skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Anomaly Detection and Approximate Similarity Searches of Transients in Real-time Data Streams
Abstract We present Lightcurve Anomaly Identification and Similarity Search (LAISS), an automated pipeline to detect anomalous astrophysical transients in real-time data streams. We deploy our anomaly detection model on the nightly Zwicky Transient Facility (ZTF) Alert Stream via the ANTARES broker, identifying a manageable ∼1–5 candidates per night for expert vetting and coordinating follow-up observations. Our method leverages statistical light-curve and contextual host galaxy features within a random forest classifier, tagging transients of rare classes (spectroscopicanomalies), of uncommon host galaxy environments (contextualanomalies), and of peculiar or interaction-powered phenomena (behavioralanomalies). Moreover, we demonstrate the power of a low-latency (∼ms) approximate similarity search method to find transient analogs with similar light-curve evolution and host galaxy environments. We use analogs for data-driven discovery, characterization, (re)classification, and imputation in retrospective and real-time searches. To date, we have identified ∼50 previously known and previously missed rare transients from real-time and retrospective searches, including but not limited to superluminous supernovae (SLSNe), tidal disruption events, SNe IIn, SNe IIb, SNe I-CSM, SNe Ia-91bg-like, SNe Ib, SNe Ic, SNe Ic-BL, and M31 novae. Lastly, we report the discovery of 325 total transients, all observed between 2018 and 2021 and absent from public catalogs (∼1% of all ZTF Astronomical Transient reports to the Transient Name Server through 2021). These methods enable a systematic approach to finding the “needle in the haystack” in large-volume data streams. Because of its integration with the ANTARES broker,LAISSis built to detect exciting transients in Rubin data.  more » « less
Award ID(s):
2307710 2019786 2206195
PAR ID:
10558736
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more » ; ; ; ; ; ; ; ; ; ; ; ; « less
Publisher / Repository:
IOP Publishing
Date Published:
Journal Name:
The Astrophysical Journal
Volume:
974
Issue:
2
ISSN:
0004-637X
Page Range / eLocation ID:
172
Subject(s) / Keyword(s):
.
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ; ; et al (, The Astrophysical Journal Supplement Series)
    Abstract We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multicolor PanSTARRS1 griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host–galaxy associations, redshifts, spectroscopic and/or photometric classifications, and additional data products from 2019 November 24 to 2021 December 20. YSE DR1 spans discoveries and observations from young and fast-rising supernovae (SNe) to transients that persist for over a year, with a redshift distribution reaching z ≈ 0.5. We present relative SN rates from YSE’s magnitude- and volume-limited surveys, which are consistent with previously published values within estimated uncertainties for untargeted surveys. We combine YSE and ZTF data, and create multisurvey SN simulations to train the ParSNIP and SuperRAENN photometric classification algorithms; when validating our ParSNIP classifier on 472 spectroscopically classified YSE DR1 SNe, we achieve 82% accuracy across three SN classes (SNe Ia, II, Ib/Ic) and 90% accuracy across two SN classes (SNe Ia, core-collapse SNe). Our classifier performs particularly well on SNe Ia, with high (>90%) individual completeness and purity, which will help build an anchor photometric SNe Ia sample for cosmology. We then use our photometric classifier to characterize our photometric sample of 1483 SNe, labeling 1048 (∼71%) SNe Ia, 339 (∼23%) SNe II, and 96 (∼6%) SNe Ib/Ic. YSE DR1 provides a training ground for building discovery, anomaly detection, and classification algorithms, performing cosmological analyses, understanding the nature of red and rare transients, exploring tidal disruption events and nuclear variability, and preparing for the forthcoming Vera C. Rubin Observatory Legacy Survey of Space and Time. 
