Hough Transform Track Reconstruction in the Cathode Strip Chambers in ATLAS

The world's largest and highest energy particle accelerator, the Large Hadron Collider (LHC), will collide two highly energetic proton beams in an attempt to discover a wide range of new physics. Among which, the primary ambitions are the discovery of the Higgs boson and suppersymmetric particles. ATLAS, one of its primary particle detectors, was designed as a general-purpose detector covering a broad range of energies and physical processes. A special emphasis on accurate muon tracking has led the ATLAS collaboration to design a stand-alone Muon Spectrometer, an extremely large tracking system extending all the way around the detector. Due to its immense size and range, parts of the spectrometer were designed to withstand a high rate of radiation, sifting the muon signals from the rest of the signals (primarily neutrons and photons). The Cathode Strip Chambers (CSCs) are special multiwire proportional chambers placed in the high $\eta$ region on of the Muon Spectrometer, where flux of background particles is highest. Their purpose is to efficiently filter out the background particle, tracking only the muons traversing it with high degree of accuracy. In order to do that, this special algorithm was designed using a novel modification of the Hough Transform. This thesis will detail the key elements of this algorithm, how it is used for better muon track detection and parameterization, and give a preliminary evaluation of the perform ance of this algorithm

The use of cluster quality for track fitting in the CSC detector

The new particle accelerators and its experiments create a challenging data processing environment, characterized by large amount of data where only small portion of it carry the expected new scientific information. Modern detectors, such as the Cathode Strip Chamber (CSC), achieve high accuracy of coordinate measurements (between 50 to 70 microns). However, heavy physical backgrounds can decrease the accuracy significantly. In the presence of such background, the charge induced over adjacent CSC strips (cluster) is different from the ideal Matheison distribution. The traditional least squares method which takes the same ideal position error for all clusters loses its optimal properties on contaminated data. A new technique that calculates the cluster quality and uses it to improve the track fitting results is suggested. The algorithm is applied on test beam data, and its performance is compared to other fitting methods. It is shown that the suggested algorithm improves the fitting performance significantly.Comment: Proceedings of 2006 IEEE NSS, San Diego, California, USA, November 200

Position resolution and efficiency measurements with large scale Thin Gap Chambers for the super LHC

New developments in Thin Gap Chambers (TGC) detectors to provide fast trigger and high precision muon tracking under sLHC conditions are presented. The modified detectors are shown to stand a high total irradiation dose equivalent to 6 Coulomb/cm of wire, without showing any deterioration in their performance. Two large (1.2 x 0.8 m^2) prototypes containing four gaps, each gap providing pad, strips and wires readout, with a total thickness of 50 mm, have been constructed. Their local spatial resolution has been measured in a 100 GeV/c muon test beam at CERN. At perpendicular incidence angle, single gap position resolution better than 60 microns has been obtained. For incidence angle of 20 degrees resolution of less than 100 micron was achieved. TGC prototypes were also tested under a flux of 10^5 Hz/cm^2 of 5.5-6.5 MeV neutrons, showing a high efficiency for cosmic muons detection.Comment: Presented at the 12 Vienna conference on Instrumentation, February 201

b and c physics with early ATLAS data

Conference slides for Physics at LHC 201

b and c physics with early ATLAS data

Studies of the first J/psi --> mu+ mu- and D*+-, D+- and D(s)+- observations using the ATLAS detector, in 7-TeV proton-proton collisions at the LHC, is reported

Tuftsin-Phosphorylcholine Maintains Normal Gut Microbiota in Collagen Induced Arthritic Mice

Rheumatoid arthritis (RA) is characterized by chronic autoinflammation of the joints, with a prevalence of about 1% in Western populations. Evidence in recent years has linked RA to changes in the gut microbiota (dysbiosis). Interestingly, helminths have been shown to have therapeutic activity in RA. Specifically, a glycoprotein containing phosphorylcholine (PC) extracted from helminths was found to have immunomodulatory activity. We have previously developed a novel chimeric compound composed of tuftsin-PC (TPC) that attenuates the joint destruction in mice with collagen-induced arthritis (CIA). Here, we address the interrelationship between TPC immunomodulatory activity and the gut microbiota in CIA mice. Preventive therapy with TPC in mice with arthritis maintained a physiological arthritis score as well as a steady gut microbial environment, similar to that of healthy controls, in contrast to CIA mice with severe disease. The microbial composition differed significantly between healthy and phosphate-buffered saline-treated CIA mice, enabling classifying test samples by machine learning based on levels of a small number of bacterial species. Using these bacterial biomarkers, all TPC-treated CIA mice were classified as healthy. Thus, we describe a clear correlation between TPC treatment, healthy gut microbial communities, and prevention of arthritis. This is the first study to demonstrate the immunomodulatory effect of helminth derivatives in autoimmune diseases and the link to gut microbiota