An official website of the United States government
Abstract Among the supernovae (SNe) that show strong interaction with a circumstellar medium (CSM), there is a rare subclass of Type Ia supernovae, SNe Ia-CSM, which show strong narrow hydrogen emission lines much like SNe IIn but on top of a diluted Type Ia spectrum. The only previous systematic study of this class identified 16 SNe Ia-CSM, eight historic and eight from the Palomar Transient Factory (PTF). Now using the successor survey to PTF, the Zwicky Transient Facility (ZTF), we have classified 12 additional SNe Ia-CSM through the systematic Bright Transient Survey (BTS). Consistent with previous studies, we find these SNe to have slowly evolving optical light curves with peak absolute magnitudes between −19.1 and −21, spectra having weak Hβand large Balmer decrements of ∼7. Out of the 10 SNe from our sample observed by NEOWISE, nine have 3σdetections, with some SNe showing a reduction in the red wing of Hα, indicative of newly formed dust. We do not find our SN Ia-CSM sample to have a significantly different distribution of equivalent widths of Heiλ5876 than SNe IIn as observed in Silverman et al. The hosts tend to be late-type galaxies with recent star formation. We derive a rate estimate of Gpc−3yr−1for SNe Ia-CSM, which is ∼0.02%–0.2% of the SN Ia rate. We also identify six ambiguous SNe IIn/Ia-CSM in the BTS sample and including them gives an upper limit rate of 0.07%–0.8%. This work nearly doubles the sample of well-studied Ia-CSM objects in Silverman et al., increasing the total number to 28.
more »
« less
SNIascore: Deep Learning Classification of Low-Resolution Supernova Spectra
We present SNIascore, a deep-learning based method for spectroscopic classification of thermonuclear supernovae (SNe Ia) based on very low-resolution (R ∼100) data. The goal of SNIascore is fully automated classification of SNe Ia with a very low false-positive rate (FPR) so that human intervention can be greatly reduced in large-scale SN classification efforts, such as that undertaken by the public Zwicky Transient Facility (ZTF) Bright Transient Survey (BTS). We utilize a recurrent neural network (RNN) architecture with a combination of bidirectional long short-term memory and gated recurrent unit layers. SNIascore achieves a <0.6% FPR while classifying up to 90% of the low-resolution SN Ia spectra obtained by the BTS. SNIascore simultaneously performs binary classification and predicts the redshifts of secure SNe Ia via regression (with a typical uncertainty of <0.005 in the range from z=0.01 to z=0.12). For the magnitude-limited ZTF BTS survey (≈70% SNe Ia), deploying SNIascore reduces the amount of spectra in need of human classification or confirmation by ≈60%. Furthermore, SNIascore allows SN Ia classifications to be automatically announced in real-time to the public immediately following a finished observation during the night.
more »
« less
- PAR ID:
- 10280410
- Date Published:
- Journal Name:
- ArXivorg
- ISSN:
- 2331-8422
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multicolor PanSTARRS1grizand Zwicky Transient Facility (ZTF)grphotometry 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 reachingz≈ 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
-
Abstract We present observations of three core-collapse supernovae (CCSNe) in elliptical hosts, detected by the Zwicky Transient Facility Bright Transient Survey (BTS). SN 2019ape is a SN Ic that exploded in the main body of a typical elliptical galaxy. Its properties are consistent with an explosion of a regular SN Ic progenitor. A secondary g -band light-curve peak could indicate interaction of the ejecta with circumstellar material (CSM). An H α -emitting source at the explosion site suggests a residual local star formation origin. SN 2018fsh and SN 2020uik are SNe II which exploded in the outskirts of elliptical galaxies. SN 2020uik shows typical spectra for SNe II, while SN 2018fsh shows a boxy nebular H α profile, a signature of CSM interaction. We combine these 3 SNe with 7 events from the literature and analyze their hosts as a sample. We present multi-wavelength photometry of the hosts, and compare this to archival photometry of all BTS hosts. Using the spectroscopically complete BTS, we conclude that 0.3 % − 0.1 + 0.3 of all CCSNe occur in elliptical galaxies. We derive star formation rates and stellar masses for the host galaxies and compare them to the properties of other SN hosts. We show that CCSNe in ellipticals have larger physical separations from their hosts compared to SNe Ia in elliptical galaxies, and discuss implications for star-forming activity in elliptical galaxies.more » « less
-
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
-
Abstract The current Cepheid-calibrated distance ladder measurement of H 0 is reported to be in tension with the values inferred from the cosmic microwave background (CMB), assuming standard cosmology. However, some tip of the red giant branch (TRGB) estimates report H 0 in better agreement with the CMB. Hence, it is critical to reduce systematic uncertainties in local measurements to understand the Hubble tension. In this paper, we propose a uniform distance ladder between the second and third rungs, combining Type Ia supernovae (SNe Ia) observed by the Zwicky Transient Facility (ZTF) with a TRGB calibration of their absolute luminosity. A large, volume-limited sample of both calibrator and Hubble flow SNe Ia from the same survey minimizes two of the largest sources of systematics: host-galaxy bias and nonuniform photometric calibration. We present results from a pilot study using the existing TRGB distance to the host galaxy of ZTF SN Ia SN 2021rhu (aka ZTF21abiuvdk) in NGC7814. Combining the ZTF calibrator with a volume-limited sample from the first data release of ZTF Hubble flow SNe Ia, we infer H 0 = 76.94 ± 6.4 km s −1 Mpc −1 , an 8.3% measurement. The error budget is dominated by the single object calibrating the SN Ia luminosity in this pilot study. However, the ZTF sample includes already five other SNe Ia within ∼20 Mpc for which TRGB distances can be obtained with the Hubble Space Telescope. Finally, we present the prospects of building this distance ladder out to 80 Mpc with James Webb Space Telescope observations of more than 100 ZTF SNe Ia.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- The DOI is not currently available.
