Reconstruction in ALICE and calibration of TPC space-charge distortions in Run 3
Ernst Hellb\"ar (for the ALICE Collaboration)

TL;DR
The paper discusses the upgrades and calibration techniques for the ALICE TPC in Run 3, focusing on handling high interaction rates and space-charge distortions using advanced algorithms and hardware improvements.
Contribution
It introduces new hardware upgrades and a data-driven calibration scheme employing machine learning to correct space-charge distortions in the TPC during high-rate collisions.
Findings
Successful hardware upgrades to the TPC readout chambers.
Development of machine learning algorithms for real-time distortion correction.
Enhanced tracking resolution at high interaction rates.
Abstract
The ALICE experiment will run with continuous readout at interaction rates of up to 50 kHz in Pb-Pb collisions during Run 3 of the LHC. In order to achieve this goal, a new data processing scheme and software are developed. This scheme strongly relies on GPUs (Graphics Processing Unit) for fast online and offline calibration and reconstruction as well as on efficient data compression. On the hardware side, the Time Projection Chamber (TPC), among other detector systems, received major upgrades to its readout chambers and readout electronics. The multiwire proportional chambers were replaced by stacks of four Gas Electron Multiplier foils to allow for continuous readout while keeping the ion backflow below 1%, minimizing space-charge effects from amplification ions entering the drift volume. Nevertheless, significant space-point distortions due to space charge are expected at the highest…
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