Kavli Affiliate: D. B. Macfarlane
| First 5 Authors: M. F. Albakry, M. F. Albakry, , ,
| Summary:
SuperCDMS SNOLAB uses kilogram-scale germanium and silicon detectors to
search for dark matter. Each detector has Transition Edge Sensors (TESs)
patterned on the top and bottom faces of a large crystal substrate, with the
TESs electrically grouped into six phonon readout channels per face. Noise
correlations are expected among a detector’s readout channels, in part because
the channels and their readout electronics are located in close proximity to
one another. Moreover, owing to the large size of the detectors, energy
deposits can produce vastly different phonon propagation patterns depending on
their location in the substrate, resulting in a strong position dependence in
the readout-channel pulse shapes. Both of these effects can degrade the energy
resolution and consequently diminish the dark matter search sensitivity of the
experiment if not accounted for properly. We present a new algorithm for pulse
reconstruction, mathematically formulated to take into account correlated noise
and pulse shape variations. This new algorithm fits N readout channels with a
superposition of M pulse templates simultaneously – hence termed the N$times$M
filter. We describe a method to derive the pulse templates using principal
component analysis (PCA) and to extract energy and position information using a
gradient boosted decision tree (GBDT). We show that these new N$times$M and
GBDT analysis tools can reduce the impact from correlated noise sources while
improving the reconstructed energy resolution for simulated mono-energetic
events by more than a factor of three and for the 71Ge K-shell electron-capture
peak recoils measured in a previous version of SuperCDMS called CDMSlite to $<$
50 eV from the previously published value of $sim$100 eV. These results lay
the groundwork for position reconstruction in SuperCDMS with the N$times$M
outputs.
| Search Query: ArXiv Query: search_query=au:”D. B. Macfarlane”&id_list=&start=0&max_results=3