An Algorithm to Optimize the Search for Electromagnetic Counterparts to Gravitational Wave Events

Our understanding of gravitational wave (GW) events is greatly enhanced by identifying and studying their electromagnetic (EM) counterparts. For nearby GW events with a small localization uncertainty, an effective strategy is to search for new transient sources in previously catalogued galaxies, whose properties are consistent with the GW data. Even with a limited field of view, it is plausible to discover the EM counterparts using an efficient observational strategy. But because many galaxies must be observed and the EM counterparts are faint and fade rapidly, a reliable automatic procedure is crucial to schedule observations efficiently. To meet these challenges, we designed an algorithm in Python that uses a catalogue of nearby galaxies and the three-dimensional GW localization map to create a prioritized list of galaxies based on GW error-map probability, observability, and absolute magnitude. We tested our algorithm with past GW events and, within a few minutes, obtained consistent results with previous observations. We conclude highlighting how this algorithm can more generally assist in formulating effective followup plans with various types of small field telescopes at a variety of wavelengths, including radio.