AstroNote 2024-217

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DRAFT
2024-08-07 18:36:35
Type: Object/s-Discovery/Classification
SLSN-I and TDE candidates from NEEDLE on Lasair
Authors: X. Sheng, M. Nicholl, K. W. Smith, C. R. Angus, A. Aamer, M. Fulton, T. Moore, J. Weston, D. R. Young (QUB), P. Ramsden (Birmingham/QUB), S. J. Smartt (Oxford/QUB), S. Srivastav, H. Stevance (Oxford), A. Sankar.K (NCU)
Source Group: OxQUB
Abstract:
We report 10 SLSN-I and 2 TDE candidates from the ZTF public alert stream, identified by the NEEDLE classifier running on the Lasair alert broker. We encourage spectroscopic classification of these events.

The Neural Engine for Discovering Luminous Events (NEEDLE) classifier (Sheng et al. 2024) is a machine-learning tool for identifying rare astronomical transients from real-time alerts. NEEDLE is trained to identify Superluminous Supernova (SLSN) and Tidal Disruption Events (TDE) candidates in data from the Zwicky Transient Facility (ZTF; Bellm et al. 2019; Graham et al. 2019). We are running NEEDLE daily on public ZTF alerts, streamed via the Lasair alert broker (K. Smith et al. 2019), and publicly providing classification predictions as annotations on Lasair.

We provide three SQL filters on Lasair with our candidates (also output as Kafka streams): NEEDLE SLSN candidates, NEEDLE TDE candidates, and all NEEDLE annotations. Lasair users can also incorporate NEEDLE outputs into their own custom SQL filters.

We manually vet all alerts with a SLSN or TDE score > 0.5, and will highlight the most promising candidates in these AstroNotes. This report includes recent SLSN-I and TDE candidates, shown below. We encourage spectroscopic classification and follow-up.

Show current TNS values
CatalogNameReported RAReported DECReported Obj-TypeReported RedshiftHost NameHost RedshiftCandidate typeRemarksTNS RATNS DECTNS Obj-TypeTNS Redshift
TNS2024knb [ZTF24aaqpnyq]02:11:24.140+46:42:14.83SLSN-Ihttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aaqpnyq/02:11:24.140+46:42:14.83SN II0.0673
TNS2024pyk [ZTF24aawxsjw]15:07:58.435+25:20:48.10SLSN-Ihttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aawxsjw/15:07:58.435+25:20:48.10
TNS2024pqo [ZTF24aaumjxr]15:53:23.455+41:49:21.12SLSN-Ihttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aaumjxr/15:53:23.455+41:49:21.12
TNS2024qnx [ZTF24aawxqtz]15:43:36.078+01:21:38.46SLSN-Ihttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aawxqtz/15:43:36.078+01:21:38.46
TNS2024qaw [ZTF24aaxasok]15:51:14.810+28:43:03.48SDSS J155114.73+284303.4SLSN-Ihttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aaxasok/15:51:14.810+28:43:03.48
TNS2024qyz [ZTF24aaybugo]18:03:07.508+69:50:17.91SLSN-Ihttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aaybugo/18:03:07.486+69:50:17.93
TNS2024qxg [ZTF24aavxdpn]21:44:28.309+01:33:52.80SLSN-Ihttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aavxdpn/21:44:28.309+01:33:52.80SLSN-I0.45
TNS2024nbk [ZTF24aatkycx]17:37:38.482+48:07:01.41SLSN-Ihttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aatkycx/17:37:38.482+48:07:01.41
TNS2024qkx [ZTF24aaxoguq]15:18:39.712+03:21:24.86SLSN-Ihttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aaxoguq/15:18:39.712+03:21:24.86
TNS2024ntf [ZTF24aauevaw]17:30:09.243+57:36:07.35SDSS J173009.23+573604.7SLSN-Ihttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aauevaw/17:30:09.243+57:36:07.35
TNS2024qyx [ZTF24aaycdea]16:56:32.629+58:07:09.85WISEA J165632.70+580709.4TDEhttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aaycdea/16:56:32.629+58:07:09.85
TNS2024qkr [ZTF24aaxgcyi]16:14:04.129+28:29:15.09SDSS J161404.11+282915.0TDEhttps://lasair-ztf.lsst.ac.uk/objects/ZTF24aaxgcyi/16:14:04.129+28:29:15.09