New Approaches for Acoustic Analysis in PICO Dark Matter Searches

Abstract

With the search for dark matter well underway among the physics community, the PICO experiment, using superheated fluorocarbons in bubble chambers, has set world-leading limits on the WIMP-proton cross section with multiple detectors. One strength of the PICO experiment is its exceptional background rejection methods, particularly in background events from alpha particles, which produce significantly different acoustic signals than WIMP-like interactions. Furthermore, PICO bubble chambers are almost entirely insensitive to electron recoils, so the majority of background events are caused by neutrons and alphas. This thesis proposes new metrics for acoustic analysis of events for alpha rejection, and introduces new analysis techniques which seek to optimize these metrics. We start by providing motivation for the PICO experiment, as well as for updated monitoring tools for the upcoming PICO40L bubble chamber. The previous acoustic analysis for PICO-60 is covered, motivating new methods in acoustic analysis for alpha rejection. We then introduce relevant metrics for acoustic analysis, as well as new methods for selecting relevant frequencies to optimize these metrics. Finally, a novel attempt to reduce noise levels in the context of alpha rejection is made using spectral filtering.