Measurement of galaxy redshifts from multi-band photometric data with machine learning
Poursuite possible en thèse
This stage has as goal to measure photometric redshifts of galaxies from the multi-band UNIONS survey.
The student will apply state-of-the-art machine learning techniques including deep learning, to obtain precise photometric redshifts and error estimates. Those photometric redshifts represent a crucial ingredient for the cosmological analysis of the UNIONS survey.
Sujet détaillé/Full description
Image processing, photometry, machine learning