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ATLAS is one of the four major Large Hadron Collider (LHC) experiments that will start data taking in 2007. It is designed to cover a wide range of physics topics. The ATLAS trigger system has to be able to reduce an initial 40 MHz event rate, corresponding to an average of 23 proton-proton inelastic interactions per every 25 ns bunch crossing, to 200 Hz admissible by the Data Acquisition System. The ATLAS trigger is divided in three different levels. The first one provides a signal describing an event signature using dedicated custom hardware. This signature must be confirmed by the High Level Trigger (HLT) which using commercial computing farms performs an event reconstruction by running a sequence of algorithms. The validity of a signature is checked after every algorithm execution. A main characteristic of the ATLAS HLT is that only the data in a certain window around the position flagged by the first level trigger are analyzed. In this work, the performance of one sequence that runs at the Event Filter level (third level) is demonstrated. The goal of this sequence is to reconstruct and identify high transverse momentum electrons by performing cluster reconstruction at the electromagnetic calorimeter, track reconstruction at the Inner Detector, and cluster track matching. © 2006 IEEE.

The ATLAS experiment at the Large Hadron Collider (LHC) will face the challenge of efficiently selecting interesting candidate events in pp collisions at 14 TeV center-of-mass energy, whilst rejecting the enormous number of background events. The High-Level Trigger (HLT = second level trigger and Event Filter), which is a software based trigger will need to reduce the level-1 output rate of ≈ 75 kHz to ≈ 200 Hz written out to mass storage. In this talk an overview of the current physics and system performance of the HLT selection for electrons and photons is given. The performance has been evaluated using Monte Carlo simulations and has been partly demonstrated in the ATLAS testbeam in 2004. The efficiency for the signal channels, the rate expected for the selection, the global data preparation and execution times will be highlighted. Furthermore, some physics examples will be discussed to demonstrate that the triggers are well adapted for the physics programme envisaged at the LHC. © 2005 IEEE.

The ATLAS combined test beam in the second half of 2004 saw the first deployment of the ATLAS High-Level Triggers (HLT). The next steps are deployment on the pre-series farms in the experimental area during 2005, commissioning and cosmics tests in 2006 and collisions in 2007. This paper reviews the experience gained in the test beam, describes the current status and discusses the further enhancements to be made. We address issues related to the dataflow, selection algorithms, testing, software distribution, installation and improvements. © 2005 IEEE.

The Large Hadron Collider at CERN offers unprecedented challenges to the design and construction of detectors and trigger/data acquisition systems. For ATLAS, a three level trigger system has been developed to extract interesting physics signatures with a 106 rate reduction. To accomplish this, components of physics analysis traditionally deferred to offline physics analysis must be embedded within the online trigger system. For the Muon trigger, the specific off-line algorithms MOORE (Muon Object Oriented REconstruction) and MuId (Muon Iden tification) have been adopted so far for the on-line use, imposing an operation in a Bayesian-like environment where only specific hypotheses must be validated. After a short review of the ATLAS trigger, the paper shows the general strategy of the Muon Identification and Selection accessing the full event data, or being seeded from results derived at a previous stage of the trigger chain. © 2005 IEEE.

The ATLAS trigger reduces the rate of interesting events to be recorded for off-line analysis in three successive levels from 40 MHz to ∼ 100 kHz, ∼ 2 kHz and ∼ 200 Hz. The high level triggers and data acquisition system are designed to profit from commodity computing and networking components to achieve the required performance. In this paper, we discuss data flow aspects of the design of the second level trigger (LVL2) and present results of performance measurements.

The Liquid Argon calorimeters play a central role in the ATLAS experiment. The environment at the LHC collider imposes challenging tasks to their read-out system. To achieve measurements of particles and trigger signals at high precision, the detector signals are processed at various stages before reaching the Data Acquisition system (DAQ). Signals from the calorimeter cells are received by front-end boards, which digitize and sample the incoming pulse. Read-out Driver (ROD) boards further process the data at a trigger rate of up to 75 kHz. An optimal filtering procedure is applied to optimize the signal-to-noise ratio. The ROD boards calculate precise energy, time and quality of the detector pulse, which are then sent to the DAQ. In addition, the RODs perform a monitoring of the data. The architecture of the ATLAS Liquid Argon detector read-out is discussed, in particular the design and functionality of the ROD board. Performance results obtained with ROD prototypes as well as experience from complete test setups with final production boards are reported. Index Terms--Data processing, digital signal processors, digital systems, filters, real time systems, signal processing.

