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Type II supernovae from the Carnegie Supernova Project-I II. Physical parameter distributions from hydrodynamical modelling
Indexado
WoS WOS:000779103200001
Scopus SCOPUS_ID:85128366871
DOI 10.1051/0004-6361/202142076
Año 2022
Tipo artículo de investigación

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras


Abstract



Linking supernovae to their progenitors is a powerful method for furthering our understanding of the physical origin of their observed differences while at the same time testing stellar evolution theory. In this second study of a series of three papers where we characterise type II supernovae (SNe II) to understand their diversity, we derive progenitor properties (initial and ejecta masses and radius), explosion energy, and Ni-56 mass and its degree of mixing within the ejecta for a large sample of SNe IL This dataset was obtained by the Carnegie Supernova Project-I and is characterised by a high cadence of SNe II optical and near-infrared light curves and optical spectra that were homogeneously observed and processed. A large grid of hydrodynamical models and a fitting procedure based on Markov chain Monte Carlo methods were used to fit the bolometric light curve and the evolution of the photospheric velocity of 53 SNe II. We infer ejecta masses of between 7.9 and 14.8 M-circle dot, explosion energies between 0.15 and 1.40 foe, and Ni-56 masses between 0.006 and 0.069 M-circle dot. We define a subset of 24 SNe (the 'gold sample') with well-sampled bolometric light curves and expansion velocities for which we consider the results more robust. Most SNe II in the gold sample (similar to 88%) are found with ejecta masses in the range of similar to 8-10 M-circle dot, coming from low zero-age main-sequence masses (9-12 M-circle dot). The modelling of the initial-mass distribution of the gold sample gives an upper mass limit of 21.3(-0.4)(+3.8)M(circle dot) and a much steeper distribution than that for a Salpeter massive-star initial mass function (IMF). This IMF incompatibility is due to the large number of low-mass progenitors found - when assuming standard stellar evolution. This may imply that high-mass progenitors lose more mass during their lives than predicted. However, a deeper analysis of all stellar evolution assumptions is required to test this hypothesis.

Revista



Revista ISSN
Astronomy & Astrophysics 0004-6361

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Disciplinas de Investigación



WOS
Astronomy & Astrophysics
Scopus
Sin Disciplinas
SciELO
Sin Disciplinas

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Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Colaboración Institucional



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Autores - Afiliación



Ord. Autor Género Institución - País
1 Kankare, E. Hombre CCT CONICET UNLP - Argentina
UNIV NACL LA PLATA - Argentina
Univ Nacl Rio Negro - Argentina
2 BERSTEN-SOSA, MELINA CECILIA Mujer CCT CONICET UNLP - Argentina
UNIV NACL LA PLATA - Argentina
Univ Tokyo - Japón
Consejo Nacional de Investigaciones Científicas y Técnicas - Argentina
Universidad Nacional de La Plata - Argentina
The University of Tokyo - Japón
3 Anderson, J. P. - ESO - Chile
4 HAMUY-WACKENHUT, MARIO ANDRÉS Hombre Mission AURA O Chile - Chile
Texas A&M Univ - Estados Unidos
Vice President and Head of Mission of AURA-O in Chile - Chile
Texas A&M University - Estados Unidos
5 Gonzalez-Gaitan, S. Hombre Univ Lisbon - Portugal
Instituto Superior Técnico - Portugal
6 FORSTER-BURON, FRANCISCO Hombre Universidad de Chile - Chile
Instituto Milenio de Astrofísica - Chile
7 Orellana, M. Mujer Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) - Argentina
Universidad Nacional de Río Negro - Argentina
Consejo Nacional de Investigaciones Científicas y Técnicas - Argentina
8 Stritzinger, M. D. Hombre Aarhus Univ - Dinamarca
Aarhus Universitet - Dinamarca
9 Phillips, Mark M. Hombre Observatorio Las Campanas - Chile
Las Campanas Observatory - Chile
10 GUTIERREZ-AVENDANO, CLAUDIA PATRICIA Mujer Univ Turku - Finlandia
Turun yliopisto - Finlandia
Tuorlan observatorio - Finlandia
11 Burns, C. Hombre Observ Carnegie Inst Sci - Estados Unidos
Observatorio Las Campanas - Estados Unidos
12 CONTRERAS-HIDALGO, CARLOS SEBASTIAN Hombre Observatorio Las Campanas - Chile
Las Campanas Observatory - Chile
13 DE JAEGER-GAILLARD, THOMAS MAXIMILIEN Hombre Univ Hawaii - Estados Unidos
UNIV CALIF BERKELEY - Estados Unidos
University Hawaii Institute for Astronomy - Estados Unidos
University of California, Berkeley - Estados Unidos
14 Ertini, K. - CCT CONICET UNLP - Argentina
UNIV NACL LA PLATA - Argentina
Consejo Nacional de Investigaciones Científicas y Técnicas - Argentina
Universidad Nacional de La Plata - Argentina
15 Folatelli, Gaston Hombre CCT CONICET UNLP - Argentina
UNIV NACL LA PLATA - Argentina
Univ Tokyo - Japón
Consejo Nacional de Investigaciones Científicas y Técnicas - Argentina
Universidad Nacional de La Plata - Argentina
The University of Tokyo - Japón
16 Frohmaier, C. Hombre CSIC - España
CSIC - Instituto de Ciencias del Espacio (ICE) - España
17 Hoeflich, P. Hombre FLORIDA STATE UNIV - Estados Unidos
Florida State University - Estados Unidos
College of Arts and Sciences - Estados Unidos
18 Hsiao, Eric Y. Hombre FLORIDA STATE UNIV - Estados Unidos
Florida State University - Estados Unidos
College of Arts and Sciences - Estados Unidos
19 MORRELL, NIDIA IRENE Mujer Observatorio Las Campanas - Chile
Las Campanas Observatory - Chile
20 Pessi, P. J. Mujer UNIV NACL LA PLATA - Argentina
ESO - Chile
Universidad Nacional de La Plata - Argentina
European Southern Observatory Santiago - Chile
European Southern Observ - Chile
21 Suntzeff, N. B. Hombre Texas A&M Univ - Estados Unidos
Texas A&M University - Estados Unidos

