🚀 QUESTDB: A Database of Highly-Accurate Excitation Energies

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📚 Table of Contents

• ✨ Key Features
• 🧪 Why Use QUESTDB?
• 📂 Repository Contents
• ⚡ Charged Excitations (charged/)
  • valence_IPs
  • DIPs
  • core_IPs
• 👥 Contributors
• 📚 Main References
• 📖 Other References
• 🔋 Extension to Charged Excitations
• 🗂️ Data Structure
• 💰 Funding
• 🧮 HPC resources

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✨ Key Features

• 🔬 High Accuracy:
  Data obtained using state-of-the-art methods (FCI, CC3, CCSDT, CCSDTQ, CC4, CASPT2/3, NEVPT2, etc.)

• 🌍 Wide Chemical Coverage:
  Includes small molecules, radicals, charged species, and transition metal complexes.

• 🎯 Challenging Excitations:
  Focus on double excitations and intramolecular charge-transfer (CT) states.

• 🛠️ Continuously Updated:
  Regularly improved with new high-level calculations and critical assessments.

• 📂 Easy-to-Use Format:
  Organized .xlsx spreadsheets and .json files for simple extraction and analysis.

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🧪 Why Use QUESTDB?

QUESTDB supports researchers to:

• Benchmark TD-DFT, wavefunction-based, and emerging excited-state methods.
• Guide the development of new computational models.
• Facilitate interpretation of experimental spectra and photochemistry.

Note: Our vision is to establish QUESTDB as a cornerstone resource for benchmarking and training the next generation of AI-driven models in excited-state science.

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⚙️ Scripts for Subset Generation and Analysis

This repository includes Python scripts to help users generate representative "diet" subsets of QUEST excitation energies—for instance, sets of 50, 100, or 200 transitions that reproduce the s[...]

These tools are especially useful for benchmarking new methods quickly or for training machine learning models when computational cost is a limiting factor.

Main functionalities include:

• ✅ Generation of optimized subsets matching the full dataset’s distribution across:
  • Spin states
  • Valence vs Rydberg states
  • Excitation types (e.g., nπ*, ππ*, etc.)
  • Molecule sizes or other custom filters
• ✅ Support for flexible user-defined filters (e.g., only valence, only singlets, exclude genuine doubles)
• ✅ Preservation of full metadata in output JSON files
• ✅ Optional optimization of subset selection using a genetic algorithm with Bayesian hyperparameter tuning (via optuna)

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📂 Repository Contents

This repository provides:

• Molecular Structures
• Vertical Excitation Energies
• Oscillator Strengths
• Many Other Properties
• Charged Excitations: High-quality datasets for ionization potentials (IPs), valence double ionization potentials (DIPs), and core ionization potentials — see the charged/ directory for details and per-molecule JSON files (charged/README.md).

📌 See the accompanying paper:
The QUEST database of highly-accurate excitation energies
P.-F. Loos, M. Boggio-Pasqua, A. Blondel, F. Lipparini, and D. Jacquemin,
J. Chem. Theory Comput. 21, 8010 (2025). DOI:10.1021/acs.jctc.5c00975

© Béatrice Lejeune (@bea_quarelle)

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👥 Contributors

The QUESTDB project is maintained by a collaboration between:

• Denis Jacquemin (Nantes)
• Pierre-François Loos (Toulouse)
• Martial Boggio-Pasqua (Toulouse)
• Fábris Kossoski (Toulouse)
• Filippo Lipparini (Pisa)
• Anthony Scemama (Toulouse)
• Aymeric Blondel ( Nantes)
• Mickael Véril (Toulouse)
• Yann Damour (Toulouse)
• Antoine Marie (Toulouse)

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📚 Main References

Review articles on the QUEST database:

• The QUEST database of highly-accurate excitation energies
  P.-F. Loos, M. Boggio-Pasqua, A. Blondel, F. Lipparini, and D. Jacquemin,
  J. Chem. Theory Comput. 21, 8010 (2025).

• QUESTDB: a database of highly-accurate excitation energies for the electronic structure community
  M. Véril, A. Scemama, M. Caffarel, F. Lipparini, M. Boggio-Pasqua, D. Jacquemin, and P.-F. Loos,
  WIREs Comput. Mol. Sci. 11, e1517 (2021).

• The quest for highly accurate excitation energies: a computational perspective
  P.-F. Loos, A. Scemama, and D. Jacquemin,
  J. Phys. Chem. Lett. 11, 2374 (2020).

• Reference energies for double excitations: improvement & extension
  F. Kossoski, M. Boggio-Pasqua, P.-F. Loos, and D. Jacquemin,
  J. Chem. Theory Comput. 20, 5655 (2024).

• Reference vertical excitation energies for transition metal compounds
  D. Jacquemin, F. Kossoski, F. Gam, M. Boggio-Pasqua, and P.-F. Loos,
  J. Chem. Theory Comput. 19, 8782 (2023).

• A mountaineering strategy to excited states: revising reference values with EOM-CC4
  P.-F. Loos, F. Lipparini, D. A. Matthews, A. Blondel, and D. Jacquemin,
  J. Chem. Theory Comput. 18, 4418 (2022.

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📖 Other References

• Excited-state absorption: Reference oscillator strengths, wavefunction and TD-DFT benchmarks
  J. Širůček, B. Le Guennic, Y. Damour, P.-F. Loos, and D. Jacquemin,
  J. Chem. Theory Comput. 21, 4688 (2025).

• Reference CC3 excitation energies for organic chromophores: benchmarking TD-DFT, BSE/GW and wave function methods
  I. Knysh, F. Lipparini, I. Duchemin, X. Blase, P.-F. Loos, and D. Jacquemin,
  J. Chem. Theory Comput. 20, 8152 (2024).

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🔋 Extension to Charged Excitations

The QUEST database also contains charged excitations, mainly ionization potentials (IPs) at the moment. Here is the short description of the charged excited states included in QUEST (see the charged directory):

• Inner- and Outer-Valence IPs and Satellite Transitions:
  Reference energies for valence ionizations and satellite transitions
  A. Marie and P.-F. Loos,
  J. Chem. Theory Comput. 20, 4751 (2024).

• Valence Double IPs (DIPs) and Double Core Holes (DCHs):
  Anomalous propagators and the particle-particle channel: Bethe-Salpeter equation
  A. Marie, P. Romaniello, X. Blase, and P.-F. Loos,
  J. Chem. Phys. 162, 134105 (2025).

• Core IPs:
  Reference energies for non-relativistic core ionization potentials
  A. Marie, L. Burth, and P.-F. Loos,
  J. Chem. Theory Comput. (submitted) arXiv:2604.05920.

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🗂️ Data Structure

• Molecular Structures:
  .xyz or .TeX formats

• Excitation Energies, Oscillator Strengths and Other Properties:
  .xls spreadsheets and .json files

• Scripts to Convert and Analyze Data
  .py scripts to convert data from one format to another and analyze them.

• Additional Metadata:
  (Planned for future releases)

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💰 Funding

This database is supported by the PTEROSOR project, funded by the European Research Council (ERC) under the EU Horizon 2020 research and innovation prog[...]

This database is also funded, in part, by the Agence Nationale de la Recherche (ANR), grant ANR-25-CE29-4996.

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🧮 HPC resources

This work was performed using HPC resources from CALMIP (Toulouse, France) under allocations 2018-18005 through 2026-18005, as well as resources provided[...]