302 research outputs found

    Statistics of Wave Functions in Coupled Chaotic Systems

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    Using the supersymmetry technique, we calculate the joint distribution of local densities of electron wavefunctions in two coupled disordered or chaotic quantum billiards. We find novel spatial correlations that are absent in a single chaotic system. Our exact result can be interpreted for small coupling in terms of the hybridization of eigenstates of the isolated billiards. We show that the presented picture is universal, independent of microscopic details of the coupling.Comment: 4 pages, 2 figures; acknowledgements and references adde

    Measurements of the Q2Q^2-Dependence of the Proton and Neutron Spin Structure Functions g1p and g1n

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    The structure functions g1p and g1n have been measured over the range 0.014 < x < 0.9 and 1 < Q2 < 40 GeV2 using deep-inelastic scattering of 48 GeV longitudinally polarized electrons from polarized protons and deuterons. We find that the Q2 dependence of g1p (g1n) at fixed x is very similar to that of the spin-averaged structure function F1p (F1n). From a NLO QCD fit to all available data we find Γ1pΓ1n=0.176±0.003±0.007\Gamma_1^p - \Gamma_1^n =0.176 \pm 0.003 \pm 0.007 at Q2=5 GeV2, in agreement with the Bjorken sum rule prediction of 0.182 \pm 0.005.Comment: 17 pages, 3 figures. Submitted to Physics Letters

    Measurement of the mass difference between top quark and antiquark in pp collisions at root s=8 TeV

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    The genetic architecture of the human cerebral cortex

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    INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function

    Observation of a peaking structure in the J/psi phi mass spectrum from B(+/-) to J/psi phi K(+/-) decays

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    Measurement of the production cross section for a W boson and two b jets in pp collisions at root s=7 TeV

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    The production cross section for a W boson and two b jets is measured using proton&#8211;proton collisions at s=7 TeV in a data sample collected with the CMS experiment at the LHC corresponding to an integrated luminosity of 5.0 fb &#8722;1 . The W+bb¯ events are selected in the W&#8594;&#956;&#957; decay mode by requiring a muon with transverse momentum pT>25 GeV and pseudorapidity |&#951;|25 GeV and |&#951;|<2.4 . The measured W+bb¯ production cross section in the fiducial region, calculated at the level of final-state particles, is &#963;(pp&#8594;W+bb¯)×B(W&#8594;&#956;&#957;)=0.53±0.05(stat.)±0.09(syst.)±0.06(theo.)±0.01(lum.) pb , in agreement with the standard model prediction. In addition, kinematic distributions of the W+bb¯ system are in agreement with the predictions of a simulation using MadGraph and pythia

    Measurements of the t(t)Overbar charge asymmetry using the dilepton decay channel in pp collisions at root s=7 TeV

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    The tt¯ charge asymmetry in proton-proton collisions at s&#8730; = 7 TeV is measured using the dilepton decay channel (ee, e &#956; , or &#956;&#956; ). The data correspond to a total integrated luminosity of 5.0 fb &#8722;1 , collected by the CMS experiment at the LHC. The tt and lepton charge asymmetries, defined as the differences in absolute values of the rapidities between the reconstructed top quarks and antiquarks and of the pseudorapidities between the positive and negative leptons, respectively, are measured to be A C = &#8722;0 . 010 ± 0 . 017 (stat . ) ± 0 . 008 (syst . ) and AlepC = 0 . 009 ± 0 . 010 (stat . ) ± 0 . 006 (syst . ). The lepton charge asymmetry is also measured as a function of the invariant mass, rapidity, and transverse momentum of the tt¯ system. All measurements are consistent with the expectations of the standard model

    Studies of azimuthal dihadron correlations in ultra-central PbPb collisions at=2.76 TeV

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