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Related Experiment Video

Updated: Jan 6, 2026

Spatial Separation of Molecular Conformers and Clusters
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Knowles Partitioning from a Stationary Condition: Single- and Multireference Case.

Ágnes Szabados1, András Gombás2, Péter R Surján1

  • 1Laboratory of Theoretical Chemistry, Institute of Chemistry, Faculty of Science, ELTE Eötvös Loránd University, 112, P.O.B. 32, H-1518 Budapest, Hungary.

Journal of Chemical Theory and Computation
|October 22, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces Knowles partitioning for multireference perturbation theory (PT), optimizing one-body integrals for superior performance over Møller-Plesset (MP) methods. The new approach enhances accuracy in electronic structure calculations.

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Area of Science:

  • Quantum Chemistry
  • Computational Physics
  • Theoretical Chemistry

Background:

  • Many-body perturbation theory (PT) is crucial for electronic structure calculations.
  • Existing methods like Møller-Plesset (MP) partitioning have limitations, especially for multireference (MR) systems.
  • Knowles' recent work introduced a novel partitioning scheme.

Purpose of the Study:

  • To generalize Knowles partitioning for multireference PT (MRPT) schemes.
  • To improve the performance and accuracy of MRPT calculations.
  • To address shortcomings in previous MR adaptations of PT.

Main Methods:

  • Utilizing a stationary condition on the first-order wave function in PT.
  • Optimizing one-body integrals within the first-order interacting subspace.
  • Applying the method within the frame multiconfiguration PT (fMCPT) framework, a pivot-independent variant.

Main Results:

  • The stationary condition naturally leads to Knowles partitioning.
  • The fMCPT method with Knowles partitioning shows superior performance compared to MP partitioning.
  • The resulting PT series closely approximates stationary condition-based extensions in complete active space PT (CASPT).

Conclusions:

  • Knowles partitioning offers a significant advancement for MRPT calculations.
  • This method provides a more accurate and robust alternative to traditional MP partitioning.
  • The developed approach rectifies limitations of prior MR adaptations, enhancing computational chemistry tools.