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Learning to find weird particles

Tuesday 13 May 2025, 15:00 → 16:00 US/Central

WH11NE(Sunrise)

WH11NE(Sunrise)

65029048274

Please login if you have a cern account or email lpc-tw@fnal.gov to obtain the password to this meeting

Ka Hei Martin Kwok

Marguerite Belt Tonjes, Keith Ulmer, Luigi Marchese, Gabriele Benelli

- 15:00 → 16:00
  
  Learning to find weird particles 1h
  
  Finding the tracks that particles make through detectors is a critical component of identifying new physics and phenomena, but is very a challenging combinatorial problem. Traditionally, track finding codes assume that tracks must be helical, which simplifies the task but also restricts power to discover new physics which might produce non-helical tracks, effectively ignoring some potentially striking signatures. However, recent advances in ML-based tracking allow for new inroads into previously inaccessible territory, such as efficient reconstruction of tracks that do not follow helical trajectories. I will present a demonstration of training a network to reconstruct a particular type of non-helical tracks, quirks, and discuss the potential to generalize ML tracking to a wider class of non-helical tracks, enabling a search for overlooked anomalous tracks. I’ll end by talking briefly about my experience in science communication.
  
  Speaker: Daniel Whiteson (University of California Irvine (US))
  
  TOTW_DanielWhiteson.mp4