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| Funder | Science and Technology Facilities Council |
|---|---|
| Recipient Organization | University College London |
| Country | United Kingdom |
| Start Date | Sep 30, 2022 |
| End Date | Sep 29, 2026 |
| Duration | 1,460 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2719045 |
The CRES Demonstration Apparatus (CRESDA) will be developed over the next two years.
The student will become familiar with a range of topics including quantum detection & amplification, antenna theory and signal processing.
CRESDA will collect a large volume of time-domain antenna waveforms, both simulated and real, and the heart of this PhD project is the development of techniques to extract complex signals that are barely visible above thermal background. The CRES signals can have a variety of shapes depending on the electron energy and motion inside the trap.
Techniques to be explored include using matched-filters to compare a library of waveforms with the data, and the extraction of the most important features such as the starting frequency of the cyclotron emission (which carries information about the electron decay energy). Image analysis of spectrograms will be used to identify electron trajectories in our data.
The over-arching aim of the project will be to use these machine-learning and data-analysis techniques to help inform projections for the ultimate reach of a future neutrino mass experiment employing the CRES technique.
University College London
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