Journal
PHYSICAL REVIEW D
Volume 85, Issue 5, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevD.85.052002
Keywords
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Funding
- U.S. Department of Energy
- National Science Foundation
- Italian Istituto Nazionale di Fisica Nucleare
- Ministry of Education, Culture, Sports, Science and Technology of Japan
- Natural Sciences and Engineering Research Council of Canada
- National Science Council of the Republic of China
- Swiss National Science Foundation
- A. P. Sloan Foundation
- Bundesministerium fur Bildung und Forschung, Germany
- Korean World Class University, the National Research Foundation of Korea
- Science and Technology Facilities Council
- Royal Society, UK
- Institut National de Physique Nucleaire et Physique des Particules/CNRS
- Russian Foundation for Basic Research
- Ministerio de Ciencia e Innovacion, and Programa Consolider-Ingenio, Spain
- Slovak Ramp
- D Agency
- Academy of Finland
- Australian Research Council (ARC)
- ICREA Funding Source: Custom
- STFC [ST/H001069/2, ST/H001026/2, ST/H001026/1] Funding Source: UKRI
- Science and Technology Facilities Council [ST/H001026/1, ST/H001069/2, ST/M001474/1, ST/K001418/1, ST/H001026/2] Funding Source: researchfish
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We present a search for the standard model Higgs boson production in association with a W boson in proton-antiproton collisions (p (p) over bar -> W+ H -> lvb (b) over bar) at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector which correspond to an integrated luminosity of approximately 2.7 fb(-1). We recorded this data with two kinds of triggers. The first kind required high-p(T) charged leptons and the second required both missing transverse energy and jets. The search selects events consistent with a signature of a single lepton (e(+/-)/mu(+/-)),missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method and a jet probability tagging method. Kinematic information is fed in an artificial neural network to improve discrimination between signal and background. The search finds that both the observed number of events and the neural network output distributions are consistent with the standard model background expectations, and sets 95% confidence level upper limits on the production cross section times branching ratio. The limits are expressed as a ratio to the standard model production rate. The limits range from 3.6 (4.3 expected) to 61.1 (43.2 expected) for Higgs masses from 100 to 150 GeV/c(2), respectively.
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