    more » « less
  2. ; ; ; ; ; ; ; ; ; ; et al (, The Astrophysical Journal)
    Abstract Photometric classifications of supernova (SN) light curves have become necessary to utilize the full potential of large samples of observations obtained from wide-field photometric surveys, such as the Zwicky Transient Facility (ZTF) and the Vera C. Rubin Observatory. Here, we present a photometric classifier for SN light curves that does not rely on redshift information and still maintains comparable accuracy to redshift-dependent classifiers. Our new package, Superphot+, uses a parametric model to extract meaningful features from multiband SN light curves. We train a gradient-boosted machine with fit parameters from 6061 ZTF SNe that pass data quality cuts and are spectroscopically classified as one of five classes: SN Ia, SN II, SN Ib/c, SN IIn, and SLSN-I. Without redshift information, our classifier yields a class-averagedF1-score of 0.61 ± 0.02 and a total accuracy of 0.83 ± 0.01. Including redshift information improves these metrics to 0.71 ± 0.02 and 0.88 ± 0.01, respectively. We assign new class probabilities to 3558 ZTF transients that show SN-like characteristics (based on the ALeRCE Broker light-curve and stamp classifiers) but lack spectroscopic classifications. Finally, we compare our predicted SN labels with those generated by the ALeRCE light-curve classifier, finding that the two classifiers agree on photometric labels for 82% ± 2% of light curves with spectroscopic labels and 72% ± 0% of light curves without spectroscopic labels. Superphot+ is currently classifying ZTF SNe in real time via the ANTARES Broker, and is designed for simple adaptation to six-band Rubin light curves in the future. 
    more » « less
  3. ; ; ; ; ; ; ; ; ; ; et al (, The Astrophysical Journal)
    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. 
    more » « less
  4. ; ; ; ; ; ; ; ; ; ; et al (, The Astrophysical Journal Letters)
    Abstract We report multiwavelength observations and characterization of the ultraluminous transient AT 2021lwx (ZTF20abrbeie; aka “Barbie”) identified in the alert stream of the Zwicky Transient Facility (ZTF) using a Recommender Engine For Intelligent Transient Tracking filter on the ANTARES alert broker. From a spectroscopically measured redshift of 0.995, we estimate a peak-observed pseudo-bolometric luminosity of log( L max / [ erg s − 1 ] ) = 45.7 from slowly fading ztf- g and ztf- r light curves spanning over 1000 observer-frame days. The host galaxy is not detected in archival Pan-STARRS observations ( g > 23.3 mag), implying a lower limit to the outburst amplitude of more than 5 mag relative to the quiescent host galaxy. Optical spectra exhibit strong emission lines with narrow cores from the H Balmer series and ultraviolet semi-forbidden lines of Si iii ] λ 1892, C iii ] λ 1909, and  C ii ] λ 2325. Typical nebular lines in Active Galactic Nucleus (AGN) spectra from ions such as [O ii ] and [O iii ] are not detected. These spectral features, along with the smooth light curve that is unlike most AGN flaring activity and the luminosity that exceeds any observed or theorized supernova, lead us to conclude that AT 2021lwx is most likely an extreme tidal disruption event (TDE). Modeling of ZTF photometry with MOSFiT suggests that the TDE was between a ≈14 M ⊙ star and a supermassive black hole of mass M BH ∼ 10 8 M ⊙ . Continued monitoring of the still-evolving light curve along with deep imaging of the field once AT 2021lwx has faded can test this hypothesis and potentially detect the host galaxy. 
    more » « less
  5. ; ; ; ; ; ; ; ; ; ; et al (, The Astrophysical Journal)
    Abstract We have extracted 636 spectra taken at the positions of 583 transient sources from the third data release of the Hobby–Eberly Telescope Dark Energy eXperiment (HETDEX). The transients were discovered by the Zwicky Transient Facility (ZTF) during 2018–2022. The HETDEX spectra provide a potential means to obtain classifications for a large number of objects found by photometric surveys for free. We attempt to explore and classify the spectra by utilizing several template-matching techniques. We have identified two transient sources, ZTF20aatpoos = AT 2020fiz and ZTF19abdkelq, as supernova (SN) candidates. We classify AT 2020fiz as a Type IIP SN observed ∼10 days after explosion, and we propose ZTF19abdkelq as a likely Type Ia SN caught ∼40 days after maximum light. ZTF photometry of these two sources are consistent with their classifications as SNe. Beside these two objects, we have confirmed several ZTF transients as variable active galactic nuclei based on their spectral appearance, and determined the host galaxy types of several other ZTF transients. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Text Encoded Conversion
  • XML
  • Save / Share this Record
  • Send to Email