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This study optimized time-dependent density-functional tight-binding (TDDFTB) calculations using a divide-and-conquer (DC) method on a graphical processing unit (GPU). The GPU-accelerated DC-TDDFTB code enhances computational efficiency and accuracy for molecular simulations.

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divide-and-conquer methodexcited-state theorygraphical processor unitlinear scalingtime-dependent density-functional tight-binding method

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Area of Science:

  • Computational chemistry
  • Quantum chemistry
  • Materials science

Background:

  • Time-dependent density-functional tight-binding (TDDFTB) is a method for calculating electronic excited states.
  • Large-scale TDDFTB calculations are computationally demanding.
  • Graphical Processing Units (GPUs) offer significant computational acceleration for scientific applications.

Purpose of the Study:

  • To implement and evaluate a divide-and-conquer TDDFTB (DC-TDDFTB) code on a GPU.
  • To assess the computational efficiency and accuracy of the GPU-accelerated DC-TDDFTB method.
  • To simulate excited-state intramolecular proton transfer in 2-acetylindan-1,3-dione.

Main Methods:

  • Implementation of a linear-scaling divide-and-conquer (DC) scheme for TDDFTB.
  • Parallelization of the DC-TDDFTB code for execution on a GPU.
  • Numerical validation of the GPU-accelerated code using benchmark calculations.
  • Simulation of excited-state intramolecular proton transfer in 2-acetylindan-1,3-dione.

Main Results:

  • The GPU-accelerated DC-TDDFTB code significantly reduces computational cost and memory requirements.
  • The method maintains the accuracy of standard TDDFTB calculations.
  • Simulations accurately reproduced experimental absorption and fluorescence energies for 2-acetylindan-1,3-dione.
  • The study demonstrated excited-state intramolecular proton transfer in the simulated molecule.

Conclusions:

  • The DC-TDDFTB approach on a GPU is an efficient and accurate method for large-scale electronic structure calculations.
  • This computational strategy accelerates molecular simulations, enabling the study of complex systems.
  • The developed code provides a valuable tool for investigating excited-state dynamics and photophysical properties.