Statistical Signal Processing and Detector Optimization in Project 8
Name
buzinsky-buzinsky-phd-physics-2021-thesis.pdf
Description
Thesis PDF
Size
9.25 MB
Format
Adobe PDF
Checksum (MD5)
a89062c203d3061c17dc2d81c9180711
Author(s)
Buzinsky, Nicholas
Advisor(s)
Formaggio, Joseph A.
Date Issued
September 2021
Publisher
Massachusetts Institute of Technology
Abstract
Despite the unambiguous discovery of non-zero neutrino masses from flavor oscillation experiments, a direct measurement of the absolute mass scale of the neutrino remains elusive to experimentalists. Project 8 is a tritium endpoint experiment utilizing Cyclotron Radiation Emission Spectroscopy (CRES), a novel, high-precision spectroscopic technique, in order to establish the absolute neutrino mass scale. In this document, I investigate the statistically motivated limits to CRES signal detection and parameter estimation, as well as the resultant consequences on optimal detector configuration. I implement and test an application of the Viterbi algorithm for CRES signal reconstruction, yielding the first derived limits on the minimal detection criteria. I then present an original derivation of the Cramér-Rao Lower Bound of the start frequency resolution for realistic CRES signals, along with estimators yielding near-optimal performance. Finally, these improved detection and reconstruction algorithms lead into a discussion of optimal detector design.
MIT Department
Massachusetts Institute of Technology. Department of Physics
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In Copyright - Educational Use Permitted
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