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We present a measurement of inclusive J/ψ production in p-Pb collisions at sNN−−−√ = 5.02 TeV as a function of the centrality of the collision, as estimated from the energy deposited in the Zero Degree Calorimeters. The measurement is performed with the ALICE detector down to zero transverse momentum, pT, in the backward (−4.46<ycms<−2.96) and forward (2.03<ycms<3.53) rapidity intervals in the dimuon decay channel and in the mid-rapidity region (−1.37<ycms<0.43) in the dielectron decay channel. The backward and forward rapidity intervals correspond to the Pb-going and p-going direction, respectively. The pT-differential J/ψ production cross section at backward and forward rapidity is measured for several centrality classes, together with the corresponding average pT and p2T values. The nuclear modification factor, QpPb, is presented as a function of centrality for the three rapidity intervals, and, additionally, at backward and forward rapidity, as a function of pT for several centrality classes. At mid- and forward rapidity, the J/ψ yield is suppressed up to 40% compared to that in pp interactions scaled by the number of binary collisions. The degree of suppression increases towards central p-Pb collisions at forward rapidity, and with decreasing pT of the J/ψ. At backward rapidity, the QpPb is compatible with unity within the total uncertainties, with an increasing trend from peripheral to central p-Pb collisions.
Transverse momentum (pT) spectra of pions, kaons, and protons up to pT=20 GeV/c have been measured in Pb-Pb collisions at sNN−−−√=2.76 TeV using the ALICE detector for six different centrality classes covering 0-80%. The proton-to-pion and the kaon-to-pion ratios both show a distinct peak at pT≈3 GeV/c in central Pb-Pb collisions that decreases towards more peripheral collisions. For pT>10 GeV/c, the nuclear modification factor is found to be the same for all three particle species in each centrality interval within systematic uncertainties of 10-20%. This suggests there is no direct interplay between the energy loss in the medium and the particle species composition in the hard core of the quenched jet. For pT<10 GeV/c, the data provide important constraints for models aimed at describing the transition from soft to hard physics.
Transverse momentum (pT) spectra of pions, kaons, and protons up to pT=20 GeV/c have been measured in Pb-Pb collisions at sNN−−−√=2.76 TeV using the ALICE detector for six different centrality classes covering 0-80%. The proton-to-pion and the kaon-to-pion ratios both show a distinct peak at pT≈3 GeV/c in central Pb-Pb collisions that decreases towards more peripheral collisions. For pT>10 GeV/c, the nuclear modification factor is found to be the same for all three particle species in each centrality interval within systematic uncertainties of 10-20%. This suggests there is no direct interplay between the energy loss in the medium and the particle species composition in the hard core of the quenched jet. For pT<10 GeV/c, the data provide important constraints for models aimed at describing the transition from soft to hard physics.
Direct photon production at mid-rapidity in Pb–Pb collisions at √sNN=2.76 TeV was studied in the transverse momentum range 0.9<pT<14 GeV/c. Photons were detected with the highly segmented electromagnetic calorimeter PHOS and via conversions in the ALICE detector material with the e+e− pair reconstructed in the central tracking system. The results of the two methods were combined and direct photon spectra were measured for the 0–20%, 20–40%, and 40–80% centrality classes. For all three classes, agreement was found with perturbative QCD calculations for pT≳5 GeV/c. Direct photon spectra down to pT≈1 GeV/c could be extracted for the 20–40% and 0–20% centrality classes. The significance of the direct photon signal for 0.9<pT<2.1 GeV/c is 2.6σ for the 0–20% class. The spectrum in this pT range and centrality class can be described by an exponential with an inverse slope parameter of (297±12stat±41syst) MeV. State-of-the-art models for photon production in heavy-ion collisions agree with the data within uncertainties.
ALICE (A Large Heavy Ion Experiment) is one of the four large scale experiments at the Large Hadron Collider (LHC) at CERN. The High Level Trigger (HLT) is an online computing farm, which reconstructs events recorded by the ALICE detector in real-time. The most computing-intensive task is the reconstruction of the particle trajectories. The main tracking devices in ALICE are the Time Projection Chamber (TPC) and the Inner Tracking System (ITS). The HLT uses a fast GPU-accelerated algorithm for the TPC tracking based on the Cellular Automaton principle and the Kalman filter. ALICE employs gaseous subdetectors which are sensitive to environmental conditions such as ambient pressure and temperature and the TPC is one of these. A precise reconstruction of particle trajectories requires the calibration of these detectors. As our first topic, we present some recent optimizations to our GPU-based TPC tracking using the new GPU models we employ for the ongoing and upcoming data taking period at LHC. We also show our new approach to fast ITS standalone tracking. As our second topic, we present improvements to the HLT for facilitating online reconstruction including a new flat data model and a new data flow chain. The calibration output is fed back to the reconstruction components of the HLT via a feedback loop. We conclude with an analysis of a first online calibration test under real conditions during the Pb-Pb run in November 2015, which was based on these new features.
The Time Projection Chamber (TPC) of the ALICE experiment at the CERN LHC was upgraded for Run 3 and Run 4. Readout chambers based on Gas Electron Multiplier (GEM) technology and a new readout scheme allow continuous data taking at the highest interaction rates expected in Pb-Pb collisions. Due to the absence of a gating grid system, a significant amount of ions created in the multiplication region is expected to enter the TPC drift volume and distort the uniform electric field that guides the electrons to the readout pads. Analytical calculations were considered to correct for space-charge distortion fluctuations but they proved to be too slow for the calibration and reconstruction workflow in Run 3. In this paper, we discuss a novel strategy developed by the ALICE Collaboration to perform distortion-fluctuation corrections with machine learning and convolutional neural network techniques. The results of preliminary studies are shown and the prospects for further development and optimization are also discussed.