Supernova siblings and their parent galaxies in the Zwicky Transient Facility Bright Transient Survey

Graham, M. L.; Fremling, C.; Perley, D. A.; Biswas, Rahul; Phillips, C. A.; Sollerman, J.; Nugent, P.; Nance, Sandra; Dhawan, Suhail; Nordin, J.; Goobar, A.; Miller, A. A.; Neill, James D.; Hall, Xander J.; Hankins, M.; Duev, Dmitry A.; Kasliwal, M. M.; Rigault, M.; Bellm, Eric C.; Hale, David; Mróz, P.; Kulkarni, S. R.

doi:10.1093/mnras/stab3802

Cited by 8 publications

(7 citation statements)

References 73 publications

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“…A workaround will be to analyze a sample of SN Ia siblings observed on a single photometric system, thus mitigating cross-calibration systematics. The near-future sample of ZTF DR2 siblings (Dhawan et al 2022;Graham et al 2022) is expected to contain ≈30 SN Ia sibling galaxies, so it will be an interesting test set for investigating σ Rel , and its SN-model dependence.…”

Section: Discussionmentioning

confidence: 99%

“…Intermediate-sized samples of SN Ia siblings have already been compiled, numbering ∼10-40 siblings (e.g., Burns et al 2020;Scolnic et al 2020Scolnic et al , 2022Graham et al 2022). The largest sibling sample to date was recently presented in Kelsey (2023), and it comprises 158 galaxies with 327 SNe Ia.…”

Section: Discussionmentioning

confidence: 99%

“…SN Ia siblings-SNe Ia that occur in the same host galaxyare valuable for investigating standardization systematics (Elias et al 1981;Hamuy et al 1991;Stritzinger et al 2011;Brown et al 2015;Gall et al 2018;Burns et al 2020;Scolnic et al 2020Scolnic et al , 2022Graham et al 2022;Kelsey 2023). Siblings share common properties, like distance, redshift, and host galaxy stellar mass.…”

Section: Introductionmentioning

confidence: 99%

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Relative Intrinsic Scatter in Hierarchical Type Ia Supernova Sibling Analyses: Application to SNe 2021hpr, 1997bq, and 2008fv in NGC 3147

Ward,

Thorp,

Mandel

et al. 2023

ApJ

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We present Young Supernova Experiment grizy photometry of SN 2021hpr, the third Type Ia supernova sibling to explode in the Cepheid calibrator galaxy, NGC 3147. Siblings are useful for improving SN-host distance estimates and investigating their contributions toward the SN Ia intrinsic scatter (post-standardization residual scatter in distance estimates). We thus develop a principled Bayesian framework for analyzing SN Ia siblings. At its core is the cosmology-independent relative intrinsic scatter parameter, σ Rel: the dispersion of siblings distance estimates relative to one another within a galaxy. It quantifies the contribution toward the total intrinsic scatter, σ 0, from within-galaxy variations about the siblings’ common properties. It also affects the combined distance uncertainty. We present analytic formulae for computing a σ Rel posterior from individual siblings distances (estimated using any SN model). Applying a newly trained BayeSN model, we fit the light curves of each sibling in NGC 3147 individually, to yield consistent distance estimates. However, the wide σ Rel posterior means σ Rel ≈ σ 0 is not ruled out. We thus combine the distances by marginalizing over σ Rel with an informative prior: σ Rel ∼ U(0, σ 0). Simultaneously fitting the trio’s light curves improves constraints on distance and each sibling’s individual dust parameters, compared to individual fits. Higher correlation also tightens dust parameter constraints. Therefore, σ Rel marginalization yields robust estimates of siblings distances for cosmology, as well as dust parameters for sibling–host correlation studies. Incorporating NGC 3147's Cepheid distance yields H 0 = 78.4 ± 6.5 km s−1 Mpc−1. Our work motivates analyses of homogeneous siblings samples, to constrain σ Rel and its SN-model dependence.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Relative Intrinsic Scatter in Hierarchical Type Ia Supernova Sibling Analyses: Application to SNe 2021hpr, 1997bq, and 2008fv in NGC 3147

