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New neutrino experiments can detect millicharged particles (MCPs). LSND and MiniBooNE offer leading constraints on MCP masses, with future experiments like DUNE and SHIP probing even wider mass ranges.

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Area of Science:

  • Particle Physics
  • Cosmology
  • Experimental Physics

Background:

  • Millicharged particles (MCPs) are hypothetical particles with fractional electric charge.
  • Neutrino experiments offer unique opportunities to search for new physics beyond the Standard Model.
  • Existing constraints on MCPs come from various sources, including accelerator and astrophysical observations.

Purpose of the Study:

  • To set constraints on millicharged particles (MCPs) using existing neutrino experiment data.
  • To project the sensitivity of future neutrino experiments to MCPs.
  • To explore the potential of MCP searches in particle physics.

Main Methods:

  • Analysis of electron scattering data from MiniBooNE and Liquid Scintillator Neutrino Detector (LSND) experiments.
  • Development of sensitivity projections for the Fermilab Short-Baseline Neutrino (SBN) program, Deep Underground Neutrino Experiment (DUNE), and Search for Hidden Particles (SHIP) experiment.
  • Comparison of projected MCP reach with existing bounds from collider searches and other experiments.

Main Results:

  • LSND provides leading constraints on MCPs in the 5-35 MeV mass window.
  • MiniBooNE offers leading constraints on MCPs in the 100-180 MeV mass window.
  • The SBN program (SBND and MicroBooNE) can set leading bounds for MCPs between 100-300 MeV.
  • DUNE and SHIP have the potential to probe MCP parameter space from 5 MeV to 5 GeV, significantly extending current reach.

Conclusions:

  • Neutrino experiments, particularly MiniBooNE and LSND, are powerful tools for constraining MCP properties.
  • Future experiments like DUNE and SHIP will dramatically expand the parameter space accessible for MCP searches.
  • These findings highlight the importance of neutrino experiments in the search for novel particles and physics beyond the Standard Model.