83 citations · 258 across the 30 of their papers we have counts for
15 papers · 1 filter
A Simulation Based Inference Approach to Modelling of Type Ia Supernova Populations
B. Popovic, M. Grayling, M. O'Callaghan +10
Type Ia Supernovae (SNe Ia) are prominent cosmological probes, utilising a standardisation process to reduce their observed scatter to mag. A growing number of models se…
BayeSN Dovekie: Joint Photometric Cross-calibration and SED Modelling of Type Ia Supernovae
M. Grayling, B. Popovic, M. Ginolin +2
We present a new framework for BayeSN, the hierarchical Bayesian SED model for type Ia supernovae (SNe Ia), incorporating cross-calibration of samples observed across heterogeneous…
On the origin of the environmental dependence of SN Ia magnitudes: A BayeSN view of the ZTF SN Ia DR2
Madeleine Ginolin, Matthew Grayling, Kaisey S. Mandel +5
Astrophysical variabilities of Type Ia supernovae (SNe Ia), such as their link with their birth environment, are now one of the leading sources of systematic uncertainties on the m…
FlowSN: Neural Simulation-Based Inference under Realistic Selection Effects applied to Supernova Cosmology
Benjamin M. Boyd, Kaisey S. Mandel, Matthew Grayling +10
We present FlowSN, a statistical framework using simulation-based inference (SBI) with normalising flows to account for selection effects in observational astronomy. Failure to acc…
A Fully Photometric Approach to Type Ia Supernova Cosmology in the LSST Era: Host Galaxy Redshifts and Supernova Classification
Ayan Mitra, Richard Kessler, Rebecca C. Chen +9
The upcoming Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) is expected to discover nearly a million Type Ia supernovae (SNeIa), offering an unprecedented oppor…
BayeSN-TD: Time Delay and Estimation for Lensed SN H0pe
M. Grayling, S. Thorp, K. S. Mandel +6
We present BayeSN-TD, an enhanced implementation of the probabilistic type Ia supernova (SN Ia) BayeSN SED model, designed for fitting multiply-imaged, gravitationally lensed type…
Testing Lens Models of PLCK G165.7+67.0 Using Lensed SN H0pe
Aadya Agrawal, J. D. R. Pierel, Gautham Narayan +9
Supernova H0pe is a multiply-imaged Type Ia supernova (SN~Ia) and the second lensed SN to yield a measurement of the Hubble constant by the time-delay cosmography method, finding $…
A Reassessment of the Pantheon+ and DES 5YR Calibration Uncertainties: Dovekie
B. Popovic, W. D. Kenworthy, M. Ginolin +21
Type Ia Supernovae (SNe Ia) are crucial tools to measure the accelerating expansion of the universe, comprising thousands of SNe across multiple telescopes. Accurate measurements o…
Characterising the Standardisation Properties of Type Ia Supernovae in the z band with Hierarchical Bayesian Modelling
Erin E. Hayes, Suhail Dhawan, Kaisey S. Mandel +21
Type Ia supernovae (SNe Ia) are standardisable candles: their peak magnitudes can be corrected for correlations between light curve properties and their luminosities to precisely e…
Accounting for Selection Effects in Supernova Cosmology with Simulation-Based Inference and Hierarchical Bayesian Modelling
Benjamin M. Boyd, Matthew Grayling, Stephen Thorp +1
Type Ia supernovae (SNe Ia) are thermonuclear exploding stars that can be used to put constraints on the nature of our universe. One challenge with population analyses of SNe Ia is…
JWST Photometric Time-Delay and Magnification Measurements for the Triply-Imaged Type Ia "Supernova H0pe" at z = 1.78
J. D. R. Pierel, B. L. Frye, M. Pascale +60
Supernova (SN) H0pe is a gravitationally lensed, triply-imaged, Type Ia SN (SN Ia) discovered in James Webb Space Telescope imaging of the PLCK G165.7+67.0 cluster of galaxies. Wel…
SIDE-real: Supernova Ia Dust Extinction with truncated marginal neural ratio estimation applied to real data
Konstantin Karchev, Matthew Grayling, Benjamin M. Boyd +3
We present the first fully simulation-based hierarchical analysis of the light curves of a population of low-redshift type Ia supernovae (SNae Ia). Our hardware-accelerated forward…
Scalable hierarchical BayeSN inference: Investigating dependence of SN Ia host galaxy dust properties on stellar mass and redshift
Matthew Grayling, Stephen Thorp, Kaisey S. Mandel +5
We apply the hierarchical probabilistic SED model BayeSN to analyse a sample of 475 SNe Ia (0.015 < z < 0.4) from Foundation, DES3YR and PS1MD to investigate the properties of dust…
GausSN: Bayesian Time-Delay Estimation for Strongly Lensed Supernovae
Erin E. Hayes, Stephen Thorp, Kaisey S. Mandel +3
We present GausSN, a Bayesian semi-parametric Gaussian Process (GP) model for time-delay estimation with resolved systems of gravitationally lensed supernovae (glSNe). GausSN model…
The Effect of Environment on Type Ia Supernovae in the Dark Energy Survey Three-Year Cosmological Sample
L. Kelsey, M. Sullivan, M. Smith +73
Analyses of type Ia supernovae (SNe Ia) have found puzzling correlations between their standardised luminosities and host galaxy properties: SNe Ia in high-mass, passive hosts appe…