4-8 November 2019
Adelaide Convention Centre
Australia/Adelaide timezone

Selective background Monte Carlo simulation at Belle II

5 Nov 2019, 15:00
Riverbank R6 (Adelaide Convention Centre)

Riverbank R6

Adelaide Convention Centre

Oral Track 2 – Offline Computing Track 2 – Offline Computing


James Kahn (Karlsruhe Institute of Technology (KIT))


The large volume of data expected to be produced by the Belle II experiment presents the opportunity for for studies of rare, previously inaccessible processes. To investigate such rare processes in a high data volume environment necessitates a correspondingly high volume of Monte Carlo simulations to prepare analyses and gain a deep understanding of the contributing physics processes to each individual study. This resulting challenge, in terms of computing resource requirements, calls for more intelligent methods of simulation, in particular for background processes with very high rejection rates. This work presents a method of predicting in the early stages of the simulation process the likelihood of relevancy of an individual event to the target study using convolutional neural networks. The results show a robust training that is integrated natively into the existing Belle II analysis software framework, with steps taken to mitigate systematic biases induced by the early selection procedure.

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Primary authors

James Kahn (Karlsruhe Institute of Technology (KIT)) Thomas Kuhr (Ludwig Maximilians Universitat (DE)) Andreas Maximilian Lindner (University of Munich (LMU))

Presentation Materials