| Abstract : | We introduce an automated software algorithm designed to crossmatch LIGO skymaps with ZTF alerts through ALeRCE. ALeRCE is a leading Chilean broker that processes the alert stream from ZTF. It aspires to become a community broker for LSST and other large etendue survey telescopes. We receive alerts for gravitational wave(GW) events from LIGO via the Kafka/SCiMMA client. These alerts are used to extract GW skymaps, which are further processed by creating contour maps and performing spatial queries with the ZTF alert stream. Additionally, we leverage the existing infrastructure of ALeRCE's light curve classifier to identify potential kilonovae candidates.
We also include recent rapidly rising supernovae while excluding candidates that are in proximity to the ecliptic or the Milky Way plane, or those affected by high galactic extinction. This infrastructure encompasses classification based on image stamps and employs machine learning algorithms, among other techniques.
Subsequently, we search for possible host galaxies in catalogs such as NED, SIMBAD, and HECATE. Our algorithm has been implemented on few O4 candidates, providing statistics on concentration of transient events in relation to GW skymaps. We plan to include the algorithms in real time, to get real time alerts.
With the advent of upcoming survey telescopes like LSST and various GW observatories including Einstein, Cosmic Explorer, and LIGO India, our work will demonstrate the challenges associated with crossmatching a large volume of alert data with the generated highly accurate skymaps.
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