Using rest-frame optical and NIR data from the RAISIN survey to explore the redshift evolution of dust laws in SN Ia host galaxies

Author:

Thorp Stephen12ORCID,Mandel Kaisey S23ORCID,Jones David O4,Kirshner Robert P56,Challis Peter M7

Affiliation:

1. The Oskar Klein Centre, Department of Physics, Stockholm University , AlbaNova University Centre, SE-106 91 Stockholm , Sweden

2. Institute of Astronomy and Kavli Institute for Cosmology , Madingley Road, Cambridge CB3 0HA , UK

3. Statistical Laboratory, DPMMS, University of Cambridge , Wilberforce Road, Cambridge CB3 0WB , UK

4. Institute for Astronomy, University of Hawai’i , 640 N. A’ohoku Pl., Hilo, HI 96720 , USA

5. TMT International Observatory , 100 West Walnut Street, Pasadena, CA 91124 , USA

6. California Institute of Technology , 1200 East California Boulevard, Pasadena, CA 91125 , USA

7. Harvard – Smithsonian Center for Astrophysics , 60 Garden Street, Cambridge, MA 02138 , USA

Abstract

ABSTRACT We use rest-frame optical and near-infrared (NIR) observations of 42 Type Ia supernovae (SNe Ia) from the Carnegie Supernova Project at low-z and 37 from the RAISIN (SNIA in the IR) Survey at high-z to investigate correlations between SN Ia host galaxy dust, host mass, and redshift. This is the first time the SN Ia host galaxy dust extinction law at high-z has been estimated using combined optical and rest-frame NIR data (YJ band). We use the BayeSN hierarchical model to leverage the data’s wide rest-frame wavelength range (extending to ∼1.0–1.2 μm for the RAISIN sample at 0.2 ≲ z ≲ 0.6). By contrasting the RAISIN and Carnegie Supernova Project (CSP) data, we constrain the population distributions of the host dust RV parameter for both redshift ranges. We place a limit on the difference in population mean RV between RAISIN and CSP of −1.16 < Δμ(RV) < 1.38 with 95 per cent posterior probability. For RAISIN we estimate μ(RV) = 2.58 ± 0.57, and constrain the population standard deviation to σ(RV) < 0.90 [2.42] at the 68 [95] per cent level. Given that we are only able to constrain the size of the low- to high-z shift in μ(RV) to ≲1.4 – which could still propagate to a substantial bias in the equation-of-state parameter w – these and other recent results motivate continued effort to obtain rest-frame NIR data at low- and high-redshifts (e.g. using the Roman Space Telescope).

Funder

Science and Technology Facilities Council

European Research Council

National Center for Supercomputing Applications

University of Illinois at Urbana-Champaign

Publisher

Oxford University Press (OUP)

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