Towards chemical accuracy using the Jastrow correlated antisymmetrized geminal power ansatz
arXiv:2211.05447 · doi:10.1021/acs.jctc.2c01141
Abstract
Herein, we report accurate atomization energy calculations for 55 molecules in the Gaussian-2 (G2) set using lattice regularized diffusion Monte Carlo (LRDMC). We compare the Jastrow-Slater determinant ansatz with a more flexible JsAGPs (Jastrow correlated antisymmetrized geminal power with singlet correlation) ansatz. AGPs is built from pairing functions, which explicitly include pairwise correlations among electrons and hence, this ansatz is expected to be more efficient in recovering the correlation energy. The AGPs wave functions are first optimized at the variational Monte Carlo (VMC) level, which includes both the Jastrow factor and the nodal surface optimization. This is followed by the LRDMC projection of the ansatz. Remarkably, for many molecules, the LRDMC atomization energies obtained using the JsAGPs ansatz reach chemical accuracy (1 kcal/mol) and for most other molecules, the atomization energies are accurate within 5 kcal/mol. We obtained a mean absolute deviation of 1.6 kcal/mol with JsAGPs and 3.2 kcal/mol with JDFT (Jastrow factor + Slater determinant with DFT orbitals) ansatz. This work shows the effectiveness of the flexible AGPs ansatz for atomization energy calculations and electronic structure simulations in general.
arXiv comment15 pages, 4 figures, JCTC accepted version after peer-review
References in corpus (26)
- Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural Networks
- Optimization of quantum Monte Carlo wave functions by energy minimization
- Green Function Monte Carlo with Stochastic Reconfiguration
- Wave function optimization in the variational Monte Carlo method
- Weak binding between two aromatic rings: feeling the van der Waals attraction by quantum Monte Carlo methods
- Geminal wavefunctions with Jastrow correlation: a first application to atoms
- Pfaffian pairing wave functions in electronic structure quantum Monte Carlo
- QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion Quantum Monte Carlo
- Variational and Diffusion Quantum Monte Carlo Calculations with the CASINO Code
- Size-consistent variational approaches to non-local pseudopotentials: standard and lattice regularized diffusion Monte Carlo methods revisited
- Multi-Determinant Wave-functions in Quantum Monte Carlo
- Diffusion Monte Carlo with lattice regularization
- Green Function Monte Carlo with Stochastic Reconfiguration: an effective remedy for the sign problem disease
- Proof for an upper bound in fixed-node Monte Carlo for lattice fermions
- Fixed-Node Diffusion Monte Carlo potential energy curve of the fluorine molecule F2 using selected configuration interaction trial wavefunctions
- Phase diagram of hydrogen and a hydrogen-helium mixture at planetary conditions by Quantum Monte Carlo simulations
- Ground state properties of the one dimensional Coulomb gas
- Approaching Chemical Accuracy with Quantum Monte Carlo
- Benchmark all-electron ab initio quantum Monte Carlo calculations for small molecules
- Toward an improved control of the fixed-node error in quantum Monte Carlo: The case of the water molecule
- TurboRVB: a many-body toolkit for {\it ab initio} electronic simulations by quantum Monte Carlo
- Almost exact energies for the Gaussian-2 set with the semistochastic heat-bath configuration interaction method
- All-electron quantum Monte Carlo with Jastrow single determinant Ansatz: application to the sodium dimer
- Reaction energetics of Hydrogen on the Si(100) surface: A periodic many-electron theory study
- Taming the fixed-node error in diffusion Monte Carlo via range separation
- Speeding up the ab initio diffusion Monte Carlo by a smart lattice regularization
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- Deep learning quantum Monte Carlo for solids
- Beyond single-reference fixed-node approximation in ab initio Diffusion Monte Carlo using antisymmetrized geminal power applied to systems with hundreds of electrons
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