Ward,

Thorp,

Mandel

et al. 2023

ApJ

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“…Such consistency checks were recently carried out in the literature for pairs of Type Ia supernovae (see e.g. Burns et al 2020;Scolnic et al 2020) as well as for a pair of a Type Ia and a Type IIP supernova (Graham et al 2022), yielding good matches. However, no similar tests have yet been conducted on Type II supernovae specifically.…”

Section: Introductionmentioning

confidence: 92%

Consistency of Type IIP supernova sibling distances

Csörnyei

Vogl

Taubenberger

et al. 2023

A&A

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Context. Type II supernovae offer a direct way of estimating distances via the expanding photosphere method, which is independent of the cosmic distance ladder. A Gaussian process-based method was recently introduced, allowing for a fast and precise modelling of spectral time series and placing accurate and computationally cheap Type II-based absolute distance determinations within reach. Aims. The goal of this work is to assess the internal consistency of this new modelling technique coupled with the distance estimation in an empirical way, using the spectral time series of supernova siblings, that is, supernovae that exploded in the same host galaxy. Methods. We used a recently developed spectral emulator code, trained on TARDIS radiative transfer models that is capable of a fast maximum-likelihood parameter estimation and spectral fitting. After calculating the relevant physical parameters of supernovae, we applied the expanding photosphere method to estimate their distances. Finally, we tested the consistency of the obtained values by applying the formalism of Bayes factors. Results. The distances to four different host galaxies were estimated based on two supernovae in each. The distance estimates are not only consistent within the errors for each of the supernova sibling pairs, but in the case of two hosts, they are precise to better than 5%. The analysis also showed that the main limiting factor of this estimation is the number and quality of spectra available for the individual objects, rather than the physical differences of the siblings. Conclusions. Even though the literature data we used was not tailored to the requirements of our analysis, the agreement of the final estimates shows that the method is robust and is capable of inferring both precise and consistent distances. By using high-quality spectral time series, this method can provide precise distance estimates independent of the distance ladder, which are of high value for cosmology.

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“…Other identifying factors are fast-cadence searches, including the ZTF 1 day survey, Kepler (K2; Howell et al 2014), the Evryscope (Law et al 2015), the Korea Microlensing Telescope Network (Kim et al 2016), DLT40 (Valenti et al 2017), TESS (Fausnaugh et al 2021), and wavelength regimes beyond the optical (nearinfrared via the Vista Infrared Extragalactic Legacy Survey, Hönig et al (2017); and ultraviolet via the Galaxy Evolution Explorer (GALEX) time-domain survey (Gezari et al 2013). Data from these surveys helped in our understanding of SN explosion mechanisms and local rates, SN siblings, host galaxy properties, black holes, stellar evolution, and the expansion of our universe (Nomoto et al 2013;Riess et al 2016;Abbott et al 2017;Scolnic et al 2018;Fremling et al 2020;Gagliano et al 2021;Graham et al 2022).…”

Section: Introductionmentioning

confidence: 99%

The Young Supernova Experiment Data Release 1 (YSE DR1): Light Curves and Photometric Classification of 1975 Supernovae

Aleo

Malanchev

Sharief

et al. 2023

ApJS

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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.

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Supernova siblings and their parent galaxies in the Zwicky Transient Facility Bright Transient Survey

Cited by 8 publications

References 73 publications

Relative Intrinsic Scatter in Hierarchical Type Ia Supernova Sibling Analyses: Application to SNe 2021hpr, 1997bq, and 2008fv in NGC 3147

Relative Intrinsic Scatter in Hierarchical Type Ia Supernova Sibling Analyses: Application to SNe 2021hpr, 1997bq, and 2008fv in NGC 3147

Consistency of Type IIP supernova sibling distances

The Young Supernova Experiment Data Release 1 (YSE DR1): Light Curves and Photometric Classification of 1975 Supernovae

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