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A parameter-free, solid-angle based, nearest-neighbor algorithm
Jacobus A van Meel1, Laura Filion, Chantal Valeriani
1FOM Institute for Atomic and Molecular Physics, Science Park 104, 1098 XG Amsterdam, The Netherlands.
The Journal of Chemical Physics
|July 12, 2012
Summary
We introduce a new, parameter-free algorithm for finding nearest neighbors. This solid-angle based method is computationally efficient and suitable for analyzing 3D images and real-time simulations.
Area of Science:
- Computational physics
- Materials science
- Image analysis
Background:
- Identifying nearest neighbors is crucial in many scientific fields.
- Existing algorithms often require parameter tuning or have high computational costs.
Purpose of the Study:
- To present a novel, parameter-free algorithm for nearest neighbor identification.
- To demonstrate the algorithm's advantages in terms of ease of use and computational efficiency.
Main Methods:
- The proposed algorithm, Solid-Angle Based Nearest Neighbor (SANN), assigns a solid angle to each potential neighbor.
- The cutoff radius is determined by ensuring the sum of solid angles equals 4π.
- The algorithm's performance is evaluated by comparing it to fixed-distance cutoff and Voronoi methods.
Main Results:
- SANN demonstrates effective nearest neighbor identification across various systems, including bulk phases and interfaces.
- The algorithm exhibits low computational cost, enabling its use in simulations.
- SANN offers advantages over existing methods in terms of parameter independence and ease of application.
Conclusions:
- The solid-angle based nearest-neighbor algorithm (SANN) provides a robust and efficient parameter-free approach for neighbor identification.
- SANN is versatile, applicable to 3D image analysis and real-time simulations.
- This method offers a valuable alternative to traditional nearest neighbor search techniques.
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