Abstract: Using the ATLAS detector, a centrality-dependent suppression has been observed in the yield of J/psi mesons produced in the collisions of lead ions at the Large Hadron Collider. In a sample of minimum-bias lead-lead collisions at a nucleon-nucleon centre of mass energy root s(NN) = 2.76 TeV, corresponding to an integrated luminosity of about 6.7 μb(-1), J/psi mesons are reconstructed via their decays to mu(+)mu(-) pairs. The measured J/psi yield, normalized to the number of binary nucleon-nucleon collisions, is found to significantly decrease from peripheral to central collisions. The centrality dependence is found to be qualitatively similar to the trends observed at previous, lower energy experiments. The same sample is used to reconstruct Z bosons in the mu(+)mu(-) final state, and a total of 38 candidates are selected in the mass window of 66 to 116 GeV. The relative Z yields as a function of centrality are also presented, although no conclusion can be inferred about their scaling with the number of binary collisions, because of limited statistics. This analysis provides the first results on J/psi and Z production in lead-lead collisions at the LHC.

Abstract: ATLAS is a multipurpose experiment that records the products of the LHC collisions. In order to reconstruct the trajectories of the charged particles produced in these collisions. ATLAS has an internal tracking system made of silicon planar sensors (pixels and micro-strips) and drift-tube based detectors; both together, they constitute the ATLAS Inner Detector. The alignment of the ATLAS tracking system requires the determination of their almost 36,000 degrees-of-freedom (DOF) with high accuracy. Thus, the demanded precision for the alignment of the pixel and micro-strip sensors is below 10 μm. As alignment algorithms are based on the minimization of the track-hit residuals, a linear system with a large number of DOF has to be solved. The alignment results of the ATLAS tracker using data recorded during cosmic commissioning phases in 2008 and 2009 and the LHC start up run in 2009 will be presented. Moreover recent 7 TeV data collected during 2010 run have been used to study the detector performance. These studies reveal that the detector is aligned with a precision high enough to cope with the requirements.

Abstract: Research in many areas of modern physics such as, e. g., indirect searches for dark matter and particle acceleration in supernova remnant shocks rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays, gamma-rays). While very detailed numerical models of CR propagation exist, a quantitative statistical analysis of such models has been so far hampered by the large computational effort that those models require. Although statistical analyses have been carried out before using semi-analytical models (where the computation is much faster), the evaluation of the results obtained from such models is difficult, as they necessarily suffer from many simplifying assumptions. The main objective of this paper is to present a working method for a full Bayesian parameter estimation for a numerical CR propagation model. For this study, we use the GALPROP code, the most advanced of its kind, which uses astrophysical information, and nuclear and particle data as inputs to self-consistently predict CRs, gamma-rays, synchrotron, and other observables. We demonstrate that a full Bayesian analysis is possible using nested sampling and Markov Chain Monte Carlo methods (implemented in the SuperBayeS code) despite the heavy computational demands of a numerical propagation code. The best-fit values of parameters found in this analysis are in agreement with previous, significantly simpler, studies also based on GALPROP.