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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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.
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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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Testing $\Lambda$CDM versus dynamical dark energy in one year: A DESI spectroscopic follow-up program for Rubin supernovae
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.