[Paper] Hub-Aware Hybrid Search: Accelerating the Locally Aligned Ant Technique
Source: arXiv - 2606.06198v1
Overview
Finding manifold structures in noisy and high-dimensional point clouds is a challenging but important problem. In astronomical observation survey and simulation data the detection of filaments, streams (1D), walls (2D) and clusters (3D) gives rise to deeper understanding of the evolution of our universe. The Locally Aligned Ant Technique (LAAT) uses biologically inspired agents to efficiently recover faint and multidimensional structures. However, very dense hubs (e.g. nodes or globular clusters) dominate the ants’ activity, creating unnecessary computational overheads. In this paper we propose a two-stage solution. First a fast preprocessing step locates the hubs and replaces them with a tailored likelihood model. Subsequently, a mixed likelihood-pheromone strategy guides the ants to efficiently bridge the dense regions. We demonstrate improvements in detection efficiency and robustness of LAAT with synthetic and a large-scale astronomical N-body simulation of the cosmic web.
Key Contributions
This paper presents research in the following areas:
- cs.NE
- astro-ph.CO
- astro-ph.GA
- astro-ph.IM
Methodology
Please refer to the full paper for detailed methodology.
Practical Implications
This research contributes to the advancement of cs.NE.
Authors
- Simone Vilardi
- Reynier Peletier
- Felipe Contreras
- Kerstin Bunte
Paper Information
- arXiv ID: 2606.06198v1
- Categories: cs.NE, astro-ph.CO, astro-ph.GA, astro-ph.IM
- Published: June 4, 2026
- PDF: Download PDF