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Abe, F.; Amidei, D.; Apollinari, G.; Ataç, M.; Auchincloss, P.; Baden, A.; Bacchetta, N.; Bailey, M. W.; Bamberger, A.; Barbaro, P. de; Barnett, B. A.; Barbaro‐Galtieri, A.; Barnes, V. E.; Baumann, Thomas; Bedeschi, F.; Behrends, S.; Belforte, S.; Bellettini, G.; Bellinger, J.; Benjamin, D.; Bensinger, J. R.; Beretvas, A.; Berge, J. P.; Bertolucci, S.; Bhadra, S.; Binkley, M.; Blair, R. E.; Blocker, C.; Bolognesi, V.; Booth, A. W.; Boswell, C.; Brandenburg, G.; Brown, D. N.; Buckley-Geer, E.; Budd, H. S.; Busetto, G.; Byon-Wagner, A.; Byrum, K. L.; Campagnari, C.; Campbell, M.; Caner, A.; Carey, Robert M.; Carithers, W.; Carlsmith, D.; Carroll, J. T.; Cashmore, R. J.; Castro, A.; Cervelli, F.; Chadwick, K.; Chiarelli, G.; Chinowsky, W.; Cihangir, S.; Clark, A.; Connor, D.; Contreras, M.; Cooper, J.; Cordelli, M.; Crane, D.; Curatolo, M.; Day, C.; DeJongh, F.; Dell’Agnello, S.; Dell’Orso, M.; Demortier, L.; Denby, B.; Derwent, P. F.; Devlin, T.; DiBitonto, D.; Dickson, M.; Drucker, R. B.; Einsweiler, K.; Elias, J. E.; Ely, R.; Eno, S. C.; Errede, S.; Esposito, B.; Flaugher, B.; Foster, G. W.; Franklin, M.; Freeman, J.; Frisch, H.; Fuess, T. A.; Fukui, Y.; Funayama, Y.; Garfinkel, A. F.; Gauthier, A.; Geer, S.; Gerdes, D. W.; Giannetti, P.; Giokaris, N.; Giromini, P.; Gladney, L.; Gold, M.; Goulianos, K.; Grassmann, H.; Grosso-Pilcher, C.; Haber, C.; Hahn, S. R.; Handler, R.; Hara, K.; Harris, R. M.; Hauser, J.; Hawk, C.; Hessing, T. L.; Hollebeek, R.; Hu, P.; Hubbard, B.; Huffman, B. T.; Hughes, R. E.; Hurst, P.; Huth, J.; Hylen, H.; Incagli, M.; Ino, T.; Iso, H.; Jensen, H.; Jessop, C.; Johnson, R. P.; Joshi, U.; Kadel, R. W.; Kamon, T.; Kanda, S.; Kardelis, D. A.; Karliner, I.; Kearns, E.; Keeble, L.; Kephart, R.; Kesten, P.; Keup, R. M.; Keutelian, H.; Kim, D.; Kim, S.; Kirsch, L.; Kondo, K.; Königsberg, J.; Kovacs, E.; Kuhlmann, S. E.; Kuns, E.; Laasanen, A. T.; Lamoureux, J. I.; Leone, S.; Lewis, J. D.; Li, W.; Liss, T. M.; Limon, P.; Lockyer, N. S.; Luchini, C. B.; Lukens, P.; Maas, P.; Mangano, M.; Marriner, J. P.; Mariotti, M.; Markeloff, R.; Markosky, L. A.; Mattingly, R.; McIntyre, P.; Menzione, A.; Meyer, T. C.; Mikamo, S.; Miller, Michael L.; Mimashi, T.; Miscetti, S.; Mishina, M.; Miyashita, S.; Morita, Y.; Moulding, S.; Muêller, J.; Mukherjee, A.; Nakae, L. F.; Nakano, I.; Nelson, Charles A.; Newman-Holmes, C.; Ng, J. S. T.; Ninomiya, M.; Nodulman, L.; Ogawa, S.; Paoletti, R.; Para, A.; Paré, E.; Park, Sung Keun; Patrick, J.; Phillips, T. J.; Plunkett, R.; Pondrom, L.; Proudfoot, J.; Ptohos, F.; Punzi, G.; Quarrie, D. R.; Ragan, K.; Redlinger, G.; Rhoades, J.; Roach, M.; Rimondi, F.; Ristori, L.; Rodrigo, T.; Rohaly, T.; Roodman, A.; Sakumoto, W. K.; Sansoni, A.; Sard, R. D.; Savoy-Navarro, A.; Scarpine, V.; Schlabach, P.; Schmidt, E. E.; Schneider, O.; Schub, M. H.; Schwitters, R. F.; Scribano, A.; Segler, S.; Seiya, Y.; Sekiguchi, M.; Shapiro, M.; Shaw, N. M.; Sheaff, M.; Schochet, M.; Siegrist, J.; Sinervo, P.; Skarha, J.; Sliwa, K.; Smith, D.; Snider, F. D.; Song, L.; Spahn, M.; Sphicas, P.; Denis, R. St.; Stefanini, A.; Sullivan, G. W.; Swartz, R. L.; Takano, Mikio; Tartarelli, G. F.; Takikawa, K.; Tarem, S.; Theriot, D.; Timko, M.; Tipton, P.; Tkaczyk, S.; Tollestrup, A.; Tonnison, J.; Trischuk, W.; Turini, N.; Tsay, Y.; Ukegawa, F.; Underwood, D. G.; Vejcik, S.; Vidal, R.; Wagner, R. G.; Wagner, R. L.; Wainer, N.; Walsh, J.; Watts, T.; Webb, R.; Wendt, C.; Wenzel, H.; Wester, W. C.; Westhusing, T.; White, S.; Wicklund, A. B.; Williams, H. H.; Winer, B. L.; Wyss, J.; Yagil, A.; Yamashita, A.; Yasuoka, K.; Yeh, G. P.; Yoh, J.; Yokoyama, Masaru; Yun, J. C.; Zanetti, A.; Zetti, F.; Zucchelli, S.

