Viterbi Decoding of CRES Signals in Project 8

Abstract

Cyclotron Radiation Emission Spectroscopy (CRES) is a modern approach for determining charged particle energies via high-precision frequency measurements of the emitted cyclotron radiation. For CRES experiments with gas within the fiducial volume, signal and noise dynamics can be modelled by a hidden Markov model. We introduce a novel application of the Viterbi algorithm in order to derive informational limits on the optimal detection of cyclotron radiation signals in this class of gas-filled CRES experiments, thereby providing concrete limits from which future reconstruction algorithms, as well as detector designs, can be constrained. The validity of the resultant decision rules is confirmed using both Monte Carlo and Project 8 data.

13 pages, 5 figures

References in corpus (5)

• Determining the neutrino mass with Cyclotron Radiation Emission Spectroscopy - Project 8
• Single electron detection and spectroscopy via relativistic cyclotron radiation
• Electron Radiated Power in Cyclotron Radiation Emission Spectroscopy Experiments
• Bayesian Analysis of a Future Beta Decay Experiment's Sensitivity to Neutrino Mass Scale and Ordering
• High-resolution spectroscopy of gaseous ${}^{83m}$Kr conversion electrons with the KATRIN experiment

Cited by in corpus (1)

• Deep Learning Based Event Reconstruction for Cyclotron Radiation Emission Spectroscopy