Speaker
Description
LiquidO is an opaque scintillator-based radiation detection technology which aims to
overcome some of the drawbacks of the transparent detectors. Instead of letting the
scintillation photons propagate freely through the detector, it uses an opaque medium
with low scattering length to confine the light stochastically near its creation point.
The scattered photons are then collected by an array of wavelength-shifting fibres which are read out by SiPMs at their ends. The confinement of photons preserves the local spatial
information and event topology, leading to high vertex resolution and particle identification
capability, without introducing mechanical segmentation.
This poster concerns with the mitigation of dark noise in a LiquidO-based detector. Dark noise hits are triggered in an SiPM by spontaneous thermal electrons, independently from photons. The dark noise rate depends on the SiPM overvoltage and temperature, and in a realistic case, the noise hits are expected to overwhelm the signal hits by 2-3 times. This has the potential to severely limit the vertex resolution and PID capabilities. But fortunately, the noise hits are uniformly distributed in space and time, as opposed to the signal hits which are spatio-temporally correlated. This clustered nature of the signal motivates the use of the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm to filter out the noise.
In the truth study, DBSCAN has shown excellent performance in terms of the resulting Signal-to-Noise ratio. The noise removal significantly improves vertex resolution, and the filtered hits can be used to set the start time of an event reliably, aiding subsequent analyses. The generality of the algorithm makes it potentially suitable for a wide range of LiquidO-based detectors where the stochastic confinement of light produces a clustered signal against the backdrop of uniformly distributed noise