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Testing the homogeneity of type Ia Supernovae in near-infrared for accurate distance estimations
Indexado
WoS WOS:000854291300002
Scopus SCOPUS_ID:85140204984
DOI 10.1051/0004-6361/202243845
Año 2022
Tipo artículo de investigación

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras


Abstract



Since the discovery of the accelerating expansion of the Universe more than two decades ago, Type Ia Supernovae (SNe Ia) have been extensively used as standardisable candles in the optical. However, SNe Ia have shown to be more homogeneous in the near-infrared (NIR), where the effect of dust extinction is also attenuated. In this work, we explore the possibility of using a low number of NIR observations for accurate distance estimations, given the homogeneity at these wavelengths. We found that one epoch in J and/or H band, plus good gr-band coverage, gives an accurate estimation of peak magnitudes in the J (Jmax) and H (Hmax) bands. The use of a single NIR epoch only introduces an additional scatter of 0.05 mag for epochs around the time of B-band peak magnitude (Tmax). We also tested the effect of optical cadence and signal-to-noise ratio (S/N) in the estimation of Tmax and its uncertainty propagation to the NIR peak magnitudes. Both cadence and S/N have a similar contribution, where we constrained the introduced scatter of each to ≮0.02 mag in Jmax and ≮0.01 in Hmax. However, these effects are expected to be negligible, provided the data quality is comparable to that obtained for observations of nearby SNe (z2; 0.1). The effect of S/N in the NIR was tested as well. For SNe Ia at 0.08≮z2;0.1, NIR observations with better S/N than that found in the CSP sample is necessary to constrain the introduced scatter to a minimum (2;0.05 mag). These results provide confidence for our FLOWS project that is aimed at using SNe Ia with public ZTF optical light curves and few NIR epochs to map out the peculiar velocity field of the local Universe. This will allow us to determine the distribution of dark matter in our own supercluster, Laniakea, and to test the standard cosmological model by measuring the growth rate of structures, parameterised by fD, and the Hubble-Lemaitre constant, H0.

Revista



Revista ISSN
Astronomy & Astrophysics 0004-6361

Métricas Externas



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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 Müller-Bravo, Tomás E. Hombre CSIC - Instituto de Ciencias del Espacio (ICE) - España
CSIC - España
2 Frohmaier, C. Hombre CSIC - Instituto de Ciencias del Espacio (ICE) - España
Instituto de Estudios Espaciales de Cataluña - España
Inst Estudis Espacials Catalunya IEEC - España
3 Karamehmetoglu, E. Hombre Aarhus Universitet - Dinamarca
Aarhus Univ - Dinamarca
4 Stritzinger, M. D. Hombre Aarhus Universitet - Dinamarca
Aarhus Univ - Dinamarca
5 Burns, C. Hombre Observatorio Las Campanas - Estados Unidos
Carnegie Inst Sci - Estados Unidos
6 Phan, K. - Instituto de Estudios Espaciales de Cataluña - España
Aarhus Universitet - Dinamarca
Inst Estudis Espacials Catalunya IEEC - España
Aarhus Univ - Dinamarca
7 Ferres, A. Ianez - CSIC - España
CSIC - Instituto de Ciencias del Espacio (ICE) - España
7 Iáñez Ferres, A. - CSIC - Instituto de Ciencias del Espacio (ICE) - España
8 Anderson, J. P. - European Southern Observatory Santiago - Chile
9 Ashall, C. Hombre University Hawaii Institute for Astronomy - Estados Unidos
Univ Hawaii - Estados Unidos
10 Baron, E. Hombre University of Oklahoma - Estados Unidos
The George Washington University - Estados Unidos
Universität Hamburg - Alemania
UNIV OKLAHOMA - Estados Unidos
GEORGE WASHINGTON UNIV - Estados Unidos
Hamburger Sternwarte - Alemania
The University of Oklahoma - Estados Unidos
11 Hoeflich, P. Hombre Florida State University - Estados Unidos
FLORIDA STATE UNIV - Estados Unidos
College of Arts and Sciences - Estados Unidos
12 Hsiao, Eric Y. Hombre Florida State University - Estados Unidos
FLORIDA STATE UNIV - Estados Unidos
College of Arts and Sciences - Estados Unidos
13 DE JAEGER-GAILLARD, THOMAS MAXIMILIEN Hombre University Hawaii Institute for Astronomy - Estados Unidos
Univ Hawaii - Estados Unidos
14 Kumar, S. - Florida State University - Estados Unidos
15 Lu, J. - Florida State University - Estados Unidos
FLORIDA STATE UNIV - Estados Unidos
College of Arts and Sciences - Estados Unidos
16 Phillips, Mark M. Hombre Las Campanas Observatory - Chile
Observatorio Las Campanas - Chile
17 Shahbandeh, M. Mujer Florida State University - Estados Unidos
FLORIDA STATE UNIV - Estados Unidos
College of Arts and Sciences - Estados Unidos
18 Suntzeff, N. B. Hombre Texas A&M University - Estados Unidos
Texas A&M Univ - Estados Unidos
19 Uddin, S. A. Hombre Texas A&M University - Estados Unidos
American Public University System - Estados Unidos
Texas A&M Univ - Estados Unidos
Amer Publ Univ Syst - Estados Unidos

