Building upon Fast Multipole Methods to Detect and Model Organizations

TL;DR

This paper introduces a novel method based on Fast Multipole Methods to detect and model dense organizational structures in systems of interacting entities, enhancing analysis in natural and social sciences.

Contribution

The paper presents an extension of Fast Multipole Methods specifically designed for identifying and modeling dense structures within complex systems.

Findings

Effective detection of dense structures demonstrated

Improved modeling accuracy over existing methods

Potential applications in various scientific domains

Abstract

Many models in natural and social sciences are comprised of sets of inter-acting entities whose intensity of interaction decreases with distance. This often leads to structures of interest in these models composed of dense packs of entities. Fast Multipole Methods are a family of methods developed to help with the calculation of a number of computable models such as described above. We propose a method that builds upon FMM to detect and model the dense structures of these systems.