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.

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In 2004 at the ATLAS (A Toroidal LHC ApparatuS) combined test beam, one slice of the ATLAS barrel detector (including an Inner Detector set-up and the Liquid Argon calorimeter) was exposed to particles from the H8 SPS beam line at CERN. It was the first occasion to test the combined electron performance of ATLAS. This paper presents results obtained for the momentum measurement p with the Inner Detector and for the performance of the electron measurement with the LAr calorimeter (energy E linearity and resolution) in the presence of a magnetic field in the Inner Detector for momenta ranging from 20 GeV/c to 100 GeV/c. Furthermore the particle identification capabilities of the Transition Radiation Tracker, Bremsstrahlungs-recovery algorithms relying on the LAr calorimeter and results obtained for the E/p ratio and a way how to extract scale parameters will be discussed.

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.

a b s t r a c tA fully instrumented slice of the ATLAS central detector was exposed to test beams from the SPS (Super Proton Synchrotron) at CERN in 2004. In this paper, the response of the central calorimeters to pions with energies in the range between 3 and 9 GeV is presented. The linearity and the resolution of the combined calorimetry (electromagnetic and hadronic calorimeters) was measured and compared to the prediction of a detector simulation program using the toolkit Geant 4.