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DOI 10.5286/stfctr.2026017
Persistent URL http://purl.org/net/epubs/work/67428951
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Record Id 67428951
Title Event identification for digitised traces from muon decay detectors
Contributors
Abstract In this work, we address the problem of identifying muon decay events in detector output time-series data. Several event detection approaches are reviewed, including direct thresholding, filtering, and hybrid methods. Building on these, we propose and evaluate algorithms based on fixed thresholds, derivative-based discrimination, and multiscale preprocessing using a pyramid approximation. Performance is assessed on both simulated and real datasets, focusing on detection accuracy, temporal resolution, amplitude sensitivity for the simulated data (where ground truth is known), and dead time analysis for the real datasets. The results demonstrate that derivative-based and multiscale methods improve robustness and event separation compared to standard thresholding, particularly in noisy conditions. Comparison of the fitted muon lifetimes indicates that derivative-based methods could enable approximately two- to four-fold higher usable count rates, potentially reducing data acquisition times by a similar factor for count-limited μSR experiments.
Organisation ISIS , ISIS-MuSR , ISIS-MUONS , STFC , SCI-COMP
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Licence Information: Creative Commons Attribution 4.0 International (CC BY 4.0)
Language English (EN)
Type Details URI(s) Local file(s) Year
Report STFC Technical Reports STFC-TR-2026-017. STFC, 2026. STFC-TR-2026-017.pdf 2026