Detail

Foundry - Approaching QMC quality energetics throughout chemical space using scalable quantum machine learning

Huang, Bing; von Lilienfeld, O.; Krogel, Jaron T; Benali, Anouar

Organizations

Foundry

Year

2022

Source Name

foundry_qmc_ml

DOI

10.18126/wg30-95z0 View on Datacite
This dataset contains summary inputs and outputs generated for the Paper "Approaching QMC quality energetics throughout chemical space using scalable quantum machine learning" By B. Huang, O. Anatole von Lilienfeld, J. T. Krogel and A. Benali. Included in the dataset are energies for 1175 molecules calculated with varying methods, associated error calculations, and molecular structures in XYZ and pymatgen Molecule formats. Raw data for these calculations are available at https://doi.org/10.18126/hxlp-v732