Uploaded December 2025 | Updated September 2026, 2 weeks ago
Quiqbox.jl 0.6: Basis design for electronic structure and beyond by Weishi Wang
PreTalx: pretalx.com/juliacon-2025/talk/RR3SMD
Quiqbox started as an open-source basis set generation and optimization software library for electronic structure at the intersection between quantum computing and quantum chemistry. It was designed to flexibly construct custom single-particle wave functions based on linear combinations of parameterized Gaussian-type orbitals. These parameterized basis functions are used to discretize the molecular Hamiltonians for numerical computation in electronic structure. With Quiqbox, one can study the relation between molecular Hamiltonian discretizations and classical methods or quantum algorithms in electronic structure. Our presentation's primary goal is to demonstrate new features and performance improvements of Quiqbox over the past two years, which will help further such research endeavors and related studies.
Due to the upgrades to the parameterization and construction system, Quiqbox has also become a flexible toolbox for designing computational models that may benefit a broader range of researchers. For instance, after version 0.6, Quiqbox can be used to prototype machine learning models based on artificial neural network architectures (e.g., Multilayer perceptron). We hope this talk can illuminate potential use cases of Quiqbox for both electronic structure and scientific modeling within the Julia community.
Quiqbox.jl 0.6: Basis design for electronic structure and beyond by Weishi Wang
PreTalx: pretalx.com/juliacon-2025/talk/RR3SMD
Quiqbox started as an open-source basis set generation and optimization software library for electronic structure at the intersection between quantum computing and quantum chemistry. It was designed to flexibly construct custom single-particle wave functions based on linear combinations of parameterized Gaussian-type orbitals. These parameterized basis functions are used to discretize the molecular Hamiltonians for numerical computation in electronic structure. With Quiqbox, one can study the relation between molecular Hamiltonian discretizations and classical methods or quantum algorithms in electronic structure. Our presentation's primary goal is to demonstrate new features and performance improvements of Quiqbox over the past two years, which will help further such research endeavors and related studies.
Due to the upgrades to the parameterization and construction system, Quiqbox has also become a flexible toolbox for designing computational models that may benefit a broader range of researchers. For instance, after version 0.6, Quiqbox can be used to prototype machine learning models based on artificial neural network architectures (e.g., Multilayer perceptron). We hope this talk can illuminate potential use cases of Quiqbox for both electronic structure and scientific modeling within the Julia community.
