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Discovery of An Apparent Red, High-Velocity Type Ia Supernova at z = 2.9 with JWST

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arxiv 2406.05089 v2 pith:TNS7ZGWQ submitted 2024-06-07 astro-ph.GA astro-ph.COastro-ph.HE

classification astro-ph.GAastro-ph.COastro-ph.HE
keywords adsyjwstlow-zredshiftca-richhostpopulationspectroscopic
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abstract

We present the JWST discovery of SN 2023adsy, a transient object located in a host galaxy JADES-GS$+53.13485$$-$$27.82088$ with a host spectroscopic redshift of $2.903\pm0.007$. The transient was identified in deep James Webb Space Telescope (JWST)/NIRCam imaging from the JWST Advanced Deep Extragalactic Survey (JADES) program. Photometric and spectroscopic followup with NIRCam and NIRSpec, respectively, confirm the redshift and yield UV-NIR light-curve, NIR color, and spectroscopic information all consistent with a Type Ia classification. Despite its classification as a likely SN Ia, SN 2023adsy is both fairly red (E(B-V)$\sim0.9$) despite a host galaxy with low-extinction and has a high Ca II velocity ($19,000\pm2,000$km/s) compared to the general population of SNe Ia. While these characteristics are consistent with some Ca-rich SNe Ia, particularly SN 2016hnk, SN 2023adsy is intrinsically brighter than the low-z Ca-rich population. Although such an object is too red for any low-z cosmological sample, we apply a fiducial standardization approach to SN 2023adsy and find that the SN 2023adsy luminosity distance measurement is in excellent agreement ($\lesssim1\sigma$) with $\Lambda$CDM. Therefore unlike low-z Ca-rich SNe Ia, SN 2023adsy is standardizable and gives no indication that SN Ia standardized luminosities change significantly with redshift. A larger sample of distant SNe Ia is required to determine if SN Ia population characteristics at high-z truly diverge from their low-z counterparts, and to confirm that standardized luminosities nevertheless remain constant with redshift.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The Machine Learning to reconstruct GRB lightcurves

    astro-ph.CO 2025-01 reject novelty 2.0 of 10

    A conference summary of the authors' prior work, reporting that model-based gap filling reduces GRB light-curve fitting uncertainties without new data or validation.

  2. Supernovae Ia, high-redshift probes, and the Hubble tension: current status and future perspectives

    astro-ph.CO 2025-01 unverdicted novelty 1.0 of 10

    A review of the authors' own binned supernova analyses reporting a mild redshift-dependent Hubble constant, plus a discussion of high-redshift probes.

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