English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

A Large Ion Collider Experiment (ALICE) is one of the four major experiments at the Large Hadron Collider (LHC) at CERN. The high level trigger (HLT) is a compute cluster, which reconstructs collisions as recorded by the ALICE detector in real-time. It employs a custom online data-transport framework to distribute data and workload among the compute nodes. ALICE employs subdetectors that are sensitive to environmental conditions such as pressure and temperature, e.g., the time projection chamber (TPC). A precise reconstruction of particle trajectories requires calibration of these detectors. Performing calibration in real time in the HLT improves the online reconstructions and renders certain offline calibration steps obsolete speeding up offline physics analysis. For LHC Run 3, starting in 2020 when data reduction will rely on reconstructed data, online calibration becomes a necessity. Reconstructed particle trajectories build the basis for the calibration making a fast online-tracking mandatory. The main detectors used for this purpose are the TPC and Inner Tracking System. Reconstructing the trajectories in the TPC is the most compute-intense step. We present several improvements to the ALICE HLT developed to facilitate online calibration. The main new development for online calibration is a wrapper that can run ALICE offline analysis and calibration tasks inside the HLT. In addition, we have added asynchronous processing capabilities to support long-running calibration tasks in the HLT framework, which runs event-synchronously otherwise. In order to improve the resiliency, an isolated process performs the asynchronous operations such that even a fatal error does not disturb data taking. We have complemented the original loop-free HLT chain with ZeroMQ data-transfer components. The ZeroMQ components facilitate a feedback loop that inserts the calibration result created at the end of the chain back into tracking components at the beginning of the chain, after a short delay. All these new features are implemented in a general way, such that they have use-cases aside from online calibration. In order to gather sufficient statistics for the calibration, the asynchronous calibration component must process enough events per time interval. Since the calibration is valid only for a certain time period, the delay until the feedback loop provides updated calibration data must not be too long. A first full-scale test of the online calibration functionality was performed during 2015 heavy-ion run under real conditions. Since then, online calibration is enabled and benchmarked in 2016 proton-proton data taking. We present a timing analysis of this first online-calibration test, which concludes that the HLT is capable of online TPC drift time calibration fast enough to calibrate the tracking via the feedback loop. We compare the calibration results with the offline calibration and present a comparison of the residuals of the TPC cluster coordinates with respect to offline reconstruction.

Online Calibration of the TPC Drift Time in the ALICE High Level Trigger