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Financiamiento



Fuente
National Science Foundation
Ministerio de Ciencia e Innovación
European Social Fund
NSF
Independent Research Fund Denmark
National Science Foundation (NSF)
VILLUM FONDEN
Agencia Estatal de Investigación
Danmarks Frie Forskningsfond
Agencia Estatal de Investigacion (AEI)
MCIN
Centro Superior de Investigaciones Cientificas (CSIC) under the PIE project
Spanish Ministerio de Ciencia e Innovacion (MCIN)
Centro Superior de Investigaciones Científicas
program Unidad de Excelencia Maria de Maeztu
Unidad de Excelencia María de Maeztu CEX2020-001058-M
European Social Fund (ESF) "Investing in your future" under the 2019 Ramon y Cajal program
Villum Experiment

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Agradecimientos



Agradecimiento
TEMB and LG acknowledge financial support from the Spanish Ministerio de Ciencia e Innovación (MCIN), the Agencia Estatal de Investigación (AEI) 10.13039/501100011033 under the PID2020-115253GA-I00 HOSTFLOWS project, and from Centro Superior de Investigaciones Científicas (CSIC) under the PIE project 20215AT016, and the I-LINK 2021 LINKA20409. TEMB and LG are also partially supported by the program Unidad de Excelencia María de Maeztu CEX2020-001058-M. LG also acknowledges MCIN, AEI and the European Social Fund (ESF) “Investing in your future” under the 2019 Ramón y Cajal program RYC2019-027683-I. The Aarhus SN group is support by a Villum Experiment grant (number 28021) from VILLUM FONDEN and a Project 1 grant (8021-00170B) from the Independent Research Fund Denmark. PH acknowledge support by the National Science Foundation (NSF) grant AST-1715133. The work of the Carnegie Supernova Project has been supported by the NSF under the grants AST0306969, AST0607438, AST1008343, AST1613426, AST1613472 and AST613455. Software: matplotlib (Hunter 2007), seaborn (Waskom et al. 2017), numpy (Harris et al. 2020), pandas (McKinney 2010), scipy (Virtanen et al. 2020), emcee (Foreman-Mackey et al. 2013), coner (Foreman-Mackey 2016), george (Ambikasaran et al. 2016), astropy (Astropy Collaboration 2013, 2018), peakutils (Negri & Vestri 2017).
TEMB and LG acknowledge financial support from the Spanish Ministerio de Ciencia e Innovacion (MCIN), the Agencia Estatal de Investigacion (AEI) 10.13039/501100011033 under the PID2020-115253GAI00 HOSTFLOWS project, and from Centro Superior de Investigaciones Cientificas (CSIC) under the PIE project 20215AT016, and the I-LINK 2021 LINKA20409. TEMB and LG are also partially supported by the program Unidad de Excelencia Maria de Maeztu CEX2020-001058-M. LG also acknowledges MCIN, AEI and the European Social Fund (ESF) "Investing in your future" under the 2019 Ramon y Cajal program RYC2019-027683-I. The Aarhus SN group is support by a Villum Experiment grant (number 28021) from VILLUM FONDEN and a Project 1 grant (8021-00170B) from the Independent Research Fund Denmark. PH acknowledge support by the National Science Foundation (NSF) grant AST-1715133. The work of the Carnegie Supernova Project has been supported by the NSF under the grants AST0306969, AST0607438, AST1008343, AST1613426, AST1613472 and AST613455. Software: matplotlib (Hunter 2007), seaborn (Waskom et al. 2017), numpy (Harris et al. 2020), pandas (McKinney 2010), scipy (Virtanen et al. 2020), emcee (Foreman-Mackey et al. 2013), coner (Foreman-Mackey 2016), george (Ambikasaran et al. 2016), astropy (Astropy Collaboration 2013, 2018), peakutils (Negri & Vestri 2017).

Muestra la fuente de financiamiento declarada en la publicación.