ALICE is the heavy-ion experiment at the CERN Large Hadron Collider. The experiment continuously took data during the first physics campaign of the machine from fall 2009 until early 2013, using proton and lead-ion beams. In this paper we describe the running environment and the data handling procedures, and discuss the performance of the ALICE detectors and analysis methods for various physics observables.
HADES is a versatile magnetic spectrometer aimed at studying dielectron production in pion, proton and heavy-ion induced collisions. Its main features include a ring imaging gas Cherenkov detector for electron-hadron discrimination, a tracking system consisting of a set of 6 superconducting coils producing a toroidal field and drift chambers and a multiplicity and electron trigger array for additional electron-hadron discrimination and event characterization. A two-stage trigger system enhances events containing electrons. The physics program is focused on the investigation of hadron properties in nuclei and in the hot and dense hadronic matter. The detector system is characterized by an 85 % azimuthal coverage over a polar angle interval from 18• to 85• , a single electron efficiency of 50 % and a vector meson mass resolution of 2.5 %. Identification of pions, kaons and protons is achieved combining time-of-flight and energy loss measurements over a large momentum range. This paper describes the main features and the performance of the detector system.
Abstract-A Transition Radiation Detector (TRD) has been designed to improve the electron identification and trigger capability of the ALICE experiment at the Large Hadron Collider (LHC) at CERN. We present results from tests of a prototype of the TRD concerning pion rejection for different methods of analysis over a momentum range from 0.7 to 2 GeV/c. We investigate the performance of different radiator types, composed of foils, fibres and foams.
We study the electron/pion identification performance of the ALICE Transition Ra-diation Detector (TRD) prototypes using a neural network (NN) algorithm. Measurements were carried out for particle momenta from 2 to 6 GeV/c. An improvement in pion rejection by about a factor of 3 is obtained with NN compared to standard likelihood methods.
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