Speaker
Ms
Cary Kan
(University of Toronto)
Description
Using Machine Learning models trained on simulated detector responses, we have made predictions of the energy and position of candidate dark matter collisions with ordinary matter in cryogenic germanium crystals at SNOLAB. Analysis of these results shows that mismatches between the samples used to train the models and data depend on event position, specifically at the detector's edges, and that further studies into the timing data from the detectors will be used to improve the accuracy of the model predictions.
| What area of study best describes your talk? | Analysis |
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Author
Ms
Cary Kan
(University of Toronto)