30 August 2026 to 4 September 2026
Asia/Tokyo timezone

Legacy analysis of Milky Way dwarf spheroidal satellite galaxies: an update

Not scheduled
20m
Oral Dark matter searches (both direct and indirect)

Speaker

Antonio Circiello (Clemson university)

Description

Dwarf spheroidal satellite galaxies (dSphs) of the Milky Way are targets of great interest for searches of Dark Matter (DM) signatures with the Fermi-LAT. In the last decade the number of detected and putative dSphs has been rapidly increasing, allowing for some of the most stringent constraints to be put on models of annihilating DM in the GeV-TeV range. The most recent results even highlight the presence of local significance excesses at the 2-3 sigma level.
With the recent observations of ultra-faint compact stellar systems (UFCSs), that might be the darkest galaxies ever observed, and the predictions on the upcoming results of the Legacy Survey of Space and Time (LSST), which poses to double or more the sample of known dSphs over the next decade, we stand before a fundamental moment for gamma-ray searches of DM signatures.
In this work, we apply key improvements to the analysis of the dSphs. We use stricter cuts on the data, implement a method to adaptively model the background, and assume an updated framework for DM annihilation. We find that our improved background modeling leads to a better agreement between the model and the data. This produces an increase in the local and global significance of the dSphs excess compared to previous studies. Finally, we find that the DM properties obtained in this work are less dependent on the sample of dSphs being considered, while remaining in agreement with the predictions from the Galactic center excess observed by theFermi- LAT and the antiproton excess observed by the Alpha Magnetic Spectriometer (AMS-02).

Primary author

Antonio Circiello (Clemson university)

Co-authors

Dr Alex Drlica-Wagner (University of Chicago) Dr Chris Karwin (Clemson University) Marco Ajello (Clemson University) Mattia Di Mauro (INFN Turin) Dr Miguel Sánchez-Conde (Universidad Autonoma de Madrid)

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