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Conical Intersection Optimization Based on a Double Newton-Raphson Algorithm Using Composed Steps.

Sergi Ruiz-Barragan1, Michael A Robb2, Lluís Blancafort1

  • 1Institut de Química Computacional and Department de Química, University of Girona, 17071 Girona, Spain.

Journal of Chemical Theory and Computation
|November 21, 2015
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Summary
This summary is machine-generated.

A new double Newton-Raphson step (DNR) algorithm efficiently optimizes conical intersections. This hybrid DNR-Composed Step (CS) method converges faster than previous algorithms, improving computational efficiency in quantum chemistry.

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Area of Science:

  • Quantum Chemistry
  • Computational Chemistry
  • Theoretical Chemistry

Background:

  • Conical intersections are crucial in photochemistry and spectroscopy.
  • Efficient optimization algorithms are needed to locate these critical points.
  • Existing methods like Composed Gradient (CG) have limitations.

Purpose of the Study:

  • To implement and test a Double Newton-Raphson (DNR) algorithm for conical intersection optimization.
  • To evaluate the performance of a hybrid DNR-Composed Step (CS) algorithm.
  • To compare the efficiency of DNR-CS with CG and hybrid CG-CS methods.

Main Methods:

  • The DNR algorithm uses two independent Newton-Raphson steps in redundant coordinates.
  • The first step targets energy degeneracy using the gradient difference and branching space Hessian.
  • The second step minimizes energy in the intersection space using projected excited state gradients and intersection space Hessians.

Main Results:

  • The hybrid DNR-CS algorithm was tested on 11 cases using CASSCF.
  • DNR-CS reached the Minimum Energy Conical Intersection (MECI) in 30% and 15% fewer steps than CG and hybrid CG-CS, respectively.
  • The improved efficiency is attributed to a more effective approach to the conical intersection seam.

Conclusions:

  • The DNR-CS algorithm offers a significant improvement in the efficiency of conical intersection optimization.
  • This method provides a robust approach to overcome challenges like state mixing near the seam.
  • The findings contribute to more accurate and faster calculations in photochemistry and related fields.