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Financiamiento



Fuente
FONDECYT
Consejo Nacional de Investigaciones Científicas y Técnicas
National Science Foundation
Fundação para a Ciência e a Tecnologia
Fondo Nacional de Desarrollo Científico y Tecnológico
Ministerio de Economía, Fomento y Turismo, Chile
Universidad Nacional de Río Negro
Ministerio de Ciencia, Innovacion y Universidades
Ministry of Economy, Development, and Tourism's Millennium Science Initiative
National Science Foundation (NSF)
VILLUM FONDEN
Spanish Ministry of Science, Innovation and Universities (MICIU)
Danmarks Frie Forskningsfond
CONICET fellowship
ANID
National Agency for Research and Development (ANID)
MICIU
Independent Research Fund Denmark (IRFD)
UNRN
National Agency for Research and Development
FCT under Project CRISP
Hagler Institute of Advanced Study at Texas AM University
Spanish MICIU project
Hagler Institute for Advanced Study, Texas A&M University

Muestra la fuente de financiamiento declarada en la publicación.

Agradecimientos



Agradecimiento
We thank the referee for the useful comments that improved the manuscript. The work of the Carnegie Supernova Project was supported by the National Science Foundation under grants AST-0306969, AST-0607438, AST-1008343, AST-1613426, AST-1613472, and AST-1613455. L.M. acknowledges support from a CONICET fellowship. L.M. and M.O. acknowledge support from UNRN PI2018 40B885 grant. M.H. acknowledges support from the Hagler Institute of Advanced Study at Texas A&M University. S.G.G. acknowledges support by FCT under Project CRISP PTDC /FISAST-31546 /2017 and Project No. UIDB /00099 /2020. M.S. is supported by grants from the VILLUM FONDEN (grant number 28021) and the Independent Research Fund Denmark (IRFD; 8021-00170B). F.F. acknowledges support from the National Agency for Research and Development (ANID) grants: BASAL Center of Mathematical Modelling AFB-170001, Ministry of Economy, Development, and Tourism's Millennium Science Initiative through grant IC12009, awarded to the Millennium Institute of Astrophysics, and FONDECYT Regular #1200710. L.G. acknowledges financial support from the Spanish Ministry of Science, Innovation and Universities (MICIU) under the 2019 Ramon y Cajal program RYC2019-027683 and from the Spanish MICIU project PID2020-115253GA-I00. P.H. acknowledges the support by National Science Foundation (NSF) grant AST-1715133. Software: corner.py (Foreman-Mackey 2016), emcee (Foreman-Mackey et al. 2013), NumPy (Oliphant 2006; Van Der Walt et al. 2011), matplotlib (Hunter 2007), MESA (Paxton et al. 2011, 2013, 2015, 2018, 2019), SciPy (Virtanen et al. 2020), Pandas (McKinney 2010), ipython/jupyter (Perez & Granger 2007).
Acknowledgements. We thank the referee for the useful comments that improved the manuscript. The work of the Carnegie Supernova Project was supported by the National Science Foundation under grants AST-0306969, AST-0607438, AST-1008343, AST-1613426, AST-1613472, and AST-1613455.

Muestra la fuente de financiamiento declarada en la publicación.