J/A+A/702/A128      Type II and IIb Supernovae        (Gonzalez-Banuelos+, 2025)

Statistical analysis of early spectra in Type II and IIb Supernovae, Gonzalez-Banuelos M., Gutierrez C.P., Galbany L., Gonzalez-Gaitan S. <Astron. Astrophys. 702, A128 (2025)> =2025A&A...702A.128G 2025A&A...702A.128G (SIMBAD/NED BibCode)
ADC_Keywords: Supernovae ; Redshifts Keywords: supernovae: general Abstract: We present a comprehensive analysis of the early spectra of type II and type IIb supernovae (SNe) to explore their diversity and distinguishable characteristics. Using 866 publicly available spectra from 393 SNe, including 407 from type IIb SNe (SNe IIb) and 459 from type II SNe (SNe II), we analysed Hα and HeI 5876Å at early phases (<40 days from the explosion) to identify possible differences between these two SN types. By comparing the pseudo-equivalent width (pEW) and full width at half maximum (FWHM), we found that the strength of the absorption component of Hα and HeI lines serves as a quantitative discriminator, with SNe IIb exhibiting stronger lines at all times. The most significant differences emerge within the first 10-20 days. To assess the statistical significance of these differences, we applied statistical methods and machine-learning techniques. Population density evolution reveals a clear distinction in both pEW and FWHM. A quadratic discriminant analysis (QDA) confirmed distinct evolutionary patterns, particularly in pEW, while FWHM variations were less pronounced. Effectively, a combination of t-distributed stochastic neighbour embedding (t-SNE) and linear discriminant analysis (LDA) distinguishes the two SN types. In addition, we used a a random forest classifier (RFC) to demonstrate the robustness of pEW and FWHM as classification criteria, allowing for accurate classifications of newly observed SNe II and IIb based on computed classification probabilities. Applying our method to low-resolution spectra obtained from the magnitude-limited survey carried out by the Zwicky Transient Facility (ZTF BTS), we identified 34 mis-classified SNe. This revision increases the estimated fraction of SNe IIb from 4.0% to 7.26%. This finding suggests that mis-classification significantly impacts the estimated core-collapse SN rate. Our approach enhances the classification accuracy and provides a valuable tool for future SN studies. Description: This table presents the complete supernova (SN) sample used in our analysis. Each row corresponds to a SN and includes the following information: the SN name, its type as adopted in this work, the number of spectra used in our analysis, the redshift, the discovery reference, and additional references. The latter may include papers used for classification, previous works that analyzed the same spectra, or other studies supporting the classification adopted here. File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file tableb5.dat 144 393 Complete SN sample used in our analysis -------------------------------------------------------------------------------- See also: J/A+A/579/A40 : PESSTO catalog (Smartt+, 2015) Byte-by-byte Description of file: tableb5.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 11 A11 --- SN Supernova name 13- 20 A8 --- Type Supernova type used in this work 22- 23 I2 --- Nspec Number of spectra used in our analysis 26- 37 F12.9 --- z Redshift 39- 57 A19 --- refDisc Discovery reference (BibCode or short citation) 60-144 A85 --- RefOther Additional references for classification, previous works, or support for the adopted type (BibCode or short citation) (1) -------------------------------------------------------------------------------- Note (1): Codes after reference: *** = Classified by the Public European Southern Observatory Spectroscopic Survey of Transient Objects (PESSTO; Smartt et al., 2015A&A...579A..40S 2015A&A...579A..40S, Cat. J/A+A/579/A40). * = Obtained from the public data releases of the PESSTO and ePESSTO+ collaborations. Data taken up to 2016 were retrieved from the cumulative PESSTO releases (SSDR1-3; Smartt et al., 2015A&A...579A..40S 2015A&A...579A..40S, Cat. J/A+A/579/A40) available through the ESO Science Archive. Data from 2019 onward were retrieved from the ePESSTO+ dynamic release (Inserra et al. 2023, https://doi.org/10.18727/archive/86). a = Spectra are available from WISeREP (Yaron & Gal-Yam, 2012PASP..124..668Y 2012PASP..124..668Y); contributed by Han Lin. -------------------------------------------------------------------------------- Acknowledgements: Maider Gonzalez-Banuelos, maigb27(at)gmail.com
(End) Patricia Vannier [CDS] 17-Jul-2025
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