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The QUEST Database of Highly-Accurate Excitation Energies

Published 13 Jun 2025 in physics.chem-ph, cond-mat.mtrl-sci, cond-mat.str-el, nucl-th, and physics.comp-ph | (2506.11590v1)

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.

Summary

  • The paper presents a comprehensive QUEST database containing 1489 vertical transition energies with chemical accuracy (±0.05 eV) for diverse excited states.
  • It employs advanced coupled-cluster, selected CI, and MR perturbation methods to accurately capture both valence and Rydberg transitions, including double-excitations.
  • The database provides a critical benchmark for validating and advancing computational quantum chemistry models and supports AI-driven research in excited state dynamics.

Overview of the QUEST Database of Highly-Accurate Excitation Energies

The QUEST database stands as a comprehensive repository for highly accurate vertical transition energies (VTEs) of a variety of excited states across a diverse set of molecules. The core aim of this database creation is to offer chemically accurate reference values for VTEs, enabling rigorous benchmarking of computational methods in electronic structure calculations relevant to quantum chemistry and material science.

Content and Methodology

The database encompasses 1489 VTEs, meticulously calculated with the aug-cc-pVTZ basis set. These transitions include singlets, doublets, triplets, and quartets, representing both valence and Rydberg states. Importantly, it extends to excited states with notable partial or genuine double-excitation character, posing significant challenges for standard computational methods. The vast majority of data points achieve chemical accuracy, remaining within ±0.05 eV of the Full Configuration Interaction (FCI) standard for the aug-cc-pVTZ basis set.

Each VTE is determined through high-level coupled-cluster methods, selected configuration interaction (SCI), and multireference (MR) perturbation approaches. Such theoretical rigor ensures the reliability of these values for benchmarking state-of-the-art wavefunction methodologies, including single- and multi-reference approaches.

Implications

The implications of the QUEST database are multifaceted:

  1. Benchmarking & Validation: It offers an unparalleled resource for validating new computational models and methods. The chemically accurate data serve as reliable reference points to assess the precision and efficacy of emerging theories in excited state quantum chemistry.
  2. Theoretical Insights: The database facilitates deeper theoretical insights into complex excitation phenomena, particularly those involving double-excitations and radical states, potentially contributing to the refinement of existing electronic structure methods.
  3. Tool for Development: Beyond validation, QUEST acts as a cornerstone for developing more adept computational approaches, encouraging advances in areas such as electronic excitation and transition properties prediction.

Future Prospects

Looking forward, the QUEST database could stimulate advancements in AI applications within quantum chemistry. AI models trained on such high-accuracy datasets hold promise for predictive modeling in excited state dynamics, potentially offering expedited solutions for complex molecular systems where traditional computations are impractical.

Moreover, QUEST's comprehensive scale and precision pave the way for exploration into larger molecular systems and exotic electronic states, providing a benchmark for the continuing evolution of computational chemistry methods. As the field embraces multi-configurational electronic structure theories and machine learning strategies, the database will likely serve as a critical tool in guiding the selection and evaluation of theoretical models, adding dimension to multidisciplinary research in chemistry, materials science, and beyond.

In summary, the QUEST database not only exemplifies excellence in generating highly accurate electronic transition data but also offers a robust framework to foster theoretical innovation and performance assessment in computational chemistry.

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