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SUMMARY:Lina Necib (MIT)
DTSTART:20230905T183000Z
DTEND:20230905T193000Z
DTSTAMP:20260423T024509Z
UID:nhetc/79
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/nhetc/79/">(
 Machine) Learning of Dark Matter</a>\nby Lina Necib (MIT) as part of NHETC
  Seminar\n\n\nAbstract\nIn this talk\, I explore the impact of stellar kin
 ematics on understanding the particle nature of Dark Matter\, overviewing 
 the correlations between stellar and Dark Matter phase space distributions
  in three separate locations: the solar neighborhood\, the Galactic center
 \, and dwarf galaxies. I will focus on the use of machine learning techniq
 ues applied to data from the Gaia mission to disentangle the local kinemat
 ics substructures\, and the use of simulations to study the correlations b
 etween stars and Dark Matter. I will end by relating these empirical measu
 rements to Dark Matter detection experiments.\n
LOCATION:https://researchseminars.org/talk/nhetc/79/
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