A Time-Series Statistical Analysis to model Heavy Neutral Lepton production in the day-night cycle

Abstract: Solar neutrino upscattering inside the Earth can source heavy neutral leptons (HNLs) that can reach terrestrial experiments and decay into photons within them. As HNLs are sourced through upscattering inside the Earth, the photon deposition signal will modulate daily, reaching the peak during the night and its minimum during the day; where the distance traveled by the solar neutrinos is the longest and shortest, respectively. In this project, we represent this modulation as a sine wave with amplitude that depends on the mass of the HNLs, mN , and its dipole portal interaction strength, dN . Using Poisson-distributed backgrounds and the day-night asymmetry as the observable, we simulated a Borexino-like counting experiment in the $0.3 − 0.8 \text{MeV}$ range. Using this method, we can exclude, at a $98$% CL, HNL dipole strengths of $d_n \gtrsim 10^{-9.5}$ $\text{MeV}^−1$ in the mass range of $2 − 3.2$ MeV.

This Github repository, specifically the code within the "OnOff" folder, details all the code that went into developing this project. It was primarily made in Python with packages NumPy, MatPlotLib, Pandas, and SciPy. This is a research projected conducted and contributed by Arsh Suri, Dr. Ryan Plestid, and Dr. Vedran Brdar, with thanks to the Fermilab (Fermi National Particle Accelerator).