Speaker
Description
The Eos experiment is a 4-tonne monolithic optical detector operating at University of California, Berkeley campus. Eos serves as a testbed for next generation detector technologies for neutrino experiments. Eos has taken data with a suite of calibration sources in multiple target media. The collaboration is now exploring the detector's use case beyond a testbed.
We propose deployment of the Eos detector at the Spallation Neutron Source (SNS), Eos@SNS, at Oak Ridge National Laboratory. Neutrinos at the SNS have been observed by multiple experiments, producing new physics results. Eos is well suited for measuring multiple neutrino-nucleus cross sections include CC and NC scattering on Oxygen and Carbon, as well as searches for Beyond Standard Model physics. This work describes the use of machine learning techniques to reduce the backgrounds of concern, primarily those coming from cosmic-ray muons and the SNS beam-related neutrons. This work will inform the deployment strategy of Eos@SNS and the choice of target materials.