Overcoming the minimum image constraint using the closest point search

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Abstract

Finding the set of nearest images of a point in a simulation cell with periodic (torus) boundary conditions is of central importance for molecular dynamics algorithms. To compute all pairwise distances closer than a given cutoff in linear time requires region-based neighbor-listing algorithms. Available algorithms encounter increasing difficulties when the cutoff distance exceeds half the shortest cell length. This work provides details on two ways to directly and efficiently generate region–region interaction lists in n-dimensional space, free from the minimum image restriction. The solution is based on a refined version of existing algorithms solving the closest vector problem. A self-contained discussion of lattice reduction methods for efficient higher-dimensional searches is also provided. In the MD setting, these reduction criteria provide useful guidelines for lattice compaction.

Original languageEnglish
Pages (from-to)197-205
Number of pages9
JournalJournal of Molecular Graphics and Modelling
Volume68
DOIs
StatePublished - Jul 1 2016
Externally publishedYes

Funding

This work was supported by the USF Research Foundation and NSF MRI CHE-1531590 . We thank Joshua Vermaas and Olaf Lenz for help implementing this method within VMD.

FundersFunder number
USF Research Foundation
National Science Foundation1531590, MRI CHE-1531590

    Keywords

    • Finite size effects
    • Lattice summation
    • Molecular dynamics
    • Neighbor list

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