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ipie is a Python-based auxiliary-field quantum Monte Carlo (AFQMC) package that has undergone substantial improvements since its initial release [J. Chem. Theory Comput., 2022, 19(1): 109-121]. This paper outlines the improved modularity and new capabilities implemented in ipie. We highlight the ease of incorporating different trial and walker types and the seamless integration of ipie with external libraries. We enable distributed Hamiltonian simulations, allowing for multi-GPU simulations of large systems. This development enabled us to compute the interaction energy of a benzene dimer with 84 electrons and 1512 orbitals, which otherwise would not have fit on a single GPU. We also support GPU-accelerated multi-slater determinant trial wavefunctions [arXiv:2406.08314] to enable efficient and highly accurate simulations of large-scale systems. This allows for near-exact ground state energies of multi-reference clusters, [Cu$_2$O$_2$]$^{2+}$ and [Fe$_2$S$_2$(SCH$_3$)]$^{2-}$. We also describe implementations of free projection AFQMC, finite temperature AFQMC, AFQMC for electron-phonon systems, and automatic differentiation in AFQMC for calculating physical properties. These advancements position ipie as a leading platform for AFQMC research in quantum chemistry, facilitating more complex and ambitious computational method development and their applications.
Hedin's equations provide an elegant route to compute the exact one-body Green's function (or propagator) via the self-consistent iteration of a set of non-linear equations. Its first-order approximation, known as $GW$, corresponds to a resummation of ring diagrams and has shown to be extremely successful in physics and chemistry. Systematic improvement is possible, although challenging, via the introduction of vertex corrections. Considering anomalous propagators and an external pairing potential, we derive a new self-consistent set of closed equations equivalent to the famous Hedin equations but having as a first-order approximation the particle-particle (pp) $T$-matrix approximation where one performs a resummation of the ladder diagrams. This pp version of Hedin's equations offers a way to go systematically beyond the $T$-matrix approximation by accounting for low-order pp vertex corrections.
The Bethe–Salpeter equation (BSE) is the key equation in many-body perturbation theory based on Green's functions to access response properties. Within the GW approximation to the exchange-correlation kernel, the BSE has been successfully applied to several finite and infinite systems. However, it also shows some failures, such as underestimated triplet excitation energies, lack of double excitations, ground-state energy instabilities in the dissociation limit, etc. In this work, we study the performance of the BSE within the GW approximation as well as the T-matrix approximation for the excitation energies of the exactly solvable asymmetric Hubbard dimer. This model allows one to study various correlation regimes by varying the on-site Coulomb interaction U as well as the degree of the asymmetry of the system by varying the difference of potential Δv between the two sites. We show that, overall, the GW approximation gives more accurate excitation energies than GT over a wide range of U and Δv. However, the strongly correlated (i.e., large U) regime still remains a challenge.
We introduce a novel algorithm that leverages stochastic sampling techniques to compute the perturbative triples correction in the coupled-cluster (CC) framework. By combining elements of randomness and determinism, our algorithm achieves a favorable balance between accuracy and computational cost. The main advantage of this algorithm is that it allows for the calculation to be stopped at any time, providing an unbiased estimate, with a statistical error that goes to zero as the exact calculation is approached. We provide evidence that our semi-stochastic algorithm achieves substantial computational savings compared to traditional deterministic methods. Specifically, we demonstrate that a precision of 0.5 millihartree can be attained with only 10\% of the computational effort required by the full calculation. This work opens up new avenues for efficient and accurate computations, enabling investigations of complex molecular systems that were previously computationally prohibitive.
Sujets
BENZENE MOLECULE
Electron correlation
Wave functions
Range separation
Argile
Atomic and molecular collisions
Relativistic quantum mechanics
Numerical calculations
3115am
Electron electric moment
Atrazine-cations complexes
Ground states
A posteriori Localization
BSM physics
Petascale
Dipole
Spin-orbit interactions
Carbon Nanotubes
Atomic processes
Auto-énergie
Pesticides Metabolites Clustering Molecular modeling Environmental fate Partial least squares
Chemical concepts
Atomic and molecular structure and dynamics
Configuration Interaction
Diatomic molecules
AB-INITIO
Adiabatic connection
Coupled cluster
Atomic charges chemical concepts maximum probability domain population
Relativistic quantum chemistry
CIPSI
Pesticide
Fonction de Green
X-ray spectroscopy
Parity violation
Rydberg states
Molecular properties
Quantum Monte Carlo
Dirac equation
3470+e
New physics
Chimie quantique
AB-INITIO CALCULATION
Diffusion Monte Carlo
Anderson mechanism
Line formation
Time reversal violation
BIOMOLECULAR HOMOCHIRALITY
3115vj
Dispersion coefficients
Density functional theory
Abiotic degradation
Atomic data
3115ag
Acrolein
Corrélation électronique
3315Fm
Biodegradation
Approximation GW
Configuration interaction
Azide Anion
Atoms
AROMATIC-MOLECULES
Basis set requirements
3115vn
Analytic gradient
Xenon
Excited states
Parallel speedup
Relativistic corrections
3115bw
QSAR
Green's function
Perturbation theory
Argon
Configuration interactions
Atom
Quantum chemistry
Electron electric dipole moment
CP violation
3115ae
Time-dependent density-functional theory
Large systems
États excités
Quantum Chemistry
ALGORITHM
Atomic charges
Ion
3115aj
Polarizabilities
Hyperfine structure
Atrazine
Molecular descriptors
Valence bond
Ab initio calculation
Aimantation
A priori Localization
Single-core optimization
Coupled cluster calculations
Mécanique quantique relativiste