5 papers
Orbital Optimization and Neural-Network-Assisted Configuration Interaction Calculations of Rydberg States
Gianluca Levi, Max Kroesbergen, Louis Thirion +5
Rydberg excited states of molecules pose a challenge for electronic structure calculations because of their highly diffuse electron distribution. Even large and elaborate atomic ba…
Natural-Orbital-Based Neural Network Configuration Interaction
Louis Thirion, Yorick L. A. Schmerwitz, Max Kroesbergen +5
Selective configuration interaction methods approximate correlated molecular ground- and excited states by considering only the most relevant Slater determinants in the expansion.…
A neural-network-based Python package for performing large-scale atomic CI using pCI and other high-performance atomic codes
Pavlo Bilous, Charles Cheung, Marianna Safronova
Modern atomic physics applications in science and technology pose ever higher demands on the precision of computations of properties of atoms and ions. Especially challenging is th…
A Neural-Network-Based Selective Configuration Interaction Approach to Molecular Electronic Structure
Yorick L. A. Schmerwitz, Louis Thirion, Gianluca Levi +4
By combining Hartree-Fock with a neural-network-supported quantum-cluster solver proposed recently in the context of solid-state lattice models, we formulate a scheme for selective…
SOLAX: A Python solver for fermionic quantum systems with neural network support
Louis Thirion, Philipp Hansmann, Pavlo Bilous
Numerical modeling of fermionic many-body quantum systems presents similar challenges across various research domains, necessitating universal tools, including state-of-the-art mac…