Abstract The Bright Transient Survey (BTS) aims to obtain a classification spectrum for all bright (mpeak≤ 18.5 mag) extragalactic transients found in the Zwicky Transient Facility (ZTF) public survey. BTS critically relies on visual inspection (“scanning”) to select targets for spectroscopic follow-up, which, while effective, has required a significant time investment over the past ∼5 yr of ZTF operations. We presentBTSbot, a multimodal convolutional neural network, which provides a bright transient score to individual ZTF detections using their image data and 25 extracted features.BTSbotis able to eliminate the need for daily human scanning by automatically identifying and requesting spectroscopic follow-up observations of new bright transient candidates.BTSbotrecovers all bright transients in our test split and performs on par with scanners in terms of identification speed (on average, ∼1 hr quicker than scanners). We also find thatBTSbotis not significantly impacted by any data shift by comparing performance across a concealed test split and a sample of very recent BTS candidates.BTSbothas been integrated intoFritzandKowalski, ZTF’s first-party marshal and alert broker, and now sends automatic spectroscopic follow-up requests for the new transients it identifies. Between 2023 December and 2024 May,BTSbotselected 609 sources in real time, 96% of which were real extragalactic transients. WithBTSbotand other automation tools, the BTS workflow has produced the first fully automatic end-to-end discovery and classification of a transient, representing a significant reduction in the human time needed to scan.
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YSE-PZ: A Transient Survey Management Platform that Empowers the Human-in-the-loop
Abstract The modern study of astrophysical transients has been transformed by an exponentially growing volume of data. Within the last decade, the transient discovery rate has increased by a factor of ∼20, with associated survey data, archival data, and metadata also increasing with the number of discoveries. To manage the data at this increased rate, we require new tools. Here we presentYSE-PZ, a transient survey management platform that ingests multiple live streams of transient discovery alerts, identifies the host galaxies of those transients, downloads coincident archival data, and retrieves photometry and spectra from ongoing surveys.YSE-PZalso presents a user with a range of tools to make and support timely and informed transient follow-up decisions. Those subsequent observations enhance transient science and can reveal physics only accessible with rapid follow-up observations. Rather than automating out human interaction,YSE-PZfocuses on accelerating and enhancing human decision making, a role we describe as empowering the human-in-the-loop. Finally,YSE-PZis built to be flexibly used and deployed;YSE-PZcan support multiple, simultaneous, and independent transient collaborations through group-level data permissions, allowing a user to view the data associated with the union of all groups in which they are a member.YSE-PZcan be used as a local instance installed via Docker or deployed as a service hosted in the cloud. We provideYSE-PZas an open-source tool for the community.
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- PAR ID:
- 10491550
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Publications of the Astronomical Society of the Pacific
- Date Published:
- Journal Name:
- Publications of the Astronomical Society of the Pacific
- Volume:
- 135
- Issue:
- 1048
- ISSN:
- 0004-6280
- Page Range / eLocation ID:
- 064501
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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