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UID:UW-Physics-Event-7795
DTSTART:20220518T160000Z
DTEND:20220518T171500Z
DTSTAMP:20260414T113232Z
LAST-MODIFIED:20220712T130931Z
LOCATION:Online Seminar: Please sign up for our mailing list at www.ph
 ysicsmeetsml.org for zoom link
SUMMARY:Simulation-based inference for astrophysical dark matter searc
 hes\, Physics ∩ ML Seminar\, Siddharth Mishra-Sharma\, MIT
DESCRIPTION:In this talk\, I will motivate the use of simulation-based
  machine learning methods for new physics searches\, in particular for
  understanding the nature of dark matter\, using astrophysical observa
 tions. After showcasing several applications and discussing advantages
  as well as caveats against traditional techniques\, I will spend the 
 bulk of the talk describing a study of gamma-ray data from the center 
 of the Milky Way where the goal is to characterize a potential signal 
 of dark matter – the so-called Galactic Center Excess. While emphasi
 zing the modeling and inference challenges associated with this task\,
  I will discuss how leveraging machine learning methods offers a path 
 towards resolving the long-standing puzzle of the origin of the signal
 .
URL:https://www.physics.wisc.edu/events/?id=7795
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