Beyond single-reference fixed-node approximation in ab initio Diffusion Monte Carlo using antisymmetrized geminal power applied to systems with hundreds of electrons
arXiv:2402.01458 · doi:10.1021/acs.jctc.4c00139
Abstract
Diffusion Monte Carlo (DMC) is an exact technique to project out the ground state (GS) of a Hamiltonian. Since the GS is always bosonic, in fermionic systems the projection needs to be carried out while imposing anti-symmetric constraints, which is a nondeterministic polynomial hard problem. In practice, therefore, the application of DMC on electronic structure problems is made by employing the fixed-node (FN) approximation, consisting of performing DMC with the constraint of having a fixed predefined nodal surface. How do we get the nodal surface? The typical approach, applied in systems having up to hundreds, or even thousands of electrons, is to obtain the nodal surface from a preliminary mean-field approach (typically, a density functional theory calculation) used to obtain a single Slater determinant. This is known as {\emph{single reference}}. In this paper, we propose a new approach, applicable to systems as large as the C fullerene, which improves the nodes by going beyond the single reference. In practice, we employ an implicitly multireference ansatz (Antisymmetrized Geminal power wavefunction constraint with molecular orbitals), initialized on the preliminary mean-field approach, which is relaxed by optimizing a few parameters of the wave function determining the nodal surface by minimizing the FN-DMC energy. We highlight the improvements of the proposed approach over the standard single reference method on several examples and, where feasible, the computational gain over the standard multireference ansatz, which makes the methods applicable to large systems. We also show that physical properties relying on relative energies, such as binding energies, are affordable and reliable within the proposed scheme.
References in corpus (62)
- Solving the Quantum Many-Body Problem with Artificial Neural Networks
- Computational complexity and fundamental limitations to fermionic quantum Monte Carlo simulations
- Recent developments in the PySCF program package
- Deep neural network solution of the electronic Schrödinger equation
- Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural Networks
- Restricted-Boltzmann-Machine Learning for Solving Strongly Correlated Quantum Systems
- Optimization of quantum Monte Carlo wave functions by energy minimization
- Fermionic neural-network states for ab-initio electronic structure
- Inhomogeneous backflow transformations in quantum Monte Carlo calculations
- Weak binding between two aromatic rings: feeling the van der Waals attraction by quantum Monte Carlo methods
- Beyond the locality approximation in the standard diffusion Monte Carlo method
- Correlated geminal wave function for molecules: an efficient resonating valence bond approach
- Full optimization of Jastrow-Slater wave functions with application to the first-row atoms and homonuclear diatomic molecules
- Geminal wavefunctions with Jastrow correlation: a first application to atoms
- Constructing exact representations of quantum many-body systems with deep neural networks
- Interactions between Large Molecules: Puzzle for Reference Quantum-Mechanical Methods
- Pfaffian pairing wave functions in electronic structure quantum Monte Carlo
- On the physisorption of water on graphene: Sub-chemical accuracy from many-body electronic structure methods
- Size-consistent variational approaches to non-local pseudopotentials: standard and lattice regularized diffusion Monte Carlo methods revisited
- Dirac-type nodal spin liquid revealed by refined quantum many-body solver using neural-network wave function, correlation ratio, and level spectroscopy
- Multi-Determinant Wave-functions in Quantum Monte Carlo
- A New Generation of Effective Core Potentials for Correlated Calculations
- Diffusion Monte Carlo with lattice regularization
- Pfaffian pairing and backflow wave functions for electronic structure quantum Monte Carlo methods
- Fixed-Node Diffusion Monte Carlo potential energy curve of the fluorine molecule F2 using selected configuration interaction trial wavefunctions
- Fast and accurate quantum Monte Carlo for molecular crystals
- An exactly size consistent geminal power via Jastrow factor networks in a local one particle basis
- Resonating valence bond wave function with molecular orbitals: Application to first-row molecules
- Transformer variational wave functions for frustrated quantum spin systems
- Approaching Chemical Accuracy with Quantum Monte Carlo
- Boosting the accuracy and speed of quantum Monte Carlo: size-consistency and time-step
- Computing the energy of a water molecule using MultiDeterminants: A simple, efficient algorithm
- Toward an improved control of the fixed-node error in quantum Monte Carlo: The case of the water molecule
- Quantum Monte Carlo study of the first-row atoms and ions
- TurboRVB: a many-body toolkit for {\it ab initio} electronic simulations by quantum Monte Carlo
- Properties of the water to boron nitride interaction: from zero to two dimensions with benchmark accuracy
- Towards the ground state of molecules via diffusion Monte Carlo on neural networks
- Static and dynamical correlation in diradical molecules by Quantum Monte Carlo using the Jastrow Antisymmetrized Geminal Power ansatz
- Almost exact energies for the Gaussian-2 set with the semistochastic heat-bath configuration interaction method
- Simple formalism for efficient derivatives and multi-determinant expansions in quantum Monte Carlo
- Perturbatively selected configuration-interaction wave functions for efficient geometry optimization in quantum Monte Carlo
- Quantum Monte Carlo with Jastrow-valence-bond wave functions
- Correlation-Driven Dimerization and Topological Gap Opening in Isotropically Strained Graphene
- A new scheme for fixed node diffusion quantum Monte Carlo with pseudopotentials: improving reproducibility and reducing the trial-wave-function bias
- Quantum Monte Carlo study of the Ne atom and the Ne+ ion
- Quantum Monte Carlo with very large multideterminant wavefunctions
- The fate of the resonating valence bond in graphene
- Accurate atomic correlation and total energies for correlation consistent effective core potentials
- Self-healing diffusion quantum Monte Carlo algorithms: methods for direct reduction of the fermion sign error in electronic structure calculations
- Systematic reduction of sign errors in many-body calculations of atoms and molecules
- TREXIO: A File Format and Library for Quantum Chemistry
- Systematic Comparison and Cross-validation of Fixed-Node Diffusion Monte Carlo and Phaseless Auxiliary-Field Quantum Monte Carlo in Solids
- Assessing the Accuracy of the Jastrow Antisymmetrized Geminal Power in the H4 Model System
- All-electron quantum Monte Carlo with Jastrow single determinant Ansatz: application to the sodium dimer
- 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
- Improper s-wave symmetry for the electronic pairing in iron-based superconductors by first-principles calculation
- TurboGenius: Python suite for high-throughput calculations of ab initio quantum Monte Carlo methods
- Towards chemical accuracy using the Jastrow correlated antisymmetrized geminal power ansatz
- Systematic reduction of sign errors in many-body problems: generalization of self-healing diffusion Monte Carlo to excited states
- Gradient Descent Optimization of Fermion Nodes in Diffusion Monte Carlo
- Generalizing the self-healing diffusion Monte Carlo approach to finite temperature: a path for the optimization of low-energy many-body bases