Quantum Monte Carlo with very large multideterminant wavefunctions

An algorithm to compute efficiently the first two derivatives of (very) large multideterminant wavefunctions for quantum Monte Carlo calculations is presented. The calculation of determinants and their derivatives is performed using the Sherman-Morrison formula for updating the inverse Slater matrix. An improved implementation based on the reduction of the number of column substitutions and on a very efficient implementation of the calculation of the scalar products involved is presented. It is emphasized that multideterminant expansions contain in general a large number of identical spin-specific determinants: for typical configuration interaction-type wavefunctions the number of unique spin-specific determinants $N_{\rm det}^\sigma$ ($\sigma=\uparrow,\downarrow$) with a non-negligible weight in the expansion is of order ${\cal O}(\sqrt{N_{\rm det}})$. We show that a careful implementation of the calculation of the $N_{\rm det}$-dependent contributions can make this step negligible enough so that in practice the algorithm scales as the total number of unique spin-specific determinants, $\; N_{\rm det}^\uparrow + N_{\rm det}^\downarrow$, over a wide range of total number of determinants (here, $N_{\rm det}$ up to about one million), thus greatly reducing the total computational cost. Finally, a new truncation scheme for the multideterminant expansion is proposed so that larger expansions can be considered without increasing the computational time. The algorithm is illustrated with all-electron Fixed-Node Diffusion Monte Carlo calculations of the total energy of the chlorine atom. Calculations using a trial wavefunction including about 750 000 determinants with a computational increase of $\sim$ 400 compared to a single-determinant calculation are shown to be feasible.Comment: 9 pages, 3 figure

Spin adaptation with determinant-based selected configuration interaction

Selected configuration interaction (sCI) methods, when complemented with a second order perturbative correction , provide near full configuration interaction (FCI) quality energies with only a small fraction of the Slater determinants of the FCI space. The selection of the determinants is often implemented in a determinant-based formalism, and therefore does not provide spin adapted wave functions. In other words, sCI wave functions are not eigenfunctions of theŜ 2 operator. In some situations, having a spin adapted wave function is essential for the proper convergence of the method. We propose an efficient algorithm which, given an arbitrary determinant space, generates all the missing Slater determinants allowing one to obtain spin adapted wave functions while avoiding working with configuration state functions. For example, generating all the possible determinants with 6 up-spin and 6 down-spin electrons in 12 open shells takes 21 CPU cycles per generated Slater determinant. We also propose a modification of the denominators in the Epstein-Nesbet perturbation theory reducing significantly the non-invariance of the second order correction with respect to different values of the spin quantum number m s. The computational cost of this correction is also negligible

