AstroNote 2024-140

BTSbot (Rehemtulla et al. 2024) is a convolutional neural network designed for the automated identification of bright extragalactic transients for the Zwicky Transient Facility (ZTF; Bellm et al. 2019) Bright Transient Survey (BTS; Fremling et al. 2020, Perley et al. 2020, Rehemtulla et al. 2024). Once deployed in 2023 October, it enabled BTS to fully autonomously detect, identify, follow-up, classify, and publicly report bright transients in real-time (Rehemtulla et al. 2023). Here, we introduce BTSbot-nearby, a program repurposing BTSbot for very rapid autonomous follow-up of young, nearby extragalactic transients.

BTSbot-nearby runs a ZTF alert filter similar to the BTS alert filter (Perley et al. 2020) with a few additions. The BTSbot-nearby filter (i) makes use of ZTF alert packet forced photometry to more rapidly reject asteroids; (ii) selects only alerts within 120” of a CLU (Census of the Local Universe; Cook et al. 2019) cataloged galaxy with z < 0.01 (d < 40 Mpc); and (iii) selects only alerts with BTSbot score >= 0.5. As is the case for regular BTSbot triggers, additional triggering criteria are imposed to prevent redundant triggers (see Rehemtulla et al. 2024). Once all criteria are passed, a high-priority follow-up request is immediately sent to the SED Machine (SEDM; Blagorodnova et al. 2018, Rigault et al. 2019) requesting photometry (u-, g-, r-, and i-bands) and spectroscopy.

We also report the rapid identification of two recent nearby supernovae by BTSbot-nearby: SNe 2024iss and 2024jlf.

SN 2024iss (ZTF24aankvcy) was first reported to TNS by Godson et al. 2024 using GOTO data (Steeghs et al. 2022). BTSbot-nearby identified SN 2024iss before any existing TNS AT Report using ZTF data (i.e. before the 2024-05-13 10:23:04 report by Pérez-Fournon et al. 2024). No follow-up observations were collected, however, because the BTSbot-nearby program was still in testing.

SN 2024jlf (ZTF24aaozxhx) was first reported to TNS by Hinds et al. 2024 using ZTF data at UTC 2024-05-28 10:29:59. It was discovered autonomously about two and a half hours earlier (UTC 2024-05-28 07:53:38) through BTSbot-nearby, which triggered a high-priority SEDM follow-up request. Seven minutes and 20 seconds later (UTC 2024-05-28 08:00:58), SEDM obtained an acquisition image of SN 2024jlf. SEDM then took a spectrum and additional photometry, producing a low-resolution spectrum, two r-band detections, and one u-band detection (g- and i-band photometry failed due to an unrelated instrumental issue). The spectrum shows a blue continuum and a weak H-alpha feature. We caution further interpretation of the spectrum given its low resolution. Below we report the observed SEDM photometry, reduced as described in Fremling et al. 2016 (AB system, host-subtracted but not corrected for reddening):

We will continue sending automatic SEDM triggers and issuing AstroNotes for sources discovered through the BTSbot-nearby program. 

BTSbot runs on Kowalski (Duev et al. 2019), an alert broker and data system for ZTF, and autonomously submits triggers to SEDM using Fritz, a SkyPortal instance (Coughlin et al. 2023).

This report is based on observations obtained with the Samuel Oschin Telescope 48-inch and the 60-inch Telescope at the Palomar Observatory as part of the Zwicky Transient Facility project. ZTF is supported by the National Science Foundation under Grants No. AST-1440341 and AST-2034437 and a collaboration including current partners Caltech, IPAC, the Oskar Klein Center at Stockholm University, the University of Maryland, University of California, Berkeley, the University of Wisconsin at Milwaukee, University of Warwick, Ruhr University, Cornell University, Northwestern University and Drexel University.

Zwicky Transient Facility access for N.R., S.S., and A.M. was supported by Northwestern University and the Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA).

SED Machine is based upon work supported by the National Science Foundation under Grant No. 1106171.

The Gordon and Betty Moore Foundation, through both the Data-Driven Investigator Program and a dedicated grant, provided critical funding for SkyPortal.