{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-quest-database-of-highly-accurate","title":"The QUEST Database of Highly-Accurate Excitation Energies","arxiv_id":"2506.11590","date":"2025-06-13","proceeding":null,"authors":["Pierre-François Loos","Martial Boggio-Pasqua","Aymeric Blondel","Filippo Lipparini","Denis Jacquemin"],"abstract":"We report theoretical best estimates of vertical transition energies (VTEs) for a large number of excited states and molecules: the \\textsc{quest} database. This database includes 1489 \\emph{aug}-cc-pVTZ VTEs (731 singlets, 233 doublets, 461 triplets, and 64 quartets) for both valence and Rydberg transitions occurring in molecules containing from 1 to 16 non-hydrogen atoms. \\textsc{Quest} also includes a significant list of VTEs for states characterized by a partial or genuine double-excitation character, known to be particularly challenging for many computational methods. The vast majority of the reported values are deemed chemically-accurate, that is, are within $\\pm0.05$ eV of the FCI/\\emph{aug}-cc-pVTZ estimate. This allows for a balanced assessment of the performance of popular excited-state methodologies. We report the results of such benchmarks for various single- and multi-reference wavefunction approaches, and provide extensive supporting information allowing testing of other models. All corresponding data associated with the \\textsc{quest} database, along with analysis tools, can be found in the associated \\textsc{GitHub} repository at the following URL: https://github.com/pfloos/QUESTDB.","url_abs":"https://arxiv.org/abs/2506.11590v1","url_pdf":"https://arxiv.org/pdf/2506.11590v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"the-quest-database-of-highly-accurate","repo_url":"https://github.com/pfloos/questdb","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}