MomentsML
Machine Learning shallow network accurate prediction of shear estimators for The Euclid Satellite
MomentsML is a machine learning method designed to provide accurate shear estimates. It involves training a shallow neural network using realistic simulations with known shear values, to recover the shear signal. This is a challenging process given the multiple sources of noise and biases, such as PSF errors, blending of galaxies, detector effects, low signal-to-noise ratios, galaxy morphologies, and others.
The Euclid Satellite, which aims to study the dark exotic components of the universe and reveal insights about cosmological tensions, uses MomentsML as one of its three independent shear measurement methods.