Search for a W ' boson decaying to a muon and a neutrino in pp collisions at √s =7 TeV

This is the Pre-Print version of the Article. The official published version can be accessed from the link below - Copyright @ 2011 ElsevierA new heavy gauge boson, W', decaying to a muon and a neutrino, is searched for in pp collisions at a centre-of-mass of 7 TeV. The data, collected with the CMS detector at the LHC, correspond to an integrated luminosity of 36 inverse picobarns. No significant excess of events above the standard model expectation is found in the transverse mass distribution of the muon-neutrino system. Masses below 1.40 TeV are excluded at the 95% confidence level for a sequential standard-model-like W'. The W' mass lower limit increases to 1.58 TeV when the present analysis is combined with the CMS result for the electron channel.This work is supported by the 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 and WCU (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); MSTD (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

Transverse-momentum and pseudorapidity distributions of charged hadrons in pp collisions at √s=7 TeV

Charged-hadron transverse-momentum and pseudorapidity distributions in proton-proton collisions at root s = 7 TeV are measured with the inner tracking system of the CMS detector at the LHC. The charged-hadron yield is obtained by counting the number of reconstructed hits, hit pairs, and fully reconstructed charged-particle tracks. The combination of the three methods gives a charged-particle multiplicity per unit of pseudorapidity dN(ch)/d eta vertical bar(vertical bar eta vertical bar<0.5) = 5.78 +/- 0.01(stat) +/- 0.23(stat) for non-single-diffractive events, higher than predicted by commonly used models. The relative increase in charged-particle multiplicity from root s = 0.9 to 7 TeV is [66.1 +/- 1.0(stat) +/- 4.2(syst)]%. The mean transverse momentum is measured to be 0.545 +/- 0.005(stat) +/- 0.015(syst) GeV/c. The results are compared with similar measurements at lower energies

Performance of the CMS Level-1 trigger during commissioning with cosmic ray muons and LHC beams

This is the Pre-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2010 IOPThe CMS Level-1 trigger was used to select cosmic ray muons and LHC beam events during data-taking runs in 2008, and to estimate the level of detector noise. This paper describes the trigger components used, the algorithms that were executed, and the trigger synchronisation. Using data from extended cosmic ray runs, the muon, electron/photon, and jet triggers have been validated, and their performance evaluated. Efficiencies were found to be high, resolutions were found to be good, and rates as expected.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)

Performance study of the CMS barrel resistive plate chambers with cosmic rays

This is the Pre-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2010 IOPIn October and November 2008, the CMS collaboration conducted a programme of cosmic ray data taking, which has recorded about 270 million events. The Resistive Plate Chamber system, which is part of the CMS muon detection system, was successfully operated in the full barrel. More than 98% of the channels were operational during the exercise with typical detection efficiency of 90%. In this paper, the performance of the detector during these dedicated runs is reported.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)

Performance of the CMS hadron calorimeter with cosmic ray muons and LHC beam data

This is the Pre-print version of the Article. The official published version of the Paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS Hadron Calorimeter in the barrel, endcap and forward regions is fully commissioned. Cosmic ray data were taken with and without magnetic field at the surface hall and after installation in the experimental hall, hundred meters underground. Various measurements were also performed during the few days of beam in the LHC in September 2008. Calibration parameters were extracted, and the energy response of the HCAL determined from test beam data has been checked.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)

Exclusive gamma gamma -> mu(+)mu(-) production in proton-proton collisions at root s=7TeV

A measurement of the exclusive two-photon production of muon pairs in proton-proton collisions at root s = 7 TeV, pp -> p mu(+)mu(-) p, is reported using data corresponding to an integrated luminosity of 40 pb-1. For muon pairs with invariant mass greater than 11.5 GeV, transverse momentum p(T)(mu) > 4 GeV and pseudorapidity 1770.1) p mu(+)mu(-) p) - 3.38(-0.55)(+0.58) (stat.)+/- 0.16 (syst.) +/- 0.14 (lumi.) pb, consistent with the theoretical prediction evaluated with the event generator LPAIR. The ratio to the predicted cross section is 0.83+(0.14)(-0.13) (stat.) +/- 0.04 (syst.) +/- 0.03 (lumi.). The characteristic distributions of the muon pairs produced via Ty fusion, such as the muon acoplanarity, the muon pair invariant mass and transverse momentum agree with those from the theory

