[en] ALEPH and DELPHI were the first experiments operating a silicon vertex detector at LEP. During the past 10 years of data taking the DELPHI Silicon Tracker was upgraded three times to follow the different tracking requirements for LEP 1 and LEP 2 as well as to improve the tracking performance. Several steps in the development of the pattern recognition software were done in order to understand and fully exploit the silicon tracker information. This article gives an overview of the final algorithms and concepts of the track reconstruction using the Silicon Tracker in DELPHI

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[en] A measurement of the c and s quarks forward-backward asymmetry is presented, based on the multihadronic events collected by the DELPHI detector at LEP during 1991 and 1992. The initial quark is tagged by the presence of a D^*+ in the case of c and a high momentum Λ or K_L⁰ in the case of s. The experimental results are A_FB^c=0.066 and A_FB^s=0.129. (author). 9 refs., 2 figs., 1 tab

[en] The long term accessibility of its data is an important concern of the DELPHI collaboration. It is the authors' assumption that the storage of the data itself will be a minor issue due to the progress in storage technologies. Therefore DELPHI focuses on a reorganisation of the data, which should provide a flexible and coherent framework for physics analysis in the future. The authors describe the current status of the IDEA (Improved DElphi Analysis) project which will ensure usability of DELPHI data for future generations of physicists

[en] The track reconstruction of modern high energy physics experiments is a very complex task that puts stringent requirements onto the software realisation. The ATLAS track reconstruction software has been in the past dominated by a collection of individual packages, each of which incorporating a different intrinsic event data model, different data flow sequences and calibration data. Recently, the ATLAS track reconstruction has undergone a major design revolution to ensure maintainability during the long lifetime of the ATLAS experiment and the flexibility needed for the startup phase. The entire software chain has been re-organised in modular components and a common event data model has been deployed. A complete new track reconstruction that concentrates on common tools aimed to be used by both ATLAS tracking devices, the Inner Detector and the Muon System, has been established. It has been already used during many large scale tests with data from Monte Carlo simulation and from detector commissioning projects such as the combined test beam 2004 and cosmic ray events. This document concentrates on the technical and conceptual details of the newly developed track reconstruction

[en] The ATLAS experiment at the LHC has been recording data from proton-proton collisions with 13 TeV center-of-mass energy since spring 2015. The collaboration is using a fast physics monitoring framework (TADA) to automatically perform a broad range of fast searches for early signs of new physics and to monitor the data quality across the year with the full analysis level calibrations applied to the rapidly growing data. TADA is designed to provide fast feedback directly after the collected data has been fully calibrated and processed at the Tier-0. The system can monitor a large range of physics channels, offline data quality and physics performance quantities. TADA output is available on a website accessible by the whole collaboration. It gets updated twice a day with the data from newly processed runs. Hints of potentially interesting physics signals or performance issues identified in this way are reported to be followed up by physics or combined performance groups. The note reports as well about the technical aspects of TADA: the software structure to obtain the input TAG files, the framework workflow and structure, the webpage and its implementation. (paper)

[en] While many high energy experiments use track fitting software that is based solely on the Kalman Filter technique, the ATLAS offline reconstruction also has several global track fitters available. One of these is the GlobalChi2Fitter, which is based on the scattering angle formulation of the track fit. One of the advantages of this method over the Kalman fit is that it can provide the scattering angles and related quantities (e.g. the residual derivatives) to the alignment algorithms. The algorithm has been implemented in the new common tracking framework in ATLAS, the philosophy of which is to improve the modularity and flexibility of the tracking software. This flexibility has proven crucial for the understanding of the data from the testbeam and cosmic runs. An overview of recent results will be presented, in particular the results from the combined tracking with the inner detector and the muon spectrometer using the cosmics data

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[en] The ATLAS experiment uses a complex trigger strategy to be able to reduce the Event Filter rate output, down to a level that allows the storage and processing of these data. These concepts are described in the ATLAS Computing Model which embraces Grid paradigm. The output coming from the Event Filter consists of four main streams: physical stream, express stream, calibration stream, and diagnostic stream. The calibration stream will be transferred to the Tier-0 facilities that will provide the prompt reconstruction of this stream with a minimum latency of 8 hours, producing calibration constants of sufficient quality to allow a first-pass processing. The Inner Detector community is developing and testing an independent common calibration stream selected at the Event Filter after track reconstruction. It is composed of raw data, in byte-stream format, contained in Readout Buffers (ROBs) with hit information of the selected tracks, and it will be used to derive and update a set of calibration and alignment constants. This option was selected because it makes use of the Byte Stream Converter infrastructure and possibly gives better bandwidth usage and storage optimization. Processing is done using specialized algorithms running in the Athena framework in dedicated Tier-0 resources, and the alignment constants will be stored and distributed using the COOL conditions database infrastructure. This work is addressing in particular the alignment requirements, the needs for track and hit selection, and the performance issues