The Effect of Vera C. Rubin Observatory Cadence Selections on Kilonova Detectability

TL;DR

This paper investigates how different observing strategies of the Vera C. Rubin Observatory can be optimized to improve the detection of kilonovae, which are fast-fading astronomical events associated with neutron star mergers.

Contribution

It introduces a fast transient detection metric to evaluate and optimize LSST survey cadences for kilonova discovery, building on methods successful with other surveys.

Findings

Baseline cadences increase detection likelihood.

Triplet observation strategies like presto gap are effective.

Filter selection and visit return times significantly impact detection rates.

Abstract

The discovery of the optical/infra-red counterpart (AT2017gfo) to the binary neutron star gravitational-wave detection (GW170817), which was followed by a short gamma-ray burst (GRB170817), marked a groundbreaking moment in multi-messenger astronomy. To date, it remains the only confirmed joint detection of its kind. However, many experiments are actively searching for similar fast-fading electromagnetic counterparts, known as kilonovae. Fortunately, the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) provides excellent prospects for identifying kilonova candidates either from, or independent of, gravitational-wave and gamma-ray burst triggers. Cadence choices for LSST surveys are especially important for maximising the likelihood of kilonovae detections. In this work, we explore the possibility of optimizing Rubin Observatory's ability to detect kilonovae by implementing a fast transient metric shown to be successful with an existing wide field survey, e.g. the Zwicky Transient Facility (ZTF). We study existing LSST cadences, how detection rates are affected by filter selections, the return timescales for visits of the same area in the sky, and other relevant factors. Through our analysis, we have found that employing baseline cadences and utilizing triplet families like presto gap produced the highest likelihood of kilonova detection.