Calcul haute performance & chimie quantique

This thesis work has two main objectives: 1. To develop and apply original electronic structure methods for quantum chemistry 2. To implement several computational strategies to achieve efficient large-scale computer simulations. In the first part, both the Configuration Interaction (CI) and the Quantum Monte Carlo (QMC) methods used in this work for calculating quantum properties are presented. We then describe more specifically the selected CI approach (so-called CIPSI approach, Configuration Interaction using a Perturbative Selection done Iteratively) that we used for building trial wavefunctions for QMC simulations. As a first application, we present the QMC calculation of the total non-relativistic energies of transition metal atoms of the 3d series. This work, which has required the implementation of Slater type basis functions in our codes, has led to the best values ever published for these atoms. We then present our original implementation of the pseudo-potentials for QMC and discuss the calculation of atomization energies for a benchmark set of 55 organic molecules. The second part is devoted to the Hight Performance Computing (HPC) aspects. The objective is to make possible and/or facilitate the deployment of very large-scale simulations. From the point of view of the developer it includes: The use of original programming paradigms, single-core optimization process, massively parallel calculations on grids (supercomputer and Cloud), development of collaborative tools , etc - and from the user's point of view: Improved code installation, management of the input/output parameters, GUI, interfacing with other codes, etc.L'objectif de ce travail de thèse est double : - Le développement et application de méthodes originales pour la chimie quantique ; - La mise au point de stratégies informatiques variées permettant la réalisation de simulations à grande échelle. Dans la première partie, les méthodes d'integration de configuration (IC) et monte carlo quantique (QMC) utilisées dans ce travail pour le calcul des propriétés quantiques sont présentées. Nous détaillerons en particulier la méthode d'\IC sélectionnée perturbativement (CISPI) que nous avons utilisée pour construire des fonctions d'onde d'essai pour le QMC. La première application concerne le calcul des énergies totales non-relativistes des atomes de transition de la série 3d ; ceci a nécessité l'implémentation de fonctions de base de type Slater et a permis d'obtenir les meilleures valeurs publiées à ce jour. La deuxième application concerne l'implémentation de pseudo-potentiels adaptés à notre approche QMC, avec pour application une étude concernant le calcul des énergies d'atomisation d'un ensemble de 55 molécules. La seconde partie traite des aspects calcule haute performance (HPC) avec pour objectif l'aide au déploiement des simulations à très grande échelle, aussi bien sous l'aspect informatique proprement dit - utilisation de paradigmes de programmation originaux, optimisation des processus monocœurs, calculs massivement parallèles sur grilles de calcul (supercalculateur et Cloud), outils d'aide au développement collaboratif \textit{et cætera} -, que sous l'aspect \emph{utilisateur} - installation, gestion des paramètres d'entrée et de sortie, interface graphique, interfaçage avec d'autres codes. L'implémentation de ces différents aspects dans nos codes-maison quantum pakcage et qmc=chem est également présentée

Spin adaptation with determinant-based selected configuration interaction

Selected configuration interaction (sCI) methods, when complemented with a second order perturbative correction, provide near full configuration interaction (FCI) quality energies with only a small fraction of the Slater determinants of the FCI space. The selection of the determinants is often implemented in a determinant-based formalism, and therefore does not provide spin adapted wave functions. In other words, sCI wave functions are not eigenfunctions of the $\widehat{S^2}$ operator. In some situations, having a spin adapted wave function is essential for the proper convergence of the method. We propose an efficient algorithm which, given an arbitrary determinant space, generates all the missing Slater determinants allowing one to obtain spin adapted wave functions while avoiding working with configuration state functions. For example, generating all the possible determinants with 6 up-spin and 6 down-spin electrons in 12 open shells takes 21 CPU cycles per generated Slater determinant. We also propose a modification of the denominators in the Epstein-Nesbet perturbation theory reducing significantly the non-invariance of the second order correction with respect to different values of the spin quantum number $m_s$. The computational cost of this correction is also negligible

