Erlangen 2026 – wissenschaftliches Programm

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HK: Fachverband Physik der Hadronen und Kerne

HK 3: Hadron Structure and Spectroscopy II

HK 3.5: Vortrag

Montag, 16. März 2026, 17:30–17:45, PHIL A 401

Particle Identification (eγγ) of Primakoff-Electroproduction π⁰-Events for PRIMA FAIR Phase-0 — Òscar Andújar Sabán¹, Ning Cao¹, Luigi Capozza¹, Jonas Geisbüsch¹, Ravi Gowdru Manjunata¹, Frank Maas^1,2,3, •Antoine Martinet¹, Oliver Noll^1,2, Paul Schöner¹, Christoph Rosner¹, Pierre Vijayan¹, and Sahra Wolff¹ — ¹Helmholtz-Institut Mainz, Mainz, Germany — ²Institute of Nuclear Physics, Mainz, Germany — ³PRISMA+ Cluster of Excellence, Mainz, Germany

The FAIR Phase-0 experiment PRIMA, conducted at the Mainzer Mikrotron (MAMI), aims at measuring the π⁰ transition form factor (TFF) in doubly-virtual Primakoff kinematics. Improving the TFF uncertainty is crucial, as it contributes a large uncertainty to the Standard Model prediction of the anomalous magnetic moment of the muon. The TFF represents the leading order of the hadronic light-by-light scattering (HLbL) correction. To achieve this, a modified version of the homogeneous PbWO₄-based PANDA backward-electromagnetic-calorimeter is used to measure the final state of the scattered electron and the π⁰-decay photons. Key to this analysis is the particle identification for the eγγ final state. This can be done using the invariant mass of the detected particles, but potentially also using a neural network. This talk presents the current progress on particle identification of electrons and photons using a neural network.

Keywords: Hadron structure; Data analysis; Machine Learning