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We apply the method of Monte Carlo configuration interaction (MCCI) to calculate ground-state potential energy curves for a range of small molecules and compare the results with full configuration interaction. We show that the MCCI…

Chemical Physics · Physics 2012-12-12 J. P. Coe , D. J. Taylor , M. J. Paterson

Ab initio calculations face the challenge of describing a complex multiscale quantum many-body system. The nuclear wave function has both strong short-range correlations and long-range contributions. Natural orbitals provide a means of…

Nuclear Theory · Physics 2017-04-11 Chrysovalantis Constantinou

We calculate potential curves for transition metal dimers using Monte Carlo configuration interaction (MCCI). These results, and their associated spectroscopic values, are compared with experimental and computational studies. The…

Chemical Physics · Physics 2014-05-23 J. P. Coe , P. Murphy , M. J. Paterson

Ab initio no-core configuration interaction (NCCI) calculations for the nuclear many-body problem have traditionally relied upon an antisymmetrized product (Slater determinant) basis built from harmonic oscillator orbitals. The accuracy of…

The method of Monte Carlo configuration interaction (MCCI) [1,2] is applied to the calculation of multipole moments. We look at the ground and excited state dipole moments in carbon monoxide. We then consider the dipole of NO, the…

Chemical Physics · Physics 2013-04-12 J. P. Coe , D. J. Taylor , M. J. Paterson

The concept of machine learning configuration interaction (MLCI) [J. Chem. Theory Comput. 2018, 14, 5739], where an artificial neural network (ANN) learns on the fly to select important configurations, is further developed so that accurate…

Chemical Physics · Physics 2019-10-31 J. P. Coe

We investigate the performance of a class of compact and systematically improvable Jastrow-Slater wave functions for the efficient and accurate computation of structural properties, where the determinantal component is expanded with a…

Chemical Physics · Physics 2019-01-17 Monika Dash , Saverio Moroni , Anthony Scemama , Claudia Filippi

We study several approaches to orbital optimization in selected configuration interaction plus perturbation theory (SCI+PT) methods, and test them on the ground and excited states of three molecules using the semistochastic heatbath…

Chemical Physics · Physics 2021-07-14 Yuan Yao , C. J. Umrigar

While first order perturbation theory is routinely used in quantum Monte Carlo (QMC) calculations, higher-order terms present significant numerical challenges. We present a new approach for computing perturbative corrections in projection…

Nuclear Theory · Physics 2022-06-16 Bing-Nan Lu , Ning Li , Serdar Elhatisari , Yuan-Zhuo Ma , Dean Lee , Ulf-G. Meißner

We introduce state-averaging into the method of Monte Carlo configuration interaction (SA-MCCI) to allow the stable and efficient calculation of excited states. We show that excited potential curves for H$_{3}$, including a crossing with…

Chemical Physics · Physics 2014-03-03 J. P. Coe , M. J. Paterson

We propose the concept of machine learning configuration interaction (MLCI) whereby an artificial neural network is trained on-the-fly to predict important new configurations in an iterative selected configuration interaction procedure. We…

Chemical Physics · Physics 2018-10-18 J. P. Coe

Selective configuration interaction methods approximate correlated molecular ground- and excited states by considering only the most relevant Slater determinants in the expansion. While a recently proposed neural-network-assisted approach…

Nonorthogonal multireference methods can predict statically correlated adiabatic energies while providing chemical insight through the combination of diabatic reference states. However, reaching quantitative accuracy using nonorthogonal…

Chemical Physics · Physics 2020-07-30 Hugh G. A. Burton , Alex J. W. Thom

The original formulation (Phys. Rev. Lett. 119, 063002, 2017) of the natural orbital functional - second-order M{\o}ller-Plesset (NOF-MP2) method is based on the MP2 that uses the canonical Hartree-Fock molecular orbitals. The current work…

Chemical Physics · Physics 2018-08-22 Mario Piris

The potential energy curve of the F$_2$ molecule is calculated with Fixed-Node Diffusion Monte Carlo (FN-DMC) using Configuration Interaction (CI)-type trial wavefunctions. To keep the number of determinants reasonable (the first and second…

Chemical Physics · Physics 2016-07-25 Emmanuel Giner , Anthony Scemama , Michel Caffarel

The multi-configurational self-consistent field theory is considered the standard starting point for almost all multireference approaches required for strongly-correlated molecular problems. The limitation of the approach is generally given…

Chemical Physics · Physics 2015-10-14 Robert E. Thomas , Qiming Sun , Ali Alavi , George H. Booth

We explore the use in quantum Monte Carlo (QMC) of trial wave functions consisting of a Jastrow factor multiplied by a truncated configuration-interaction (CI) expansion in Slater determinants obtained from a CI perturbatively selected…

Chemical Physics · Physics 2016-01-25 Emmanuel Giner , Roland Assaraf , Julien Toulouse

In this work, we introduce three algorithmic improvements to reduce the cost and improve the scaling of orbital space variational Monte Carlo (VMC). First, we show that by appropriately screening the one- and two-electron integrals of the…

Chemical Physics · Physics 2018-07-30 Iliya Sabzevari , Sandeep Sharma

An accurate description of electron correlation is one of the most challenging problems in quantum chemistry. The exact electron correlation can be obtained by means of full configuration interaction (FCI). A simple strategy for…

Chemical Physics · Physics 2021-05-14 Jae Woo Park

Finding optimal reaction coordinates and predicting accurate kinetic rates for activated processes are two of the foremost challenges of molecular simulations. We introduce an algorithm that tackles the two problems at once: starting from a…

Statistical Mechanics · Physics 2023-10-30 Line Mouaffac , Karen Palacio-Rodriguez , Fabio Pietrucci
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