Speaker
Description
Analyzing HL-LHC heavy-ion collision data with ALICE
Victor Gonzalez, Wayne State University (US),
on behalf of the ALICE Collaboration
The ALICE detector has been taking data at heavy-ion HL-LHC regime since the start of the LHC Run 3 Pb--Pb campaign in October 2023. Recording Pb$-$Pb collisions at 50 kHz and pp collisions up to 1 MHz interaction rates without trigger results in processing data in real time at rates up to two orders of magnitude higher than during LHC Run 2. To reach that, ALICE underwent a major upgrade on all detectors to make use of the increased luminosity provided by the LHC. The Inner Tracking System now completely consists of Monolithic Active Pixel Sensors which improves pointing resolution. The Time Projection Chamber has been equipped with GEM-based readout chambers to support the continuous readout at the target interaction rate. New forward trigger detectors were installed to allow the clean identification of interactions. The computer infrastructure and the software framework have been completely redesigned for continuous readout, synchronous reconstruction, asynchronous reconstruction incorporating calibration, and a much more efficient and productive scenario for analyzing the considerable increase in the stored data. To reach this point the evolution of the new software framework required key design choices which now constitute the main characteristics of the ALICE Online-Offline, O$^2$, computing framework. In this session, the main structure of O$^2$ as well as its organized analysis infrastructure, Hyperloop train system, will be presented highlighting the features which support the HL-LHC scenario and the physics analysis scenario which provides effective, efficient, and productive access to the huge amount of collected data to the large community of analyzers that conforms the ALICE Collaboration.
