Neutral Current Neutrino Interactions at FASER$\nu$

TL;DR

FASERν can detect and analyze high-energy neutrino neutral current interactions using deep neural networks, enabling the measurement of cross sections and probing non-standard neutrino interactions at TeV energies.

Contribution

This work demonstrates the feasibility of measuring neutrino neutral current cross sections at TeV energies using neural network techniques to discriminate signals from backgrounds.

Findings

Deep neural networks effectively distinguish neutrino neutral current events.

Neutrino energies from 100 GeV to several TeV can be analyzed.

Potential to probe non-standard neutrino interactions.

Abstract

In detecting neutrinos from the Large Hadron Collider, FASER$\nu$ will record the most energetic laboratory neutrinos ever studied. While charged current neutrino scattering events can be cleanly identified by an energetic lepton exiting the interaction vertex, neutral current interactions are more difficult to detect. We explore the potential of FASER$\nu$ to observe neutrino neutral current scattering $\nu N \to \nu N$, demonstrating techniques to discriminate neutrino scattering events from neutral hadron backgrounds as well as to estimate the incoming neutrino energy given the deep inelastic scattering final state. We find that deep neural networks trained on kinematic observables allow for the measurement of the neutral current scattering cross section over neutrino energies from 100 GeV to several TeV. Such a measurement can be interpreted as a probe of neutrino non-standard interactions that is complementary to limits from other tests such as oscillations and coherent neutrino-nucleus scattering.