[17a-S2_202-1~12] 2.2 Radiation generators, Detector development, Measurement technology

10:30 AM - 10:45 AM JST(1:30 AM - 1:45 AM UTC)Presentation by Applicant for JSAP Young Scientists Presentation Award

[17a-S2_202-7] Automatic Detection of Electromagnetic Showers in Cloud Chamber Experiments Using Machine Learning

〇Tomoya Hayashi¹, Kento Nakano¹, Nobuko Kitagawa², Kunihiro Morishima¹ (1.Nagoya Univ., 2.Nagoya Univ, IMass.)

Keywords:

machine learning

A cloud chamber is a device that forms visible tracks by generating condensation nuclei as charged particles pass through supersaturated alcohol vapor. In this study, lead was placed around the cloud chamber to observe the resulting electromagnetic showers. Visual analysis suffered from reduced detection efficiency during prolonged observation and missed tracks. Therefore, we applied YOLO, an object detection algorithm using machine learning, to the cloud chamber. By enabling automatic track detection, we aimed to introduce an analysis method independent of visual inspection.