The identification of electromagnetic emission from gravitational-wave sources typically requires multiple follow-up observations due to the limited fields-of-view of follow-up observatories compared to the poorly localized direction of gravitational waves. Gravitational-wave localization regions are typically covered with multiple telescope pointings using a "honeycomb" structure, which is optimal only on an infinite, flat surface. Here we present a machine-learning algorithm which uses genetic algorithms along with Broyden-Fletcher-Goldfarb-Shanno (BFGS) optimization to find an optimal configuration of tiles to cover the gravitational-wave sky localization area on a spherical surface.
@article{arxiv.2003.04839,
title = {Optimal Gravitational-wave Follow-up Tiling Strategies Using a Genetic Algorithm},
author = {Nihar Gupte and Imre Bartos},
journal= {arXiv preprint arXiv:2003.04839},
year = {2020}
}