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May 26 – 31, 2024
Western University
America/Toronto timezone
Welcome to the 2024 CAP Congress Program website! / Bienvenue au siteweb du programme du Congrès de l'ACP 2024!

(UG*) Deeply Learning the Position Reconstruction of Antihydrogen Annihilations in ALPHA-g

May 27, 2024, 4:45 PM
15m
SSC Rm 2020 (cap. 80) (Social Science Centre, Western U.)

SSC Rm 2020 (cap. 80)

Social Science Centre, Western U.

Oral Competition (Undergraduate Student) / Compétition orale (Étudiant(e) du 1er cycle) Nuclear Physics / Physique nucléaire (DNP-DPN) (DNP) M3-4 Precision Measurements in nuclear and particle physics I | Mesures de précision en physique nucléaire et en physique des particules I (DPN)

Speaker

Ashley Ferreira (TRIUMF (CA))

Description

The ALPHA-g experiment at CERN aims to perform the first-ever direct measurement of the effect of gravity on antimatter, determining its weight to within 1% precision. At TRIUMF, we are working on a new deep learning method based on the PointNet architecture to predict the height at which the antihydrogen atoms annihilate in the detector. This approach aims to improve upon the accuracy, efficiency, and speed of the existing annihilation position reconstruction. In this presentation, I will report on the promising preliminary performance of the model and discuss future development.

Keyword-1 antimatter
Keyword-2 deep learning

Primary author

Ashley Ferreira (TRIUMF (CA))

Co-authors

Andrea Capra Anna Li Anqi Xu Daniel Duque Gareth Smith Lars Martin Makoto Fujiwara Wojtek Fedorko Yukiya Saito

Presentation materials