index - Méthodes et outils de la chimie quantique

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The era of exascale computing presents both exciting opportunities and unique challenges for quantum mechanical simulations. While the transition from petaflops to exascale computing has been marked by a steady increase in computational power, the shift towards heterogeneous architectures, particularly the dominant role of graphical processing units (GPUs), demands a fundamental shift in software development strategies. This review examines the changing landscape of hardware and software for exascale computing, highlighting the limitations of traditional algorithms and software implementations in light of the increasing use of heterogeneous architectures in high-end systems. We discuss the challenges of adapting quantum chemistry software to these new architectures, including the fragmentation of the software stack, the need for more efficient algorithms (including reduced precision versions) tailored for GPUs, and the importance of developing standardized libraries and programming models.

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We introduce a novel three-body correlation factor that is designed to vanish in the core region around each nucleus and approach a universal two-body correlation factor for valence electrons. The Transcorrelated Hamiltonian is used to optimize the orbitals of a single Slater determinant within a biorthonormal framework. The Slater-Jastrow wave function is optimized on a set of atomic and molecular systems containing both second-row elements and $3d$ transition metal elements. The optimization of the correlation factor and the orbitals, along with increasing the basis set, results in a systematic lowering of the Variational Monte Carlo energy for all systems tested. Importantly, the optimal parameters of the correlation factor obtained for atomic systems are transferable to molecules. Additionally, the present correlation factor is computationally efficient, using a mixed analytical-numerical integration scheme that reduces the costly numerical integration from $\mathbb{R}^6$ to $\mathbb{R}^3$.

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<div xmlns="http://www.tei-c.org/ns/1.0"><p>A program is a function p : input -→ output If the output of a program p 1 is of the same type as the input of a program p 2 , we can define a new program p 3 = p 2 • p</p></div>

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Sujets

Atrazine Diatomic molecules 3115aj Petascale Anderson mechanism BIOMOLECULAR HOMOCHIRALITY Approximation GW Green's function Corrélation électronique 3470+e Excited states ALGORITHM Line formation Biodegradation Coupled cluster Large systems Spin-orbit interactions 3115vj Argon Single-core optimization Ab initio calculation Relativistic corrections X-ray spectroscopy QSAR Acrolein CIPSI Wave functions Azide Anion Density functional theory Dipole Atrazine-cations complexes Molecular descriptors BSM physics Carbon Nanotubes Argile Atomic and molecular structure and dynamics Range separation 3115am Atomic and molecular collisions Time reversal violation Aimantation Molecular properties Quantum Monte Carlo A priori Localization CP violation Fonction de Green Configuration Interaction Dirac equation Atom Chimie quantique Relativistic quantum mechanics Configuration interaction Configuration interactions Auto-énergie Atomic charges Atomic data États excités Adiabatic connection 3115ag Coupled cluster calculations Parity violation Diffusion Monte Carlo Pesticide AROMATIC-MOLECULES Xenon Numerical calculations New physics Analytic gradient Quantum Chemistry Relativistic quantum chemistry Time-dependent density-functional theory Electron correlation Chemical concepts BENZENE MOLECULE 3115bw Parallel speedup Valence bond Ion Electron electric moment AB-INITIO Mécanique quantique relativiste Quantum chemistry AB-INITIO CALCULATION Théorie des perturbations Atoms Hyperfine structure Electron electric dipole moment Polarizabilities Pesticides Metabolites Clustering Molecular modeling Environmental fate Partial least squares 3115ae 3315Fm A posteriori Localization Atomic charges chemical concepts maximum probability domain population Atomic processes Perturbation theory Ground states Rydberg states 3115vn Abiotic degradation Dispersion coefficients

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