Code Examples – Grier Jones

Analyzing the aptitude of the UpCCGSD, UpCCD, UCCSD, SPA+GS, and LUCJ ansätze for distribution using circuit cutting
- Code: https://github.com/MSRG/Distributed_Electronic_Structure
- Publication: G. M. Jones^*#, H.-A. Jacobsen, Analyzing Common Electronic Structure Theory Algorithms for Distributed Quantum Computing, submitted.
Data-Driven Complete Active Space Second-Order Perturbation Theory (DDCASPT2)
- Code: Links to the version of OpenMolcas used to perform calculations in this paper can be found in the GitHub repository: https://github.com/ChemRacer/Test. The code base containing the DDCASPT2 code and ML models can be found in the following GitHub repository: https://github.com/ChemRacer/DDCASPT2.
- Publication: G. M. Jones^*, K. D. Vogiatzis, Capturing Electron Correlation with Machine Learning through a Data-Driven CASPT2 Framework , submitted.
qregress
- Code: https://github.com/MSRG/qregress
- Publication: G. M. Jones^*#, V. K. Prasad, U. Fekl, H.-A. Jacobsen, Parametrized Quantum Circuit Learning for Quantum Chemical Applications, submitted.
CO₂-Dipeptide Interaction
- Code: https://github.com/ChemRacer/dipeptide_co2
- Publication: A. G. Sylvanus, G. M. Jones, R. Custelcean, K. D. Vogiatzis, In Silico Screening of CO₂-Dipeptide Interactions for Bioinspired Carbon Capture, ChemPhysChem, 2024, e202400498.
Data-Driven Variational Two-Electron Reduced-Density-Matrix (DDv2RDM)
- Code: https://github.com/ChemRacer/DDv2RDM
- Publication: G. M. Jones, R. R. Li, A. E. DePrince III, K. D. Vogiatzis, Data-Driven Refinement of Electronic Energies from Two-Electron Reduced-Density-Matrix Theory, J. Phys. Chem. Lett., 2023, 14, 28, 6377-6385. (Preprint)
Molecular Representations for Machine Learning
- Code: https://github.com/ChemRacer/molecular_representation_examples
- Publication: G. M. Jones, B. Story, V. Maroulas, K. D. Vogiatzis, Molecular Representations for Machine Learning, ACS In Focus; American Chemical Society: Washington DC, 2023.
Fe(IV)-oxo C-H Activation
- Code: https://gitlab.com/ChemRacer/feoml_data
- Publication: G. M. Jones, B. A. Smith, J. K. Kirkland, K. D. Vogiatzis, Data-Driven Ligand Field Exploration of Fe(IV)-oxo Sites for C-H Activation, Inorg. Chem. Front., 2023, 10, 1062-1075.
Data-Driven Complete Active Space Second-Order Perturbation Theory (DDCASPT2)
- Demo: DATA-DRIVEN QUANTUM CHEMISTRY CASE STUDIES
- Code: https://github.com/ChemRacer/DDQC_Demo
- Publication: G. M. Jones, P. D. V. S. Pathirage, K. D. Vogiatzis, Data-driven Acceleration of Coupled-Cluster Theory and Perturbation Theory Methods, in: “Quantum Chemistry in the Age of Machine Learning”, 2022, Editor: Pavlo Dral, Elsevier, pp. 509-529.

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