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SNEMO: Improved Empirical Models for Type Ia Supernovae
C. Saunders, G. Aldering, P. Antilogus +39
Type Ia supernova cosmology depends on the ability to fit and standardize observations of supernova magnitudes with an empirical model. We present here a series of new models of Ty…
Photometric redshifts from SDSS images using a Convolutional Neural Network
Johanna Pasquet, Emmanuel Bertin, Marie Treyer +2
We developed a Deep Convolutional Neural Network (CNN), used as a classifier, to estimate photometric redshifts and associated probability distribution functions (PDF) for galaxies…
Strong Dependence of Type Ia Supernova Standardization on the Local Specific Star Formation Rate
M. Rigault, V. Brinnel, G. Aldering +40
As part of an on-going effort to identify, understand and correct for astrophysics biases in the standardization of Type Ia supernovae (SNIa) for cosmology, we have statistically c…
Correcting for peculiar velocities of Type Ia Supernovae in clusters of galaxies
P. -F. Léget, M. V. Pruzhinskaya, A. Ciulli +43
Type Ia Supernovae (SNe Ia) are widely used to measure the expansion of the Universe. To perform such measurements the luminosity and cosmological redshift () of the SNe Ia have…
Understanding Type Ia supernovae through their U-band spectra
J. Nordin, G. Aldering, P. Antilogus +39
Context. Observations of Type Ia supernovae (SNe Ia) can be used to derive accurate cosmological distances through empirical standardization techniques. Despite this success neithe…