Search

TileCal is the hadronic tile calorimeter of the ATLAS experiment at LHC/CERN. The central element of the back-end system of the TileCal detector is the Read-Out Driver (ROD).The main components of the TileCal ROD are the Digital Signal Processors (DSPs) placed on the Processing Unit (PU) daughterboards. This paper presents a detailed description of the code developed for the DSPs. The code is divided into two different parts: the first part contains the core functionalities and the second part the reconstruction algorithms. The core acts as an operating system and controls configuration, data reception and transmission and synchronization between front-end data and the Timing, Trigger and Control (TTC) information. The reconstruction algorithms implemented on the DSP are the Optimal Filtering (OF), Muon Tagging (MTag) and Missing ET calculation. The OF algorithm reconstructs the deposited energy and the phase of the signal for every calorimeter channel within a front-end module. This reconstructed energy is used by the MTag algorithm to tag low transverse momentum muons that may escape the ATLAS muon spectrometer Level 1 trigger whereas the Missing [E.sub.T] algorithm computes the total transverse energy and the projection on X and Y axis for the entire module that will be used by the Level 2 trigger system. Index Terms--ATLAS, digital signal processors, optimal filtering, read-out driver.

The ATLAS Hadronic Tile Calorimeter detector (TileCal) is an iron-scintillating tiles sampling calorimeter designed to operate at the Large Hadron Collider accelerator at CERN. The central element of the back-end system of the TileCal detector is a 9U VME Read-Out Driver (ROD) board. The operation of the TileCal calorimeter requires a total of 32 ROD boards. This paper summarizes the tests performed during the ROD production and the results obtained. Data processing is performed in the ROD by digital signal processors, whose operation is based on the use of online algorithms such as the optimal filtering algorithm for the signal amplitude, pedestal and time reconstruction and the online Muon tagging algorithm which identifies low transverse momentum muons. The initial performance of both algorithms run during commissioning is also presented in this paper. Index Terms--Data acquisition, data processing, electronic equipment testing, field programmable gate arrays, integrated circuit.

This paper describes the development of the optical multiplexer board (OMB), also known as PreROD board, for the TileCal readout system in the ATLAS experiment. The aim of this board is to overcome the problems that may arise in the integrity of data due to radiation effects. The solution adopted has been to add redundancy to data transmission and so two optical fibers with the same data come out from the detector front end boards. The OMB has to decide in real time which fiber, eventually, carries data with no errors switching it to the output link connected to the read out driver (ROD) motherboard where data processing takes place. Besides, the board may be also used as a data injector for testing purposes of the ROD motherboard. The paper describes the design and tests of the first prototype, implemented as a 6U VME64x slave module, including both hardware aspects, focusing on signal integrity problems, and firmware aspects, dealing with the cyclic redundancy code algorithms used to check data consistency used to make the decision. Index Terms--Data acquisition, fault tolerance, field programmable gate arrays, integrated circuit radiation effects.

We present an Optimal Filtering (OF) algorithm to reconstruct the energy, time and pedestal of a photomultiplier signal from its digital samples. The OF algorithm was first developed for liquid ionization calorimeters, its implementation in scintillator calorimeters, specifically in the ATLAS hadrouic Tile calorimeter (TileCal), is the aim of this study. The objective is to implement the algorithm on the DSPs of the Read Out Driver cards in order to reconstruct online the energy of the calorimeter and provide it to the second level trigger. The algorithm is tested and compared with a plain filtering algorithm using both calibration and real data from the TileCal detector. The results are promising specially in the regions where the electronic noise contributes significantly to the resolution.