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A universal preconditioner for simulating condensed phase materials.

David Packwood1, James Kermode2, Letif Mones1

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A new sparse preconditioner speeds up atomic-scale material simulations for geometry optimization and saddle point searches. This computational efficiency gain, observed across various materials, increases with system size.

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Area of Science:

  • Materials Science
  • Computational Chemistry
  • Physics

Background:

  • Atomic-scale simulations are crucial for understanding material properties.
  • Geometry optimization and saddle point searches are common but computationally intensive tasks.
  • Existing methods may lack efficiency for large or complex systems.

Purpose of the Study:

  • To introduce a universal sparse preconditioner for accelerating atomic-scale simulations.
  • To demonstrate its effectiveness in geometry optimization and saddle point searches.
  • To provide a practical and widely applicable computational tool.

Main Methods:

  • Development of a sparse preconditioner based on the neighborhood structure of atoms.
  • Testing the preconditioner across diverse material types (metals, insulators, molecular solids).
  • Implementation within the Atomic Simulation Environment (ASE) for broad accessibility.

Main Results:

  • Significant acceleration of geometry optimization and saddle point searches.
  • Demonstrated computational efficiency gains in metals, insulators, and molecular solids.
  • Observed speedups of factor two or more, even for small systems, with gains increasing for larger systems.

Conclusions:

  • The universal sparse preconditioner offers substantial computational advantages for atomic-scale simulations.
  • Its effectiveness is independent of the underlying electronic structure model, working with both accurate and fast potentials.
  • The open-source implementation facilitates its integration into various atomistic simulation workflows.