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Anisotropic numerical potentials for coarse-grained modeling from high-speed multidimensional lookup table and

Ananya Gangopadhyay1, Simon Winberg2, Kevin J Naidoo1

  • 1Scientific Computing Research Unit and Department of Chemistry, University of Cape Town, Cape Town, South Africa.

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|February 6, 2021
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Summary

A new high-speed numerical potential using a lookup table (LUT) offers greater physical and chemical accuracy for molecular dynamics simulations. This method significantly improves coarse-grained modeling of complex anisotropic systems compared to analytical potentials.

Keywords:
4D B-spline interpolationanisotropic coarse grain modelgraphics processing unitlookup tablemulticoremultidimensional numerical modelingnon-analytical functionsparallel computing

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Area of Science:

  • Computational chemistry
  • Materials science
  • Molecular modeling

Background:

  • Classical molecular dynamics (MD) simulations are crucial for understanding molecular behavior.
  • Existing coarse-grained (CG) analytical potentials often sacrifice physical and chemical accuracy for speed.
  • Anisotropic systems present unique challenges for accurate MD simulations.

Purpose of the Study:

  • To develop a high-speed numerical potential for enhanced accuracy in CG MD simulations.
  • To leverage graphics processing units (GPUs) for computational efficiency.
  • To improve the modeling of anisotropic systems.

Main Methods:

  • Development of a high-speed lookup table (LUT) for four-dimensional gridded data.
  • Utilized cubic B-spline interpolations for deriving off-grid values and partial derivatives.
  • Implemented GPU acceleration to achieve computational speeds competitive with analytical potentials.
  • Compared minimizations of 500 naphthalene molecules using atomistic, biaxial Gay-Berne (GB), and the developed numerical potential.

Main Results:

  • The numerical potential achieved interpolation accuracy within 3% for the potential and 5% for its derivatives compared to the uniaxial GB potential.
  • The numerical potential demonstrated significantly higher accuracy in approximating atomistic local minimum configurations than the biaxial GB potential.
  • The developed LUT-based numerical potential offers computational performance comparable to complex coarse-grained analytical potentials.

Conclusions:

  • A high-speed numerical potential based on a LUT of atomistic data significantly enhances CG modeling accuracy for complex molecules.
  • This approach shows promise for accurate CG modeling of anisotropic systems.
  • The integration of GPU functionality makes the numerical potential computationally efficient and accurate.