Speaker
Description
Since March 2019 the Belle II detector has collected data from e+ e- collisions at the SuperKEKB collider. For Belle II analyses to be competitive it is crucial that calibration constants are calculated promptly so that the reconstructed datasets can be provided to analysts. A subset of calibration constants also benefit by being re-derived during yearly recalibration campaigns to give analysts the best possible reconstructed datasets for their final publications.
At the Belle II experiment a Python package, b2cal, was developed to automate the running of Calibration and Alignment Framework (CAF) processes for prompt calibration at Brookhaven National Laboratory (BNL). This uses the open-source Apache Airflow workflow platform to schedule, run, and monitor the calibration procedures by describing them as Directed Acyclic Graphs (DAGs). This has resulted in a successful reduction of both the time taken to produce constants and the human intervention required. In 2022 the recalibration of older data at the Deutsches Elektronen-Synchrotron Laboratory (DESY) was also performed in parallel with the continuing prompt calibration at BNL. The scope of the system has now expanded to include the organisation of creating calibration constants for run-dependent Monte Carlo data and development of the b2cal package now focuses on incorporating more of the post-calibration data processing tasks. The current structure of the automated Belle II calibration system and these new developments will be described.
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