A Comprehensive Study of Detectability and Contamination in Deep Rapid Optical Searches for Gravitational Wave Counterparts (1503.07869v1)

Abstract: The first direct detection of gravitational waves (GW) by the ground-based interferometers is expected to occur within the next few years. These interferometers will detect the mergers of compact object binaries composed of neutron stars and/or black holes to a fiducial distance of ~200 Mpc and a localization region of ~100 sq. deg. To maximize the science gains from such GW detections it is essential to identify electromagnetic (EM) counterparts. The most promising such counterpart is optical/IR emission powered by the radioactive decay of r-process elements synthesized in the neutron-rich merger ejecta - a "kilonova". Here we present detailed simulated observations that encompass a range of strategies for kilonova searches during GW follow-up. We assess both the detectability of kilonovae and our ability to distinguish them from a wide range of contaminating transients. We find that if pre-existing template images for the localization region are available, then nightly observations to a depth of i=24 mag and z=23 mag are required to achieve a 95% detection rate; observations that commence within 12 hours of trigger will also capture the kilonova peak and provide stronger constraints on the ejecta properties. We also find that kilonovae can be robustly separated from other types of transients utilizing cuts on color (i-z > 0 mag) and rise time (< 4 days). In the absence of a pre-existing template the observations must reach ~1 mag deeper to achieve the same kilonova detection rate, but robust rejection of contaminants can still be achieved. Motivated by the results of our simulations we discuss the expected performance of current and future wide-field telescopes in achieving these observational goals, and find that prior to LSST the Dark Energy Camera on the Blanco 4-m telescope and Hyper Suprime-Cam on the Subaru 8-m telescope offer the best kilonova discovery potential.