Orateur
Description
We present the Lemaitre project, an independent effort to measure the Dark
Energy equation of state (w,wa) using (1) a new set of type Ia supernovae (SNe
Ia) from the ZTF, SNLS (years 4 and 5), and Subaru/HSC surveys, covering the
redshift range 0.02 < z < 1.3, (2) a completely new cosmology inference
pipeline. The Lemaitre effort aims to address the tension between recent (w,wa)
measurements and LCDM predictions.
In this talk, we provide an overview of the Lemaitre project, starting with the
dataset. We
present a general overview of the dataset, we discuss the surveys, data
selection criteria and the calibration chain.
Constraining the Dark Energy equation of state with SNe Ia requires precise
measurements of SN Ia standardized luminosity distances. To derive these
distances the inference chain relies on an empirical spectrophotometric model of
SNe~Ia, trained on the dataset used for the Hubble diagram. In this talk, we
present a key component of the Lemaitre inference chain: a new framework for
training empirical spectrophotometric models called 'NaCl' (Nouveaux Algorithmes
de Courbes de Lumière). This framework is able to efficiently train a model
while propagating all known sources of errors and systematics (measurement- and
calibration- but also modeling-uncertainties) in the training, enhancing the
accuracy of the lightcurve parameters used in the cosmological analysis.
We present results of trainings performed using NaCl on realistic simulations of
the LEMAITRE dataset. We show that NaCl can accurately describe SN Ia
lightcurves and spectra, providing a robust framework for the LEMAITRE
analysis.