ABINIT: Overview and focus on selected capabilities

Paper published as part of the special topic on Electronic Structure SoftwareABINIT is probably the first electronic-structure package to have been released under an open-source license about 20 years ago. It implements density functional theory, density-functional perturbation theory (DFPT), many-body perturbation theory (GW approximation and Bethe–Salpeter equation), and more specific or advanced formalisms, such as dynamical mean-field theory (DMFT) and the “temperaturedependent effective potential” approach for anharmonic effects. Relying on planewaves for the representation of wavefunctions, density, and other space-dependent quantities, with pseudopotentials or projector-augmented waves (PAWs), it is well suited for the study of periodic materials, although nanostructures and molecules can be treated with the supercell technique. The present article starts with a brief description of the project, a summary of the theories upon which ABINIT relies, and a list of the associated capabilities. It then focuses on selected capabilities that might not be present in the majority of electronic structure packages either among planewave codes or, in general, treatment of strongly correlated materials using DMFT; materials under finite electric fields; properties at nuclei (electric field gradient, Mössbauer shifts, and orbital magnetization); positron annihilation; Raman intensities and electro-optic effect; and DFPT calculations of response to strain perturbation (elastic constants and piezoelectricity), spatial dispersion (flexoelectricity), electronic mobility, temperature dependence of the gap, and spin-magnetic-field perturbation. The ABINIT DFPT implementation is very general, including systems with van der Waals interaction or with noncollinear magnetism. Community projects are also described: generation of pseudopotential and PAW datasets, high-throughput calculations (databases of phonon band structure, second-harmonic generation, and GW computations of bandgaps), and the library LIBPAW. ABINIT has strong links with many other software projects that are briefly mentioned.This work (A.H.R.) was supported by the DMREF-NSF Grant No. 1434897, National Science Foundation OAC-1740111, and U.S. Department of Energy DE-SC0016176 and DE-SC0019491 projects. N.A.P. and M.J.V. gratefully acknowledge funding from the Belgian Fonds National de la Recherche Scientifique (FNRS) under Grant No. PDR T.1077.15-1/7. M.J.V. also acknowledges a sabbatical “OUT” grant at ICN2 Barcelona as well as ULiège and the Communauté Française de Belgique (Grant No. ARC AIMED G.A. 15/19-09). X.G. and M.J.V. acknowledge funding from the FNRS under Grant No. T.0103.19-ALPS. X.G. and G.-M. R. acknowledge support from the Communauté française de Belgique through the SURFASCOPE Project (No. ARC 19/24-057). X.G. acknowledges the hospitality of the CEA DAM-DIF during the year 2017. G.H. acknowledges support from the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division under Contract No. DE-AC02-05-CH11231 (Materials Project Program No. KC23MP). The Belgian authors acknowledge computational resources from supercomputing facilities of the University of Liège, the Consortium des Equipements de Calcul Intensif (Grant No. FRS-FNRS G.A. 2.5020.11), and Zenobe/CENAERO funded by the Walloon Region under Grant No. G.A. 1117545. M.C. and O.G. acknowledge support from the Fonds de Recherche du Québec Nature et Technologie (FRQ-NT), Canada, and the Natural Sciences and Engineering Research Council of Canada (NSERC) under Grant No. RGPIN-2016-06666. The implementation of the libpaw library (M.T., T.R., and D.C.) was supported by the ANR NEWCASTLE project (Grant No. ANR-2010-COSI-005-01) of the French National Research Agency. M.R. and M.S. acknowledge funding from Ministerio de Economia, Industria y Competitividad (MINECO-Spain) (Grants Nos. MAT2016-77100-C2-2-P and SEV-2015-0496) and Generalitat de Catalunya (Grant No. 2017 SGR1506). This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation program (Grant Agreement No. 724529). P.G. acknowledges support from FNRS Belgium through PDR (Grant No. HiT4FiT), ULiège and the Communauté française de Belgique through the ARC project AIMED, the EU and FNRS through M.ERA.NET project SIOX, and the European Funds for Regional Developments (FEDER) and the Walloon Region in the framework of the operational program “Wallonie-2020.EU” through the project Multifunctional thin films/LoCoTED. The Flatiron Institute is a division of the Simons Foundation. A large part of the data presented in this paper is available directly from the Abinit Web page www.abinit.org. Any other data not appearing in this web page can be provided by the corresponding author upon reasonable request.Peer reviewe

