BEC crossover, as well as the nature of Cooper pairs, in a superconducting and Fermi superfluid medium is studied from the exact ground state wavefunction of the reduced BCS Hamiltonian. As the strength of the interaction…

Superconductivity · Physics 2009-11-11 Gerardo Ortiz , Jorge Dukelsky

An efficient numerical method is developed using the matrix product formalism for computing the properties at finite energy densities in one-dimensional (1D) many-body localized (MBL) systems. Arguing that any efficient (possibly quantum)…

Disordered Systems and Neural Networks · Physics 2015-08-20 Yichen Huang

Despite the remarkable progress of deep-learning methods generating a target vital sign waveform from a source vital sign waveform, most existing models are designed exclusively for a specific source-to-target pair. This requires distinct…

Sound · Computer Science 2025-06-11 Franck Meyer , Kyunghoon Hur , Edward Choi

Approximate Bayesian computation methods can be used to evaluate posterior distributions without having to calculate likelihoods. In this paper we discuss and apply an approximate Bayesian computation (ABC) method based on sequential Monte…

Computation · Statistics 2009-01-15 Tina Toni , David Welch , Natalja Strelkowa , Andreas Ipsen , Michael P. H. Stumpf

In recent years dynamical modelling has been provided with a range of breakthrough methods to perform exact Bayesian inference. However it is often computationally unfeasible to apply exact statistical methodologies in the context of large…

Computation · Statistics 2014-12-24 Umberto Picchini , Julie Lyng Forman

The phaseless auxiliary-field quantum Monte Carlo (AF QMC) method [S. Zhang and H. Krakauer, Phys. Rev. Lett. 90, 136401 (2003)] is used to carry out a systematic study of the dissociation and ionization energies of second-row group 3A-7A…

Materials Science · Physics 2007-06-25 Malliga Suewattana , Wirawan Purwanto , Shiwei Zhang , Henry Krakauer , Eric J. Walter

Ab initio quantum Monte Carlo (QMC) methods are state-of-the-art electronic structure calculations based on highly parallelizable stochastic frameworks for accurate solutions of the many-body Schr{\"o}dinger equation, suitable for modern…

Chemical Physics · Physics 2026-04-07 Kousuke Nakano , Stefano Battaglia , Jürg Hutter

Blind source separation (BSS) is a very popular technique to analyze multichannel data. In this context, the data are modeled as the linear combination of sources to be retrieved. For that purpose, standard BSS methods all rely on some…

Applications · Statistics 2015-06-23 Jerome Bobin , Jeremy Rapin , Anthony Larue , Jean-Luc Starck

Although BCS wave function for superconductors under periodic boundary conditions are well-established, obtaining an explicit form of the many-body BCS wave function under open boundary condition is usually a nontrivial problem. In this…

Superconductivity · Physics 2025-11-10 Jiarui Jiao , Chao Xu , Congjun Wu , Wang Yang

Accurate wave-function descriptions of pristine and defected solids remain challenging due to the simultaneous presence of finite-size, basis-set, and correlation errors. While embedding techniques alleviate finite-size effects and…

We propose a general variational fermionic many-body wavefunction that generates an effective Hamiltonian in a quadratic form, which can then be exactly solved. The theory can be constructed within the density functional theory framework,…

Strongly Correlated Electrons · Physics 2020-10-30 Xindong Wang , Xiao Chen , Liqin Ke , Hai-Ping Cheng , B. N. Harmon

We expand upon the recent semi-stochastic adaptation to full configuration interaction quantum Monte Carlo (FCIQMC). We present an alternate method for generating the deterministic space without a priori knowledge of the wave function and…

Computational Physics · Physics 2015-11-17 N. S. Blunt , Simon D. Smart , J. A. F. Kersten , J. S. Spencer , George H. Booth , Ali Alavi

We explore different ways of incorporating accurate trial wave functions into free projection auxiliary field quantum Monte Carlo (fp-AFQMC). Trial states employed include coupled cluster singles and doubles, multi-Slater, and symmetry…

Chemical Physics · Physics 2021-04-15 Ankit Mahajan , Sandeep Sharma

Approximate Bayesian computation (ABC) using a sequential Monte Carlo method provides a comprehensive platform for parameter estimation, model selection and sensitivity analysis in differential equations. However, this method, like other…

Machine Learning · Statistics 2015-07-21 Sanmitra Ghosh , Srinandan Dasmahapatra , Koushik Maharatna