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We developed open-source tools for fast multipole method (FMM) in polarizable embedding (PE) models, enabling efficient simulations of large molecular environments for computational spectroscopy. These tools enhance accuracy and usability for diverse biomolecular systems.

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Area of Science:

  • Computational Chemistry
  • Spectroscopy
  • Quantum Chemistry

Background:

  • Accurate simulation of molecular properties requires modeling complex environments.
  • Polarizable embedding (PE) models capture environmental effects but can be computationally expensive for large systems.
  • Fast multipole method (FMM) offers a potential solution for scaling these calculations.

Purpose of the Study:

  • To present open-source implementations of linear-scaling FMM within the PE model.
  • To demonstrate the efficiency and accuracy of FMM-accelerated PE calculations for computational spectroscopy.
  • To make these advanced simulation capabilities accessible to a broader scientific community.

Main Methods:

  • Developed open-source linear-scaling FMM algorithms integrated into the PE model.
  • Tested implementations on model and biomolecular systems to assess accuracy, efficiency, and usability.
  • Investigated the impact of FMM parameters on molecular property calculations.
  • Interfaced implementations with established open-source quantum chemistry programs.

Main Results:

  • Validated the accuracy and efficiency of FMM-PE for molecular property calculations.
  • Demonstrated "black-box" usability of FMM-PE for computational spectroscopy.
  • Showcased linear-scaling performance by simulating a UV/vis spectrum in an environment exceeding 1 million polarizable sites.
  • Ensured broad accessibility through integration with multiple quantum chemistry packages.

Conclusions:

  • Open-source linear-scaling FMM within PE provides an efficient and accurate method for large-scale computational spectroscopy.
  • The developed tools significantly reduce the computational cost of simulating polarizable environments.
  • These implementations democratize access to advanced computational spectroscopy techniques for diverse research applications.