English
Related papers

Related papers: Multireference configuration interaction and pertu…

200 papers

Most nonrelativistic electron correlation methods can be adapted to account for relativistic effects, as long as the relativistic molecular spinor integrals are available, from either a four-, two-, or one-component mean-field calculation.…

Strongly Correlated Electrons · Physics 2024-07-17 Zijun Zhao , Francesco A. Evangelista

An active space variational calculation of the 2-electron reduced density matrix (2-RDM) is derived and implemented where the active orbitals are correlated within the pair approximation. The pair approximation considers only doubly…

Chemical Physics · Physics 2020-10-13 Kade Head-Marsden , David A. Mazziotti

Accurate solution of the many-electron problem including correlations remains intractable except for few-electron systems. Describing interacting electrons as a superposition of independent electron configurations results in an apparent…

Computational Physics · Physics 2024-02-20 J. C. Greer

We investigate configuration-interaction (CI) calculations on a basis of molecular orbitals generated by preliminary density-functional theory (DFT) calculations. We use this CI/DFT framework to improve the modeling of core-excited states…

Chemical Physics · Physics 2025-09-11 Giorgio Visentin , Francois Mauger

Efficiently recovering dynamic correlation in strongly correlated systems without incurring prohibitive computational costs remains a central challenge in quantum chemistry. In this Perspective, we review and benchmark methods capable of…

Chemical Physics · Physics 2026-05-22 Michał Hapka , Aleksandra Tucholska , Katarzyna Pernal

We report internally contracted relativistic multireference configuration interaction (ic-MRCI), complete active space second-order perturbation (CASPT2), and strongly contracted n-electron valence state perturbation theory (NEVPT2) on the…

Chemical Physics · Physics 2015-12-31 Toru Shiozaki , Wataru Mizukami

By combining Hartree-Fock with a neural-network-supported quantum-cluster solver proposed recently in the context of solid-state lattice models, we formulate a scheme for selective neural-network configuration interaction (NNCI)…

We present an ab-initio dynamical configuration interaction (DCI) study of free- and Mg-porphyrin. DCI is a recently developed active space theory based on the L\"owdin downfolding technique. In the active space, static correlation is…

Materials Science · Physics 2020-06-18 Marc Dvorak , Patrick Rinke

The tailored coupled cluster (TCC) approach is a promising ansatz that preserves the simplicity of single-reference coupled cluster theory, while incorporating a multi-reference wave function through amplitudes obtained from a preceding…

Chemical Physics · Physics 2021-01-07 Maximilian Mörchen , Leon Freitag , Markus Reiher

Given a number of datasets for evaluating the performance of single reference methods for the low-lying excited states of closed-shell molecules, a comprehensive dataset for assessing the performance of multireference methods for the…

Chemical Physics · Physics 2024-11-07 Yangyang Song , Ning Zhang , Yibo Lei , Yang Guo , Wenjian Liu

The multi-reference Coupled Cluster method first proposed by Meller et al (J. Chem. Phys. 1996) has been implemented and tested. Guess values of the amplitudes of the single and double excitations (the ${\hat T}$ operator) on the top of the…

Chemical Physics · Physics 2016-04-11 Emmanuel Giner , Grégoire David , Anthony Scemama , Jean Paul Malrieu

The second-order multireference driven similarity renormalization group perturbation theory (DSRG-MRPT2) theory provides an efficient means of correcting the dynamical correlation with the multiconfiguration reference function. The…

Chemical Physics · Physics 2022-02-01 Jae Woo Park

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

A hybrid stochastic-deterministic approach for computing the second-order perturbative contribution $E^{(2)}$ within multireference perturbation theory (MRPT) is presented. The idea at the heart of our hybrid scheme --- based on a…

Chemical Physics · Physics 2018-05-31 Yann Garniron , Anthony Scemama , Pierre-François Loos , Michel Caffarel

Selected configuration interaction (sCI) methods including second-order perturbative corrections provide near full CI (FCI) quality energies with only a small fraction of the determinants of the FCI space. Here, we introduce both a…

Chemical Physics · Physics 2018-08-09 Yann Garniron , Anthony Scemama , Emmanuel Giner , Michel Caffarel , Pierre-François Loos

It is well-known that not only the orbital ordering but also the choice of the orbitals themselves as the basis may significantly influence the computational efficiency of density-matrix renormalization group (DMRG) calculations. In this…

Strongly Correlated Electrons · Physics 2013-06-14 Yingjin Ma , Haibo Ma

Neutral uranium (U I) is a very difficult atom for theoretical calculations due to a large number of valence electrons, six, strong valence-valence and valence-core correlations, high density of states, and relativistic effects.…

Atomic Physics · Physics 2020-10-14 Igor M. Savukov

We propose a data-driven approach using a Restricted Boltzmann Machine (RBM) to solve the Schr\"odinger equation in configuration space. Traditional Configuration Interaction (CI) methods construct the wavefunction as a linear combination…

Coordinated multi-robot motion planning at intersections is key for safe mobility in roads, factories and warehouses. The rapidly exploring random tree (RRT) algorithms are popular in multi-robot motion planning. However, generating the…

Robotics · Computer Science 2024-12-03 Victor Parque

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