基于遗传算法的最优引力波随动铺设策略
Optimal Gravitational-wave Follow-up Tiling Strategies Using a Genetic Algorithm
摘要：
由于后续观测站的视野有限，而引力波的方向定位较差，因此识别引力波源的电磁辐射通常需要多次后续观测。引力波定位区域通常被使用“蜂窝”结构的多个望远镜点覆盖，这仅在无限平坦表面上是最佳的。在这里，我们提出了一种机器学习算法，它使用遗传算法以及Broyden-Fletcher-Goldfarb-Shanno（BFGS）优化来找到一个最佳的瓦片配置，以覆盖球面上的引力波天空定位区域。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
