Supernova search with active learning in ZTF DR3

Abstract

Context. We provide the first results from the complete SNAD adaptive learning pipeline in the context of a broad scope of data from large-scale astronomical surveys. Aims. The main goal of this work is to explore the potential of adaptive learning techniques in application to big data sets. Methods. Our SNAD team used Active Anomaly Discovery (AAD) as a tool to search for new supernova (SN) candidates in the photometric data from the first 9.4 months of the Zwicky Transient Facility (ZTF) survey, namely, between March 17 and December 31 2018 (58194 ≤ MJD ≤ 58483). We analysed 70 ZTF fields at a high galactic latitude and visually inspected 2100 outliers. Results. This resulted in 104 SN-like objects being found, 57 of which were reported to the Transient Name Server for the first time and with 47 having previously been mentioned in other catalogues, either as SNe with known types or as SN candidates. We visually inspected the multi-colour light curves of the non-catalogued transients and performed fittings with different supernova models to assign it to a probable photometric class: Ia, Ib/c, IIP, IIL, or IIn. Moreover, we also identified unreported slow-evolving transients that are good superluminous SN candidates, along with a few other non-catalogued objects, such as red dwarf flares and active galactic nuclei. Conclusions. Beyond confirming the effectiveness of human-machine integration underlying the AAD strategy, our results shed light on potential leaks in currently available pipelines. These findings can help avoid similar losses in future large-scale astronomical surveys. Furthermore, the algorithm enables direct searches of any type of data and based on any definition of an anomaly set by the expert.

The SNAD Viewer: Everything You Want to Know about Your Favorite ZTF Object

“…For example, most of the ZTF Bright Transient Survey supernovae (Fremling et al 2020;Perley et al 2020) are missing from the DRs. However, some robust SN candidates not presented in the alert stream were found in ZTF DRs by the SNAD team in Aleo et al (2022), Pruzhinskaya et al (2022). Moreover, the DR light curves have better limiting magnitudes and may also include observations that do not pass the difference imaging pipeline detection threshold (see Section 3.4.2 and Figure 4).…”

“…It is difficult to overstate the importance of ZTF DR for timedomain astronomy. It has already motivated searches and studies of AGNs (e.g., Sánchez-Sáez et al 2021), strongly lensed QSOs (e.g., Stern et al 2021), microlensing (e.g., Rodriguez et al 2022), variable stars (e.g., Chen et al 2020;Kupfer et al 2021), young stellar objects (e.g., Kuhn et al 2021), eclipsing binary systems (e.g., Kosakowski et al 2022) and, unexpectedly, supernova-like transients (Pruzhinskaya et al 2022). Moreover, their volume and complexity, combined with their timely existence as a precursor to LSST, makes ZTF DR a unique ground for preparing data mining and machine learning techniques (Malanchev et al 2021;Aleo et al 2022) which will be of paramount importance for the next generation of telescopes and surveys.…”

“…This allows visualization of a homogeneous cadence and overall survey properties presented in ZTF observations. The SNAD team used this functionality in Malanchev et al (2021), Pruzhinskaya et al (2022), andAleo et al (2022).…”

“…Currently, the KDB contains more than 50 tags which can be split into the following categories: types and sub-types of variability such as "Eclipsing," "EA," "EB," and "EW;" 44 image and photometric pipeline artifacts like "artifact" and "defocusing;" properties of classification such as "uncertain" and "non-cataloged" which are only meaningful when combined with other tags; and cross-team communication tags like "TNS_candidate," which states the object is worth submitting to TNS. A detailed description of the currently available tags was reported by Pruzhinskaya et al (2022).…”

“…So far, the Viewer enabled all the ZTF-based results reported by the SNAD team (Malanchev et al 2021;Aleo et al 2022;Pruzhinskaya et al 2022), whose summary can be found in the SNAD catalog, 19 currently hosting 144 candidate transients found by the SNAD team on ZTF DRs, while being absent from systematic searches from other groups.…”