Abstract The detonation of a thin (≲0.03 M ⊙ ) helium shell (He-shell) atop a ∼1 M ⊙ white dwarf (WD) is a promising mechanism to explain normal Type Ia supernovae (SNe Ia), while thicker He-shells and less massive WDs may explain some recently observed peculiar SNe Ia. We present observations of SN 2020jgb, a peculiar SN Ia discovered by the Zwicky Transient Facility (ZTF). Near maximum brightness, SN 2020jgb is slightly subluminous (ZTF g -band absolute magnitude −18.7 mag ≲ M g ≲ −18.2 mag depending on the amount of host-galaxy extinction) and shows an unusually red color (0.2 mag ≲ g ZTF − r ZTF ≲ 0.4 mag) due to strong line-blanketing blueward of ∼5000 Å. These properties resemble those of SN 2018byg, a peculiar SN Ia consistent with an He-shell double detonation (DDet) SN. Using detailed radiative transfer models, we show that the optical spectroscopic and photometric evolution of SN 2020jgb is broadly consistent with a ∼0.95–1.00 M ⊙ (C/O core + He-shell) progenitor ignited by a ≳0.1 M ⊙ He-shell. However, one-dimensional radiative transfer models without non-local-thermodynamic-equilibrium treatment cannot accurately characterize the line-blanketing features, making the actual shell mass uncertain. We detect a prominent absorption feature at ∼1 μ m in the near-infrared (NIR) spectrum of SN 2020jgb, which might originate from unburnt helium in the outermost ejecta. While the sample size is limited, we find similar 1 μ m features in all the peculiar He-shell DDet candidates with NIR spectra obtained to date. SN 2020jgb is also the first peculiar He-shell DDet SN discovered in a star-forming dwarf galaxy, indisputably showing that He-shell DDet SNe occur in both star-forming and passive galaxies, consistent with the normal SN Ia population.
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HyperGal: Hyperspectral scene modeling for supernova typing with the SED Machine integral field spectrograph
Context. Recent developments in time domain astronomy, such as Zwicky Transient Facility (ZTF), have made it possible to conduct daily scans of the entire visible sky, leading to the discovery of hundreds of new transients every night. Among these detections, 10 to 15 of these objects are supernovae (SNe), which have to be classified prior to cosmological use. The spectral energy distribution machine (SEDM) is a low-resolution ( ℛ ~ 100) integral field spectrograph designed, built, and operated with the aim of spectroscopically observing and classifying targets detected by the ZTF main camera. Aims. As the current pysedm pipeline can only handle isolated point sources, it is limited by contamination when the transient is too close to its host galaxy core. This can lead to an incorrect typing and ultimately bias the cosmological analyses, affecting the homogeneity of the SN sample in terms of local environment properties. We present a new scene modeler to extract the transient spectrum from its structured background, with the aim of improving the typing efficiency of the SEDM. Methods. H yper G al is a fully chromatic scene modeler that uses archival pre-transient photometric images of the SN environment to generate a hyperspectral model of the host galaxy. It is based on the cigale SED fitter used as a physically-motivated spectral interpolator. The galaxy model, complemented by a point source for the transient and a diffuse background component, is projected onto the SEDM spectro-spatial observation space and adjusted to observations, and the SN spectrum is ultimately extracted from this multi-component model. The full procedure, from scene modeling to transient spectrum extraction and typing, is validated on 5000 simulated cubes built from actual SEDM observations of isolated host galaxies, covering a broad range of observing conditions and scene parameters. Results. We introduce the contrast, c , as the transient-to-total flux ratio at the SN location, integrated over the ZTF r -band. From estimated contrast distribution of real SEDm observations, we show that H yper G al correctly classifies ~95% of SNe Ia, and up to 99% for contrast c ≳ 0.2, representing more than 90% of the observations. Compared to the standard point-source extraction method (without the hyperspectral galaxy modeling step), H yper G al correctly classifies 20% more SNe Ia between 0.1 < c < 0.6 (50% of the observation conditions), with less than 5% of SN Ia misidentifications. The false-positive rate is less than 2% for c > 0.1 (> 99% of the observations), which represents half as much as the standard extraction method. Assuming a similar contrast distribution for core-collapse SNe, H yper G al classifies 14% additional SNe II and 11% additional SNe Ibc. Conclusions. H yper G al has proven to be extremely effective in extracting and classifying SNe in the presence of strong contamination by the host galaxy, providing a significant improvement with respect to the single point-source extraction.
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- Award ID(s):
- 2034437
- NSF-PAR ID:
- 10424018
- Date Published:
- Journal Name:
- Astronomy & Astrophysics
- Volume:
- 668
- ISSN:
- 0004-6361
- Page Range / eLocation ID:
- A43
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1051/0004-6361/202244740
