Binary Classification of Light and Dark Time Traces of a Transition Edge Sensor Using Convolutional Neural Networks
Elmeri Rivasto; Katharina-Sophie Isleif; Friederike Januschek; Axel Lindner; Manuel Meyer; Gulden Othman; José Alejandro Rubiera Gimeno; Christina Schwemmbauer · 2025 · arXiv
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
The Any Light Particle Search II (ALPS II) is a light shining through a wall experiment probing the existence of axions and axion-like particles using a 1064 nm laser source. While ALPS II is already taking data using a heterodyne based detection scheme, cryogenic transition edge sensor (TES) based single-photon detectors are planned to expand the detection system for cross-checking the potential signals, for which a sensitivity on the order of $10^{-24}$ W is required. In order to reach this goal, we have investigated the use of convolutional neural networks (CNN) as binary classifiers to dis
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Metadata source: arXiv