Issue |
A&A
Volume 672, April 2023
|
|
---|---|---|
Article Number | A129 | |
Number of page(s) | 18 | |
Section | Extragalactic astronomy | |
DOI | https://doi.org/10.1051/0004-6361/202245379 | |
Published online | 10 April 2023 |
Consistency of Type IIP supernova sibling distances
1
Max-Planck-Institute für Astrophysik, Karl-Schwarzschild-Str. 1, 85748 Garching, Germany
e-mail: csogeza@mpa-garching.mpg.de
2
Physics Department, Technische Universität München, James-Franck-Str. 1, 85748 Garching, Germany
3
Exzellenzcluster ORIGINS, Boltzmannstr. 2, 85748 Garching, Germany
4
GSI Helmholtzzentrum für Schwerionenforschung, Planckstraße 1, 64291 Darmstadt, Germany
5
Aix-Marseille Univ, CNRS, CNES, LAM, 13388 Marseille, France
6
European Southern Observatory, Karl-Schwarzschild-Str. 2, 85748 Garching, Germany
7
School of Natural Sciences, Technische Universität München, James-Franck-Str. 1., 85748 Garching, Germany
8
Zentrum für Astronomie der Universität Heidelberg, Institut für Theoretische Astrophysik, Philosophenweg 12, 69120 Heidelberg, Germany
9
Heidelberg Institute for Theoretical Studies, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany
Received:
4
November
2022
Accepted:
3
February
2023
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.
Key words: radiative transfer / stars: distances / supernovae: general
© The Authors 2023
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article is published in open access under the Subscribe to Open model.
Open access funding provided by Max Planck Society.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.