[en] We report a selection of the most recent Cdf and D0 analyses on the W and Z physics, based on the Tevatron Run 2. data. The latest results on the W mass and width and on di boson physics are reviewed. The main focus is put on results for the production of W/Z + jets with an emphasis on comparison of experimental results to the latest theoretical models.

[en] W W and W Z production in p(bar) p collisions at 1.96 TeV are studied in samples of ∼ 3 fb^-1 of data using leptons, jets and missing E_t. Fully leptonic decays as well as semi-leptonic decays are measured. Diboson production is expected in the standard model, and predicted cross sections are confirmed. It is important to investigate various signatures as associated production of Higgs bosons is topologically similar. (author)

[en] As the Tevatron luminosity increases sophisticated selections are required to be efficient in selecting rare events among a very huge background. To cope with this problem, CDF has pushed the offline calorimeter algorithm reconstruction resolution up to Level 2 and, when possible, even up to Level 1, increasing efficiency and, at the same time, keeping under control the rates. The CDF Run II Level 2 calorimeter trigger is implemented in hardware and is based on a simple algorithm that was used in Run I. This system has worked well for Run II at low luminosity. As the Tevatron instantaneous luminosity increases, the limitation due to this simple algorithm starts to become clear: some of the most important jet and MET (Missing ET) related triggers have large growth terms in cross section at higher luminosity. In this paper, we present an upgrade of the Level 2 Calorimeter system which makes the calorimeter trigger tower information available directly to a CPU allowing more sophisticated algorithms to be implemented in software. Both Level 2 jets and MET can be made nearly equivalent to offline quality, thus significantly improving the performance and flexibility of the jet and MET related triggers. However in order to fully take advantage of the new L2 triggering capabilities having at Level 1 the same L2 MET resolution is necessary. The new Level-1 MET resolution is calculated by dedicated hardware. This paper describes the design, the hardware and software implementation and the performance of the upgraded calorimeter trigger system both at Level 2 and Level 1.

[en] We describe the design and expected performance of a the Fast Tracker Trigger (FTK) system for the ATLAS detector at the Large Hadron Collider. The FTK is a highly parallel hardware system designed to operate at the Level 1 trigger output rate. It is designed to provide global tracks reconstructed in the inner detector with resolution comparable to the full offline reconstruction as input of the Level 2 trigger processing. The hardware system is based on associative memories for pattern recognition and fast FPGAs for track reconstruction. The FTK is expected to dramatically improve the performance of track based isolation and b-tagging with little to no dependencies of pile-up interactions.

[en] The use of tracking information at the trigger level in the LHC Run II period is crucial for the trigger and data acquisition system and will be even more so as contemporary collisions that occur at every bunch crossing will increase in Run III. The Fast TracKer is part of the ATLAS trigger upgrade project; it is a hardware processor that will provide every Level-1 accepted event (100 kHz) and within 100μs, full tracking information for tracks with momentum as low as 1 GeV . Providing fast, extensive access to tracking information, with resolution comparable to the offline reconstruction, FTK will help in precise detection of the primary and secondary vertices to ensure robust selections and improve the trigger performance

[en] The Fast Tracker (FTK) processor is an approved ATLAS upgrade that will reconstruct tracks using the full silicon tracker at Level-1 rate (up to 100 KHz). FTK uses a completely parallel approach to read the silicon tracker information, execute the pattern matching and reconstruct the tracks. This approach, according to detailed simulation results, allows full tracking with nearly offline resolution within an execution time of 100μs. A central component of the system is the associative memories (AM); these special devices reduce the pattern matching combinatoric problem, providing identification of coarse resolution track candidates. The system consists of a pipeline of several components with the goal to organize and filter the data for the AM, then to reconstruct and filter the final tracks. This document presents an overview of the system and reports the status of the different elements of the system