Repository logo
Log In

University Digital Conservancy

University Digital Conservancy

Communities & Collections
Browse
About
AboutHow to depositPolicies
Contact

Browse by Author

  1. Home
  2. Browse by Author

Browsing by Author "Myers, Dalton"

Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • Loading...
    Thumbnail Image
    Item
    Using Machine Learning to Hunt for Simulated WIMPs in the NOvA Near Detector
    (2023-11) Myers, Dalton
    A neural network was trained on simulated data that included events in which electrons were scattered by hypothetical Dark Matter particles (χ) of mass mχ = 30 MeV assuming a dark vector portal mechanism of a dark photon (A') with mass mA' = 90 MeV, a gauge coupling parameter αD = 1/2, and kinetic mixing parameter e = 2 × 10 -5. The NOvA Near Detector’s response to these events was then simulated, and the pixelmaps (images) of these events occurring within the NOvA Near Detector were then used to train a machine learning algorithm designed to differentiate between the each of the ordinary observed event types that involve an electron scattered by a neutrino and hypothetical events in which an electron was scattered by a dark matter particle.

UDC Services

  • About
  • How to Deposit
  • Policies
  • Contact

Related Services

  • University Archives
  • U of M Web Archive
  • UMedia Archive
  • Copyright Services
  • Digital Library Services

Libraries

  • Hours
  • News & Events
  • Staff Directory
  • Subject Librarians
  • Vision, Mission, & Goals
University Libraries

© 2025 Regents of the University of Minnesota. All rights reserved. The University of Minnesota is an equal opportunity educator and employer.
Policy statement | Acceptable Use of IT Resources | Report web accessibility issues