Hight performance computing & quantum chemistry

L'objectif de ce travail de thèse est double : - Le développement et application de méthodes originales pour la chimie quantique ; - La mise au point de stratégies informatiques variées permettant la réalisation de simulations à grande échelle. Dans la première partie, les méthodes d'integration de configuration (IC) et monte carlo quantique (QMC) utilisées dans ce travail pour le calcul des propriétés quantiques sont présentées. Nous détaillerons en particulier la méthode d'\IC sélectionnée perturbativement (CISPI) que nous avons utilisée pour construire des fonctions d'onde d'essai pour le QMC. La première application concerne le calcul des énergies totales non-relativistes des atomes de transition de la série 3d ; ceci a nécessité l'implémentation de fonctions de base de type Slater et a permis d'obtenir les meilleures valeurs publiées à ce jour. La deuxième application concerne l'implémentation de pseudo-potentiels adaptés à notre approche QMC, avec pour application une étude concernant le calcul des énergies d'atomisation d'un ensemble de 55 molécules. La seconde partie traite des aspects calcule haute performance (HPC) avec pour objectif l'aide au déploiement des simulations à très grande échelle, aussi bien sous l'aspect informatique proprement dit - utilisation de paradigmes de programmation originaux, optimisation des processus monocœurs, calculs massivement parallèles sur grilles de calcul (supercalculateur et Cloud), outils d'aide au développement collaboratif \textit{et cætera} -, que sous l'aspect \emph{utilisateur} - installation, gestion des paramètres d'entrée et de sortie, interface graphique, interfaçage avec d'autres codes. L'implémentation de ces différents aspects dans nos codes-maison quantum pakcage et qmc=chem est également présentée.This thesis work has two main objectives: 1. To develop and apply original electronic structure methods for quantum chemistry 2. To implement several computational strategies to achieve efficient large-scale computer simulations. In the first part, both the Configuration Interaction (CI) and the Quantum Monte Carlo (QMC) methods used in this work for calculating quantum properties are presented. We then describe more specifically the selected CI approach (so-called CIPSI approach, Configuration Interaction using a Perturbative Selection done Iteratively) that we used for building trial wavefunctions for QMC simulations. As a first application, we present the QMC calculation of the total non-relativistic energies of transition metal atoms of the 3d series. This work, which has required the implementation of Slater type basis functions in our codes, has led to the best values ever published for these atoms. We then present our original implementation of the pseudo-potentials for QMC and discuss the calculation of atomization energies for a benchmark set of 55 organic molecules. The second part is devoted to the Hight Performance Computing (HPC) aspects. The objective is to make possible and/or facilitate the deployment of very large-scale simulations. From the point of view of the developer it includes: The use of original programming paradigms, single-core optimization process, massively parallel calculations on grids (supercomputer and Cloud), development of collaborative tools , etc - and from the user's point of view: Improved code installation, management of the input/output parameters, GUI, interfacing with other codes, etc

Screened Coulomb interaction calculations: cRPA implementation and applications to dynamical screening and self-consistency in uranium dioxide and cerium

see also Erratum Phys. Rev. B 96, 199907 (2017) - https://journals.aps.org/prb/abstract/10.1103/PhysRevB.96.199907International audienceWe report an implementation of the constrained Random Phase Approximation (cRPA) method within the Projector Augmented-Wave framework. It allows for the calculation of the screened interaction in the same Wannier orbitals as our recent DFT+$U$ and DFT+DMFT implementations. We present calculations of the dynamical Coulomb screened interaction in uranium dioxide and $\alpha$ and $\gamma$ cerium on Wannier functions. We show that a self-consistent calculation of the static screened interaction in DFT+$U$ together with a consistent Wannier basis is mandatory for $\gamma$ cerium and uranium dioxide. We emphasize that a static approximation for the screened interaction in $\alpha$ cerium is too drastic

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Spin-adapted selected configuration interaction in a determinant basis

International audienceSelected configuration interaction (sCI) methods, when complemented with a second order perturbative correction , provide near full configuration interaction (FCI) quality energies with only a small fraction of the Slater determinants of the FCI space. The selection of the determinants is often implemented in a determinant-based formalism, and therefore does not provide spin adapted wave functions. In other words, sCI wave functions are not eigenfunctions of theŜ 2 operator. In some situations, having a spin adapted wave function is essential for the proper convergence of the method. We propose an efficient algorithm which, given an arbitrary determinant space, generates all the missing Slater determinants allowing one to obtain spin adapted wave functions while avoiding working with configuration state functions. For example, generating all the possible determinants with 6 up-spin and 6 down-spin electrons in 12 open shells takes 21 CPU cycles per generated Slater determinant. We also propose a modification of the denominators in the Epstein-Nesbet perturbation theory reducing significantly the non-invariance of the second order correction with respect to different values of the spin quantum number m s. The computational cost of this correction is also negligible