A simulation-based inference framework that jointly models type Ia supernovae brightness dependences, host galaxy evolution, and cosmology from photometric observations.
Publications of the Astronomical Society of the Pacific 131:094501
10 Pith papers cite this work. Polarity classification is still indexing.
10
Pith papers citing it
representative citing papers
Photometry-only classification of SNe Ia and Ibc reaches >=90% accuracy by fitting a semi-analytical decay model to light curves and using GMMs on the resulting parameter distributions to estimate mixing fractions without any labeled training data.
SCAT DR1 delivers 1810 spectra of 1330 transients with classifications, fitted light curves, new redshifts for many host galaxies, and host properties as a testbed for photometric classification pipelines.
A cross-entropy metric is introduced to distinguish transient populations and support novelty detection for LSST observing strategy optimization.
Pantheon+ delivers tighter SN Ia constraints on Ω_M, w0, wa, and H0 from 1550 events, consistent with a cosmological constant, with SN systematics contributing less than one third to H0 uncertainty.
The Via Project is a planned five-year dual-hemisphere spectroscopic survey targeting over 2 million stars with 100 m/s RV stability and transient spectroscopy to r~24 using instruments on MMT and Magellan/Clay telescopes starting in 2027.
BayeSN analysis of ZTF Type Ia supernovae confirms a ~0.1 mag intrinsic environmental step in standardized brightness that is not explained by differences in dust extinction properties.
Calibration uncertainties during supernova light-curve fitting cause roughly 50% degradation in dark energy figure of merit for Stage IV surveys, dominating over 13% degradation from model training errors and showing near-degeneracy with cosmology.
A coordinated Rubin-DESI supernova survey could distinguish dynamical dark energy from Lambda CDM at over 5 sigma in one year using 2300 spectroscopically confirmed SNe Ia at low redshift.
LightCurveLynx is a flexible forward-modeling tool that produces supernova light-curve simulations matching ZTF observations with low KL divergence and consistent completeness limits.
citing papers explorer
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Photometry is all you need: supernova classification as a mixing problem
Photometry-only classification of SNe Ia and Ibc reaches >=90% accuracy by fitting a semi-analytical decay model to light curves and using GMMs on the resulting parameter distributions to estimate mixing fractions without any labeled training data.
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Calibration-Induced Systematics in SALT3 Training and Their Impact on Dark Energy Constraints from Stage IV Supernova Surveys
Calibration uncertainties during supernova light-curve fitting cause roughly 50% degradation in dark energy figure of merit for Stage IV surveys, dominating over 13% degradation from model training errors and showing near-degeneracy with cosmology.