The host galaxies of type Ia supernovae and the future of spectroscopic Type Ia cosmology

  • Elizabeth Samantha Swann

Student thesis: Doctoral Thesis


This Thesis investigates how Type Ia supernova intrinsic luminosity dispersion depends on the local environment of the explosion, traced using global host galaxy properties. Our sample of Type Ia supernovae (SN Ia) is from the 5 year Dark Energy Survey and the Australian Dark Energy Survey (DES/OzDES). SN Ia are powerful cosmological probes; understanding how their intrinsic luminosities (which one relies on to calculate cosmological distances) and their light curve parameters may be affected by their environments could provide insight into the systematic errors which currently dominate in SN Ia cosmology.

We select a sample of 1296 likely Type Ia SNe classified by the software SNNova Möller & de Boissière (2020), which have cosmologically useful light curve properties and good quality host galaxy spectra from OzDES. We determine the host galaxy properties for each galaxy in our sample of spectra, using strong emission line calibrations.

We derive the star formation rates using Hα and [Oii] diagnostics for 924 galaxies (with the remaining 372 galaxies being designated a SFR=0) and measure the gas-phase metallicities for a sub-sample comprising 250 of our galaxies. We also measure the stellar mass for each galaxy using photometric techniques. We calculate cosmological distances and Hubble residuals for our sample of SNe Ia using 1D and 5D bias corrections from snana (Kessler et al., 2009) and bbc (Kessler & Scolnic, 2017).
We confirm a relationship exists between SN Ia light-curve width (stretch) and host galaxy environment, finding that high-stretch (brighter) SNe Ia are hosted by highly star-forming, low mass galaxies, high metallicity galaxies.
We have shown that a mixture of both host galaxy dust and progenitor age are likely the cause of the luminosity dispersion in Type Ia supernova. We find that SN Ia hosted in the extremes of host galaxy populations (starburst or passive) are better standardisable candles than those formed in complex, mixed stellar population, star forming environments, with lower values of intrinsic luminosity dispersion and less dispersion present in the rms of their Hubble residuals.
In future SNe Ia cosmological analysis, We recommend selecting SNe Ia from the extremes of galaxy types, removing any SNe Ia which have host galaxies that fall into the category −12 < log(sSFR/MΘyr−1 ) < −9.5, where the effects of extinction and difficult to disentangle. We also recommend both a 2-value β correction dependent on host galaxy type, and two separate sets of bias corrections (on each sample) which depend on the host galaxy characteristics including dust and likely population age. We also emphasise the need to better model the dependence of SN Ia light curves on host galaxy properties to perform accurate bias corrections on a large sample of SN Ia. The study and classification of SN Ia environment using similar techniques to those presented here, will become as important a part of determining future cosmological constraints as measuring the light-curves of the SNe Ia themselves.
We also perform large-scale simulations of the upcoming Time Domain Extragalactic Survey (TiDES), which is focused on obtaining spectra of live transients detected by the Vera Rubin Observatory (VRO) and their host galaxies. We determine that the TiDES survey will produce a sample of over 15,000 spectroscopically confirmed Type Ia supernovae and over 50,000 photometrically classified Type Ia supernova with host galaxy redshifts. We conclude that TiDES will be able to create a Hubble Diagram of ≈ 60,000 high-redshift cosmologically-useful SNe Ia and determine w to <2%. This will be the largest survey of its kind ever conducted. Such simulations are not only vital to survey planning and optimising survey strategy, but will be vital in understanding our selection effects in future studies. 
Date of AwardSept 2020
Original languageEnglish
Awarding Institution
  • University of Portsmouth
SupervisorRobert Nichol (Supervisor) & Thomas Collett (Supervisor)

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