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Arbitrary-Order Density Functional Response Theory from Automatic Differentiation.

Ulf Ekström1, Lucas Visscher1, Radovan Bast1

  • 1Division of Theoretical Chemistry, Amsterdam Center for Multiscale Modeling, VU University - Faculty of Sciences, De Boelelaan 1083, NL-1081 HV Amsterdam, The Netherlands, and Centre for Theoretical and Computational Chemistry, Department of Chemistry, University of Tromsø, N-9037 Tromsø, Norway.

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Summary
This summary is machine-generated.

Automatic differentiation simplifies calculating derivatives in time-dependent density functional theory (TDDFT). This method efficiently generates higher-order exchange-correlation functional derivatives for advanced computational chemistry.

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Area of Science:

  • Computational chemistry
  • Quantum mechanics
  • Theoretical physics

Background:

  • Perturbative time-dependent density functional theory (TDDFT) relies on calculating functional derivatives.
  • Accurate computation of higher-order derivatives is crucial for advanced TDDFT applications.
  • Existing methods for derivative calculation can be complex and difficult to maintain.

Purpose of the Study:

  • To introduce a novel method for calculating functional derivatives in TDDFT.
  • To demonstrate the efficiency and accuracy of automatic differentiation for this task.
  • To enable the generation of arbitrary-order response functions within TDDFT.

Main Methods:

  • Implementing the exchange-correlation energy functional in a computational framework.
  • Utilizing automatic differentiation to generate arbitrary-order derivatives of the functional.
  • Combining the automatic differentiation approach with an arbitrary-order response solver.

Main Results:

  • Automatic differentiation provides an accurate and general implementation of higher-order exchange-correlation functional derivatives.
  • The developed methodology is efficient and easy to maintain.
  • Arbitrary-order response functions can be systematically generated from TDDFT.

Conclusions:

  • Automatic differentiation offers a robust solution for computing functional derivatives in TDDFT.
  • This approach enhances the capabilities of TDDFT for complex electronic structure calculations.
  • The methodology facilitates more accurate and detailed investigations of molecular properties and dynamics.