7 research outputs found

    Precise mapping of the magnetic field in the CMS barrel yoke using cosmic rays

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    This is the Pre-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2010 IOPThe CMS detector is designed around a large 4 T superconducting solenoid, enclosed in a 12 000-tonne steel return yoke. A detailed map of the magnetic field is required for the accurate simulation and reconstruction of physics events in the CMS detector, not only in the inner tracking region inside the solenoid but also in the large and complex structure of the steel yoke, which is instrumented with muon chambers. Using a large sample of cosmic muon events collected by CMS in 2008, the field in the steel of the barrel yoke has been determined with a precision of 3 to 8% depending on the location.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

    Software performance of the ATLAS track reconstruction for LHC run 3

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    Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pileup) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60 pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two

    Search for heavy Majorana or Dirac neutrinos and right-handed W gauge bosons in final states with charged leptons and jets in pp collisions at √s = 13 TeV with the ATLAS detector

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    A search for heavy right-handed Majorana or Dirac neutrinos NR and heavy right-handed gauge bosons WR is performed in events with energetic electrons or muons, with the same or opposite electric charge, and energetic jets. The search is carried out separately for topologies of clearly separated final-state products (“resolved” channel) and topologies with boosted final states with hadronic and/or leptonic products partially overlapping and reconstructed as a large-radius jet (“boosted” channel). The events are selected from pp collision data at the LHC with an integrated luminosity of 139 fb−1 collected by the ATLAS detector at √s = 13 TeV. No significant deviations from the Standard Model predictions are observed. The results are interpreted within the theoretical framework of a left-right symmetric model, and lower limits are set on masses in the heavy righthanded WR boson and NR plane. The excluded region extends to about m(WR) = 6.4 TeV for both Majorana and Dirac NR neutrinos at m(NR) < 1 TeV. NR with masses of less than 3.5 (3.6) TeV are excluded in the electron (muon) channel at m(WR) = 4.8 TeV for the Majorana neutrinos, and limits of m(NR) up to 3.6 TeV for m(WR) = 5.2 (5.0) TeV in the electron (muon) channel are set for the Dirac neutrinos. These constitute the most stringent exclusion limits to date for the model considered

    Observation of four-top-quark production in the multilepton final state with the ATLAS detector

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    This paper presents the observation of four-top-quark (tt¯tt¯) production in proton-proton collisions at the LHC. The analysis is performed using an integrated luminosity of 140 fb−1 at a centre-of-mass energy of 13 TeV collected using the ATLAS detector. Events containing two leptons with the same electric charge or at least three leptons (electrons or muons) are selected. Event kinematics are used to separate signal from background through a multivariate discriminant, and dedicated control regions are used to constrain the dominant backgrounds. The observed (expected) significance of the measured tt¯tt¯ signal with respect to the standard model (SM) background-only hypothesis is 6.1 (4.3) standard deviations. The tt¯tt¯ production cross section is measured to be 22.5+6.6−5.5 fb, consistent with the SM prediction of 12.0±2.4 fb within 1.8 standard deviations. Data are also used to set limits on the three-top-quark production cross section, being an irreducible background not measured previously, and to constrain the top-Higgs Yukawa coupling and effective field theory operator coefficients that affect tt¯tt¯ production

    WebCEMiTool: Co-expression modular analysis made easy

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    Co-expression analysis has been widely used to elucidate the functional architecture of genes under different biological processes. Such analysis, however, requires substantial knowledge about programming languages and/or bioinformatics skills. We present webCEMiTool,1 a unique online tool that performs comprehensive modular analyses in a fully automated manner. The webCEMiTool not only identifies co-expression gene modules but also performs several functional analyses on them. In addition, webCEMiTool integrates transcriptomic data with interactome information (i.e., protein-protein interactions) and identifies potential hubs on each network. The tool generates user-friendly html reports that allow users to search for specific genes in each module, as well as check if a module contains genes overrepresented in specific pathways or altered in a specific sample phenotype. We used webCEMiTool to perform a modular analysis of single-cell RNA-seq data of human cells infected with either Zika virus or dengue virus

    Whole-genome sequencing reveals host factors underlying critical COVID-19

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    Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

    Performance of the reconstruction of large impact parameter tracks in the inner detector of ATLAS

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    Searches for long-lived particles (LLPs) are among the most promising avenues for discovering physics beyond the Standard Model at the Large Hadron Collider (LHC). However, displaced signatures are notoriously difficult to identify due to their ability to evade standard object reconstruction strategies. In particular, the ATLAS track reconstruction applies strict pointing requirements which limit sensitivity to charged particles originating far from the primary interaction point. To recover efficiency for LLPs decaying within the tracking detector volume, the ATLAS Collaboration employs a dedicated large-radius tracking (LRT) pass with loosened pointing requirements. During Run 2 of the LHC, the LRT implementation produced many incorrectly reconstructed tracks and was therefore only deployed in small subsets of events. In preparation for LHC Run 3, ATLAS has significantly improved both standard and large-radius track reconstruction performance, allowing for LRT to run in all events. This development greatly expands the potential phase-space of LLP searches and streamlines LLP analysis workflows. This paper will highlight the above achievement and report on the readiness of the ATLAS detector for track-based LLP searches in Run 3
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