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  3. Geometry Optimization For Nonlocal Excited State Using The Divide-and-conquer Method.
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  3. Geometry Optimization For Nonlocal Excited State Using The Divide-and-conquer Method.

Related Experiment Video

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

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Published on: April 8, 2020

Geometry Optimization for Nonlocal Excited State Using the Divide-and-Conquer Method.

Ryusei Nishimura1, Takeshi Yoshikawa2,3, Ken Sakata2

  • 1Department of Chemistry and Biochemistry, School of Advanced Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku, Tokyo 169-8555, Japan.

Journal of Chemical Theory and Computation
|May 12, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

We developed a faster analytic gradient method for excited-state calculations. This divide-and-conquer approach enables efficient geometry optimization of large molecules with delocalized excitations.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Theoretical Chemistry

Background:

  • Excited-state calculations are crucial for understanding molecular properties and reactions.
  • Geometry optimization of large molecular systems with delocalized or charge-transfer excitations is computationally demanding.
  • Existing methods like time-dependent Hartree-Fock/density functional theory face scalability challenges.

Purpose of the Study:

  • To develop an efficient and scalable analytic gradient method for excited-state geometry optimization.
  • To enable the study of large molecular systems with complex electronic excitations.
  • To reduce the computational cost associated with excited-state calculations.

Main Methods:

  • Implementation of a divide-and-conquer (DC) based analytic gradient method.
  • Extraction of transition density matrices from response densities near polarizability poles.
  • Independent solution of subsystem Z-vector equations for computational efficiency.

    • Main Results:

    • Reduced computational scaling from O(N^3.55) to O(N^1.60) for excited-state calculations.
    • Accurate reproduction of excited-state structural relaxation in push-pull polyenes and [9]cycloparaphenylene ([9]CPP).
    • Demonstrated convergence of DC-based gradients with increasing buffer size.

    Conclusions:

    • The developed DC-based analytic gradient method is a practical and scalable approach for excited-state geometry optimization.
    • The method accurately captures structural relaxations, including quinoid distortion and large Stokes shifts.
    • This technique extends the feasibility of excited-state calculations to systems previously beyond conventional methods.