Speaker
Description
In radio-based physics experiments, sensitive analysis techniques are often required to extract signals at or below the level of noise. For a recent experiment at the SLAC National Accelerator Laboratory to test a radar-based detection scheme for high energy neutrino cascades, such a sensitive analysis was employed to dig down into a spurious background and extract a signal. This analysis employed singular-value decomposition (SVD) to decompose the data into a basis of patterns constructed from the data itself. Expansion of data in a decomposition basis allows for the extraction, or filtration, of patterns which may be unavailable to other analysis techniques. In this talk we briefly present the results of this analysis in the context of experiment T-576 at SLAC, and detail the analysis method which was used to extract a hint of a radar signal at a significance of 2.3$\sigma$.
