The stellar halo of our Galaxy is mostly formed by stars that were initially residing in dwarf galaxies and globular clusters, which have been disrupted by the tidal field of the Milky Way. Because the structures created by these disruptions can survive for a long time, the stellar halo is the best place to probe the accretion history of our Galaxy.
I will present recent work that in particular makes use of the new deep u-band component of the Canada-France-Imaging Survey (CFIS), in combination with other surveys, such as Pan-STARRS 1 and Gaia. With these observations, it have been possible to study the stellar halo using different type of stars, such as the Blue Horizontal Branch stars (BHBs) or White Dwarfs (WDs). We have recently developed a machine-learning-based algorithm that disentangles the giants from the dwarfs, and that derives their distances and metallicities with high precision, using only the available photometry. This new dataset will be extremely valuable for future studies of the stellar halo of the Milky Way, using different stellar populations, in order to reconstruct the formation history of our Galaxy and probe the dark-matter distribution that surrounds it.
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2019-11-25T15:00:002019-11-25T16:00:00Unveiling the stellar halo distribution with multi-wavelength photometryEvent Information:
The stellar halo of our Galaxy is mostly formed by stars that were initially residing in dwarf galaxies and globular clusters, which have been disrupted by the tidal field of the Milky Way. Because the structures created by these disruptions can survive for a long time, the stellar halo is the best place to probe the accretion history of our Galaxy.
I will present recent work that in particular makes use of the new deep u-band component of the Canada-France-Imaging Survey (CFIS), in combination with other surveys, such as Pan-STARRS 1 and Gaia. With these observations, it have been possible to study the stellar halo using different type of stars, such as the Blue Horizontal Branch stars (BHBs) or White Dwarfs (WDs). We have recently developed a machine-learning-based algorithm that disentangles the giants from the dwarfs, and that derives their distances and metallicities with high precision, using only the available photometry. This new dataset will be extremely valuable for future studies of the stellar halo of the Milky Way, using different stellar populations, in order to reconstruct the formation history of our Galaxy and probe the dark-matter distribution that surrounds it.Event Location:
Hennings 318