Journal-club Doctorants / Journal-club PhD students
|« Catalog-free modeling of galaxy types in deep images: Massive dimensional reduction with neural networks »|
Understanding how the galaxy have evolved over time is a key to write the
history of the Universe.
We observe a large variety of galaxies with different colors, shapes and
sizes. Each population of galaxy (elliptical, spiral, ...) have evolved
differently and the density of each population has changed with redshift.
During this presentation, I will introduce a new method to study them by
fitting a neural network. This method does not require catalogs nor binning to
study the panchromatic deep fields images.
I will present the 'luminosity functions' tool to model the density of
galaxies per magnitude and per volume of the Universe.
I will also show the recent results we obtained in constraining the density of
the elliptical and spiral populations using the Canada-France-Hawaii Telescope
vendredi 26 février 2021 - 16:00
Webinaire, Institut d'Astrophysique
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