The comparative role of key environmental factors in determining savanna productivity and carbon fluxes: a review, with special reference to northern Australia

Terrestrial ecosystems are highly responsive to their local environments and, as such, the rate of carbon uptake both in shorter and longer timescales and different spatial scales depends on local environmental drivers. For savannas, the key environmental drivers controlling vegetation productivity are water and nutrient availability, vapour pressure deficit (VPD), solar radiation and fire. Changes in these environmental factors can modify the carbon balance of these ecosystems. Therefore, understanding the environmental drivers responsible for the patterns (temporal and spatial) and processes (photosynthesis and respiration) has become a central goal in terrestrial carbon cycle studies. Here we have reviewed the various environmental controls on the spatial and temporal patterns on savanna carbon fluxes in northern Australia. Such studies are critical in predicting the impacts of future climate change on savanna productivity and carbon storage

Conundrums in mixed woody-herbaceous plant systems

International audienceAims To identify approaches to improve our understanding of, and predictive capability for, mixed tree-grass systems. Elucidation of the interactions, dynamics and determinants, and identification of robust generalizations that can be broadly applied to tree-grass systems would benefit ecological theory, modelling and land management. Methods A series of workshops brought together scientific expertise to review theory, data availability, modelling approaches and key questions. Location Ecosystems characterized by mixtures of herbaceous and woody plant life-forms, often termed 'savannas', range from open grasslands with few woody plants, to woodlands or forests with a grass layer. These ecosystems represent a substantial portion of the terrestrial biosphere, an important wildlife habitat, and a major resource for provision of livestock, fuel wood and other products. Results Although many concepts and principles developed for grassland and forest systems are relevant to these dual life-form communities, the novel, complex, nonlinear behaviour of mixed tree-grass systems cannot be accounted for by simply studying or modelling woody and herbaceous components independently. A more robust understanding requires addressing three fundamental conundrums: (1) The 'treeness' conundrum. What controls the relative abundance of woody and herbaceous plants for a given set of conditions at given site? (2) The coexistence conundrum. How do the life-forms interact with each other? Is a given woody-herbaceous ratio dynamically stable and persistent under a particular set of conditions? (3) The net primary productivity (NPP) conundrum. How does NPP of the woody vegetation, the herbaceous vegetation, and the total ecosystem (woody + herbaceous) change with changes in the tree-grass ratio? Tests of the theory and conceptual models of determinants of mixed woody-herbaceous systems have been largely site- or region-specific and have seldom been broadly or quantitatively evaluated. Cross-site syntheses based on data and modelling are required to address the conundrums and identify emerging patterns, yet, there are very few data sets for which either biomass or NPP have been quantified for both the woody and the herbaceous components of tree-grass systems. Furthermore, there are few cross-site comparisons spanning the diverse array of woody-herbaceous mixtures. Hence, initial synthesis studies should focus on compiling and standardizing a global data base which could be (1) explored to ascertain if robust generalizations and consistent patterns exist; and (2) used to evaluate the performance of savanna simulation models over a range of woody-herbaceous mixtures. Savanna structure and productivity are the result of complex and dynamic interactions between climate, soils and disturbances, notably fire and herbivory. Such factors are difficult to isolate or experimentally manipulate in order to evaluate their impacts at spatial and temporal scales appropriate for assessing ecosystem dynamics. These factors can, however, be evaluated with simulation models. Existing savanna models vary markedly with respect to their conceptual approach, their data requirements and the extent to which they incorporate mechanistic processes. Model intercomparisons can elucidate those approaches most suitable for various research questions and management applications. Conclusion Theoretical and conceptual advances could be achieved by considering a broad continuum of grass-shrub-tree combinations using data meta-analysis techniques and modelling