The trigger system of the ATLAS experiment at the LHC aims at a high selectivity in order to keep the full physics potential while reducing the 40 MHz initial event rate imposed by the LHC bunch crossing down to ~100 Hz, as required by the data acquisition system. Algorithms working in the final stage of the trigger environment (Event Filter) are implemented to run both in a 'wrapped' mode (reconstructing tracks in the entire Muon Spectrometer) and in a 'seeded' mode (according to a dedicated strategy that performs pattern recognition only in regions of the detector where trigger hypotheses have been produced at earlier stages). The working principles of the offline muon reconstruction and identification algorithms (MOORE and MuId) implemented and used in the framework of the Event Filter are discussed in this paper. The reconstruction performance of these algorithms is presented for both modes in terms of efficiency, momentum resolution, rejection power and execution times on several samples of simulated single muon events, also taking into account the high background environment expected for ATLAS. Index Terms--ATLAS, event filter, HLT, Muons.

The Event Filter (EF) selection stage is a fundamental L component of the ATLAS Trigger and Data Acquisition architecture. Its primary function is the reduction of data flow and rate to values acceptable by the mass storage operations and by the subsequent offline data reconstruction and analysis steps. The computing instrument of the EF is organized as a set of independent subfarms, each connected to one output of the Event Builder (EB) switch fabric. Each subfarm comprises a number of processors analyzing several complete events in parallel. This paper describes the design of the ATLAS EF system, its deployment in the 2004 ATLAS combined test beam together with some examples of integrating selection and monitoring algorithms. Since the processing algorithms are not explicitly designed for EF but are adapted from the offline ones, special emphasis is reserved to system reliability and data security, in particular for the case of failures in the processing algorithms. Other key design elements have been system modularity and scalability. The EF shall be able to follow technology evolution and should allow for using additional processing resources possibly remotely located. Index Terms--Data acquisition, data processing, triggering.

The ATLAS High Level Trigger's (HLT) primary function of event selection will be accomplished with a Level-2 trigger farm and an event filter (EF) farm, both running software components developed in the ATLAS offline reconstruction framework. While this approach provides a unified software framework for event selection, it poses strict requirements on offline components critical for the Level-2 trigger. A Level-2 decision in ATLAS must typically be accomplished within 10 ms and with multiple event processing in concurrent threads. To address these constraints, prototypes have been developed that incorporate elements of the ATLAS data flow, high level trigger, and offline framework software. To realize a homogeneous software environment for offline components in the HLT, the Level-2 Steering Controller was developed. With electron/gamma-and muon-selection slices it has been shown that the required performance can be reached, if the offline components used are carefully designed and optimized for the application in the HLT. Index Terms--Programming environments, software reusability, triggering.

Following rigorous software design and analysis methods, an object-based architecture has been developed to derive the second- and third-level trigger decisions for the future ATLAS detector at the LHC. The functional components within this system responsible for generating elements of the trigger decisions are algorithms running within the software architecture. Relevant aspects of the architecture are reviewed along with concrete examples of specific algorithms and their performance in 'vertical' slices of various physics selection strategies. Index Terms--Algorithms, online reconstruction, trigger.

To cope with the 40 MHz event production rate of LHC, the trigger of the ATLAS experiment selects events in three sequential steps of increasing complexity and accuracy whose final results are close to the offline reconstruction. The Level-1, implemented with custom hardware, identifies physics objects within Regions of Interests and operates with a first reduction of the event rate to 75 kHz. The higher trigger levels, Level-2 and Level-3, provide a software based event selection which further reduces the event rate to about 100 Hz. This paper presents the algorithm (μFast) employed at Level-2 to confirm the muon candidates flagged by the Level-1. μFast identifies hits of muon tracks inside the barrel region of the Muon Spectrometer and provides a precise measurement of the muon momentum at the production vertex. The algorithm must process the Level-1 muon output rate (∼20 kHz), thus particular care has been taken for its optimization. The result is a very fast track reconstruction algorithm with good physics performance which, in some cases, approaches that of the offline reconstruction: it finds muon tracks with an efficiency of about 95% and computes PT of prompt muons with a resolution of 5.5% at 6 GeV and 4.0% at 20 GeV. The algorithm requires an overall execution time of ∼1 ms on a 100 SpecInt95 machine and has been tested in the online environment of the Atlas detector test beam. [ABSTRACT FROM AUTHOR]