LHCb: From the detector to the first physics results

International audienceIn this talk, the LHCb detector is presented, with emphasis on its main features and performance. The event selection is described, from the hardware trigger to the physics analysis. Last, some recent physics results are presented

Downstream Pattern Recognition

In this note the implementation of the downstream tracking for DC '06 is described, namely the package PatKShort v1r2. The principles of operation are described, together with the origin of the various algorithm parameters. Performance is given, in terms of efficiency, ghost rate and speed. Directions for improvement are also listed

LHCb detector status and upgrade

On behalf of the LHCb CollaborationInternational audienceThe LHCb experiment is a specialized experiment for B and D physics at the CERN LHC. The layout of the experiment and the various components are described, with an overview of their performance. Global running conditions and performance are also shown. The motivation for the foreseen detector upgrade is presented, together with the proposed new detectors, to be installed during Long Shutdown 2, in 2018

PatSeeding: A Standalone Track Reconstruction Algorithm

A standalone pattern recognition algorithm for the LHCb T stations is presented. Its performance on B_d --> J/psi K_s and minimum bias Monte Carlo events is evaluated, and tunings for reconstruction without magnetic field, with misalignments or for reconstruction of cosmics are shown. Furthermore, this notes describes changes to the algorithm which make it suitable for trigger applications, especially for Level 0 confirmation (the performance of these modifications is evaluated in an upcoming LHCb note)

The Forward Tracking: Algorithm and Performance Studies

This note describes the so-called Forward Tracking. This algorithm uses as input track seeds reconstructed in the VELO (Vetex Locator) and searches for associated tracks in the inner and outer tracker of the T stations based on a Hough Transformation approach. We describe in detail the implementation of the algorithm as it is in Brunel version 30r14 and the according performance on DC06 data

VELO-TT track reconstruction

The paper describes the track reconstruction in the system of VELO and TT detectors. Two separate algorithms for off-line and on-line approaches were merged. The single algorithm consists of the common code for pattern recognition and two parts specific to off-line and on-line functionalities. The note presents the performance in terms of track reconstruction efficiency and ghost rate

Control and Monitoring of the Online Computer Farm for Offline Processing in LHCb

ISBN 978-3-95450-139-7 - http://accelconf.web.cern.ch/AccelConf/ICALEPCS2013/papers/tuppc063.pdfInternational audienceLHCb, one of the 4 experiments at the LHC accelerator at CERN, uses approximately 1500 PCs (averaging 12 cores each) for processing the High Level Trigger (HLT) during physics data taking. During periods when data acquisition is not required most of these PCs are idle. In these periods it is possible to profit from the unused processing capacity to run offline jobs, such as Monte Carlo simulation. The LHCb offline computing environment is based on LHCbDIRAC (Distributed Infrastructure with Remote Agent Control). In LHCbDIRAC, job agents are started on Worker Nodes, pull waiting tasks from the central WMS (Workload Management System) and process them on the available resources. A Control System was developed which is able to launch, control and monitor the job agents for the offline data processing on the HLT Farm. This control system is based on the existing Online System Control infrastructure, the PVSS SCADA and the FSM toolkit. It has been extensively used launching and monitoring 22.000+ agents simultaneously and more than 850.000 jobs have already been processed in the HLT Farm. This paper describes the deployment and experience with the Control System in the LHCb experiment