109963054
Online neural trigger for optimizing data acquisition during particle beam calibration tests with calorimeters
For LHC, the hadronic calorimetry of the ATLAS detector is performed by Tilecal, a scintillating tile calorimeter. For calibration purposes, a fraction of the Tilecal modules is placed in particle beam lines. Despite beam high quality, experimental beam contamination is observed and this masks the actual performance of the calorimeter. For optimizing the calibration task, an online neural particle classifier was developed for Tilecal. Envisaging a neural trigger for incoming particles, a neural process runs integrated to the data acquisition task and performs online training for particle identification. The neural classification performance is evaluated by correlating the neural response to classical methodology, confirming an ability for outsider identification at levels as high as 99.3%.
125435377
The Production and Qualification of Scintillator Tiles for the ATLAS Hadronic Calorimeter
120805024
Search for First Generation Scalar Leptoquarks in pp Collisions at $\sqrt{s}=7$ TeV with the ATLAS Detector
We report a search for first generation scalar leptoquarks using 1.03 fb−1 of proton–proton collisions data produced by the Large Hadron Collider at and recorded by the ATLAS experiment. Leptoquarks are sought via their decay into an electron or neutrino and a quark, producing events with two oppositely charged electrons and at least two jets, or events with an electron, missing transverse momentum and at least two jets. Control data samples are used to validate background predictions from Monte Carlo simulation. In the signal region, the observed event yields are consistent with the background expectations. We exclude at 95% confidence level the production of first generation scalar leptoquark with masses when assuming the branching fraction of a leptoquark to a charged lepton is equal to 1.0 (0.5).
108026736
A hybrid training method for neural energy estimation in calorimetry
A neural mapping is developed to improve the overall performance of Tilecal, which is the hadronic calorimeter of the ATLAS detector. Feeding the input nodes of a multilayer feedforward neural network with the energy values sampled by the calorimeter cells in beam tests, it is shown that the original energy scale of pion beams is reconstructed over a wide energy range and linearity is significantly improved. As it happens for classical methods, a compromise between nonlinearity correction and the optimization of the energy resolution of the detector has to be accomplished. A hybrid training method for the neural mapping is proposed to achieve this design goal. Using the back-propagation algorithm, the method intercalates an epoch of training steps, for which the neural mapping mainly focus on linearity correction, with another block of training steps, in which the original energy resolution obtained by linearly combining the calorimeter cells becomes the main target.
17177612
The optical instrumentation of the ATLAS Tile Calorimeter
The Tile Calorimeter, covering the central region of the ATLAS experiment up to pseudorapidities of +/-1.7, is a sampling device built with scintillating tiles that alternate with iron plates. The ...
126420285
Table 55 ; Measurement of the pseudorapidity and transverse momentum dependence of the elliptic flow of charged particles in lead-lead collisions at $\sqrt{s_{NN}}=2.76$ TeV with the ATLAS detector
123129833
Commissioning and performance of the CMS pixel tracker with cosmic ray muons
The pixel detector of the Compact Muon Solenoid experiment consists of three barrel layers and two disks for each endcap. The detector was installed in summer 2008, commissioned with charge injections, and operated in the 3.8 T magnetic field during cosmic ray data taking. This paper reports on the first running experience and presents results on the pixel tracker performance, which are found to be in line with the design specifications of this detector. The transverse impact parameter resolution measured in a sample of high momentum muons is 18 microns.
209834924
Performance of CMS Muon Reconstruction in Cosmic-Ray Events
The performance of muon reconstruction in CMS is evaluated using a large data sample of cosmic-ray muons recorded in 2008. Efficiencies of various high-level trigger, identification, and reconstruction algorithms have been measured for a broad range of muon momenta, and were found to be in good agreement with expectations from Monte Carlo simulation. The relative momentum resolution for muons crossing the barrel part of the detector is better than 1% at 10 GeV/c and is about 8% at 500 GeV/c, the latter being only a factor of two worse than expected with ideal alignment conditions. Muon charge misassignment ranges from less than 0.01% at 10 GeV/c to about 1% at 500 GeV/c.
118621663
The Landau gauge gluon propagator at zero and finite temperature: accounting for the combined finite lattice spacing and finite volume effects
In the past years a good comprehension of the infrared gluon propagator has been achieved, with a good qualitative agreement between lattice results and Dyson-Schwinger equations. However, lattice simulations have been performed at physical volumes which are close to 20 fm but using a large lattice spacing. The interplay between volume effects and lattice spacing effects has not been investigated. Here we aim to fill this gap and address how the two effects change the gluon propagator in the infrared region. Furthermore, we provide infinite volume extrapolations which take into account the finite volume and finite lattice spacing . We also report on preliminary results for the gluon propagator at finite temperature.
33567845
The CMS Electromagnetic Calorimeter Data Acquisition System at the 2006 Test Beam.
The electromagnetic calorimeter of the CMS experiment at CERN is an homogeneous calorimeter made of about 80000 Lead Tungstate crystals, that will start to operate at the LHC at the end of 2007. From June to November 2006, ten barrel Supermodules (1700 crystals each) were exposed to beam at CERN SPS, both in standalone and in association with portions of the Hadron Calorimeter. We present the description of the system used to configure and readout the calorimeter during the campaign. The full set of final readout electronics boards was employed, together with the pre-series version of the data acquisition software. During the campaign, the hardware and software concepts for the final system were validated. The system allowed the intercalibration of the ten Supermodules and allowed to perform several important studies of the detector performances, such as energy resolution, response linearity and radiation-hardness.
209834953
Commissioning of the CMS High-Level Trigger with Cosmic Rays
The CMS High-Level Trigger (HLT) is responsible for ensuring that data samples with potentially interesting events are recorded with high efficiency and good quality. This paper gives an overview of the HLT and focuses on its commissioning using cosmic rays. The selection of triggers that were deployed is presented and the online grouping of triggered events into streams and primary datasets is discussed. Tools for online and offline data quality monitoring for the HLT are described, and the operational performance of the muon HLT algorithms is reviewed. The average time taken for the HLT selection and its dependence on detector and operating conditions are presented. The HLT performed reliably and helped provide a large dataset. This dataset has proven to be invaluable for understanding the performance of the trigger and the CMS experiment as a whole.