Heidelberg 2022 – wissenschaftliches Programm

Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

AKPIK: Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz

AKPIK 1: Data Integration & Processing

AKPIK 1.9: Vortrag

Montag, 21. März 2022, 18:15–18:30, AKPIK-H13

IEA-GAN: Intra-Event Aware GAN for the Fast Simulation of PXD Background at Belle II — •Hosein Hashemi, Nikolai Hartmann, Thomas Kuhr, and Martin Ritter — Faculty of Physics, Ludwig Maximilians University of Munich, Germany

The pixel vertex detector (PXD) is the newest and the most sensitive sub-detector at the Belle~II. Data from the PXD and other sensors allow us to reconstruct particle tracks and decay vertices. The effect of background processes on track reconstruction is simulated by adding measured or simulated background hit patterns to the hits produced by simulated signal particles that originate from the processes of interest. This model requires a large set of statistically independent PXD background noise samples to avoid a systematic bias of reconstructed tracks. However, the fine-grained PXD data requires a substantial amount of storage. As an efficient way of producing background information for fast simulation, we introduce the idea of an on-demand PXD background generator with Intra-Event Aware GAN (IEA-GAN), conditioned over the number of PXD sensors in order to produce sensor-dependent PXD images by approximating the concept of an "event" in the detector as these PXD images share both semantic and statistical features that makes it extremely hard for even the State of the Art GANs to mimic these exact properties. As a result, we developed the IEA-GAN model which captures these dependencies by imposing relational inductive bias over the batch dimension.