Think Global, Act Local: The Influence of Environment Age and Host Mass on Type Ia Supernova Light Curves

Rose, Benjamin; Garnavich, P.; Berg, Michelle A.

doi:10.3847/1538-4357/ab0704

Cited by 76 publications

(93 citation statements)

References 88 publications

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“…Jones et al (2018a) investigated the stellar masses and u − g colors within 1.5 kpc of SN Ia explosion sites, finding evidence for a local mass step, but they could not definitively say that local properties are better correlated with SN Ia HRs than global properties or random information. Rose et al (2019) found a correlation between HR and global host-galaxy age, but did not see evidence for a stronger local effect.…”

Section: Introductionmentioning

confidence: 73%

A possible distance bias for type Ia supernovae with different ejecta velocities

Siebert

Foley

Jones

et al. 2020

Monthly Notices of the Royal Astronomical Society

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After correcting for their light-curve shape and color, Type Ia supernovae (SNe Ia) are precise cosmological distance indicators. However, there remains a non-zero intrinsic scatter in the differences between measured distance and that inferred from a cosmological model (i.e., Hubble residuals or HRs), indicating that SN Ia distances can potentially be further improved. We use the open-source relational database kaepora to generate composite spectra with desired average properties of phase, light-curve shape, and HR. At many phases, the composite spectra from two subsamples with positive and negative average HRs are significantly different. In particular, in all spectra from 9 days before to 15 days after peak brightness, we find that SNe with negative HRs have, on average, higher ejecta velocities (as seen in nearly every optical spectral feature) than SNe with positive HRs. At +4 days relative to B-band maximum, using a sample of 62 SNe Ia, we measure a 0.091 ± 0.035 mag (2.7σ) HR step between SNe with Si ii λ6355 line velocities (v Si ii ) higher/lower than −11,000 km s −1 (the median velocity). After light-curve shape and color correction, SNe with higher velocities tend to have underestimated distance moduli relative to a cosmological model. The intrinsic scatter in our sample reduces from 0.094 mag to 0.082 mag after making this correction. Using the Si ii λ6355 velocity evolution of 115 SNe Ia, we estimate that a velocity difference >500 km s −1 exists at each epoch between the positive-HR and negative-HR samples with 99.4% confidence. Finally at epochs later than +37 days, we observe that negative-HR composite spectra tend to have weaker spectral features in comparison to positive-HR composite spectra.

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Section: Introductionmentioning

confidence: 73%

A possible distance bias for type Ia supernovae with different ejecta velocities

Siebert

Foley

Jones

et al. 2020

Monthly Notices of the Royal Astronomical Society

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“…Kelly et al 2010;Lampeitl et al 2010;Sullivan et al 2010;Conley et al 2011;Childress, Wolf & Zahid 2014). Understanding the driver behind, and correcting for, the mass step is the focus of significant ongoing work (Jones et al 2018;Rigault et al 2018;Roman et al 2018;Rose, Garnavich & Berg 2019;Smith et al 2020; Kelsey in preparation), all of which requires accurate and precise galaxy photometry.…”

Section: Introductionmentioning

confidence: 99%

Supernova host galaxies in the dark energy survey: I. Deep coadds, photometry, and stellar masses

Wiseman¹,

Smith²,

Childress³

et al. 2020

Monthly Notices of the Royal Astronomical Society

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The 5-yr Dark Energy Survey Supernova Programme (DES-SN) is one of the largest and deepest transient surveys to date in terms of volume and number of supernovae. Identifying and characterizing the host galaxies of transients plays a key role in their classification, the study of their formation mechanisms, and the cosmological analyses. To derive accurate host galaxy properties, we create depth-optimized coadds using single-epoch DES-SN images that are selected based on sky and atmospheric conditions. For each of the five DES-SN seasons, a separate coadd is made from the other four seasons such that each SN has a corresponding deep coadd with no contaminating SN emission. The coadds reach limiting magnitudes of order ∼27 in g band, and have a much smaller magnitude uncertainty than the previous DES-SN host templates, particularly for faint objects. We present the resulting multiband photometry of host galaxies for samples of spectroscopically confirmed type Ia (SNe Ia), core-collapse (CCSNe), and superluminous (SLSNe) as well as rapidly evolving transients (RETs) discovered by DES-SN. We derive host galaxy stellar masses and probabilistically compare stellar-mass distributions to samples from other surveys. We find that the DES spectroscopically confirmed sample of SNe Ia selects preferentially fewer high-mass hosts at high-redshift compared to other surveys, while at low redshift the distributions are consistent. DES CCSNe and SLSNe hosts are similar to other samples, while RET hosts are unlike the hosts of any other transients, although these differences have not been disentangled from selection effects.

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“…Please note that the estimate of H 0 obtained with the inverse distance ladder technique [20], where a standard pre-recombination physics is assumed and BAO data are used, is also consistent with the value obtained with CMB data alone. Many studies have been dedicated to solve the tension between late-and early-time estimates of H 0 both from a theoretical [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39] and observational [10,16,[40][41][42][43][44] point of view.…”

Section: Introductionmentioning

confidence: 99%

CMB Tensions with Low-Redshift H0 and S8 Measurements: Impact of a Redshift-Dependent Type-Ia Supernovae Intrinsic Luminosity

Martinelli

Tutusaus

2019

Symmetry

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With the recent increase in precision of our cosmological datasets, measurements of ΛCDM model parameter provided by high-and low-redshift observations started to be in tension, i.e., the obtained values of such parameters were shown to be significantly different in a statistical sense. In this work we tackle the tension on the value of the Hubble parameter, H 0 , and the weighted amplitude of matter fluctuations, S 8 , obtained from local or low-redshift measurements and from cosmic microwave background (CMB) observations. We combine the main approaches previously used in the literature by extending the cosmological model and accounting for extra systematic uncertainties. With such analysis we aim at exploring non standard cosmological models, implying deviation from a cosmological constant driven acceleration of the Universe expansion, in the presence of additional uncertainties in measurements. In more detail, we reconstruct the Dark Energy equation of state as a function of redshift, while we study the impact of type-Ia supernovae (SNIa) redshift-dependent astrophysical systematic effects on these tensions. We consider a SNIa intrinsic luminosity dependence on redshift due to the star formation rate in its environment, or the metallicity of the progenitor. We find that the H 0 and S 8 tensions can be significantly alleviated, or even removed, if we account for varying Dark Energy for SNIa and CMB data. However, the tensions remain when we add baryon acoustic oscillations (BAO) data into the analysis, even after the addition of extra SNIa systematic uncertainties. This points towards the need of either new physics beyond late-time Dark Energy, or other unaccounted systematic effects (particulary in BAO measurements), to fully solve the present tensions.

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Think Global, Act Local: The Influence of Environment Age and Host Mass on Type Ia Supernova Light Curves

Cited by 76 publications

References 88 publications

A possible distance bias for type Ia supernovae with different ejecta velocities

A possible distance bias for type Ia supernovae with different ejecta velocities

Supernova host galaxies in the dark energy survey: I. Deep coadds, photometry, and stellar masses

CMB Tensions with Low-Redshift H0 and S8 Measurements: Impact of a Redshift-Dependent Type-Ia Supernovae Intrinsic Luminosity

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