Speaker
Description
Recent discrepancies between the Standard Model prediction of the anomalous magnetic moment of the muon, $a_{\mu}^{SM}$, and experimental measurements, $a_{\mu}^{Exp}$, suggest the possibility of new physics and unknown particles. The proposed J-PARC muon g-2/EDM experiment aims to measure the muon's anomalous magnetic moment with a precision of 460 ppb(sys + stat). This will be achieved by using reaccelerated ultracold muons injected into a magnetic storage ring. A crucial aspect of the g-2/EDM experiment is the accurate reconstruction of positron tracks from muon decays, which is currently performed using the hough-transformation technique. However, the current track-finding process is computationally slow, and a speedup factor of 10 is currently required. To address this issue, alternate strategies have been proposed, one that uses Graphical Processing Units (GPUs) and another using Graph Neural Networks (GNNs). We present an overview and the current status of our efforts in this direction.
| Field of contribution | Experiment |
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