doi:10.1103/physrevd.45.1448

Cited by 300 publications

(137 citation statements)

References 18 publications

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“…We also require large missing transverse energy [14], E T > 20 GeV, and at least four jets. Jets are reconstructed with a cone algorithm [15] with radius R = (∆η) 2 + (∆φ) 2 = 0.4. In addition to the standard jet energy corrections [16], we train a neural network including additional information to the calorimeter one, such as jet momentum from the tracker as described in Ref.…”

mentioning

confidence: 99%

Precision Top-Quark Mass Measurement at CDF

Aaltonen¹,

González²,

Amerio³

et al. 2012

Phys. Rev. Lett.

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We present a precision measurement of the top-quark mass using the full sample of Tevatron √ s = 1.96 TeV proton-antiproton collisions collected by the CDF II detector, corresponding to an integrated luminosity of 8.7 fb −1 . Using a sample of tt candidate events decaying into the lepton+jets channel, we obtain distributions of the top-quark masses and the invariant mass of two jets from the W boson decays from data. We then compare these distributions to templates derived from signal and background samples to extract the top-quark mass and the energy scale of the calorimeter jets with in situ calibration. The likelihood fit of the templates from signal and background events to the data yields the single most-precise measurement of the top-quark mass, Mtop = 172.85 ± 0.71 (stat) ± 0.85 (syst) GeV/c 2 .PACS numbers: 14.65. Ha, 13.85.Ni, 13.85.Qk, 12.15.Ff The top quark (t) is by far the heaviest known elementary particle [1]. It contributes significantly to * Deceased † With visitors from

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confidence: 99%

Precision Top-Quark Mass Measurement at CDF

Aaltonen¹,

González²,

Amerio³

et al. 2012

Phys. Rev. Lett.

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“…We use the CTEQ6 [18] PDF sets. The Tevatron data in the plots have been obtained using the infrared-unsafe JETCLU jet algorithm [19]. We cannot use this algorithm in our NLO analysis, so we use the SISCONE [20] algorithm instead.…”

Section: Tevatron Resultsmentioning

confidence: 99%

Multi-jet processes at NLO

Maître¹,

Bern²,

Berger³

et al. 2010

Proceedings of European Physical Society Europhysics Conference on High Energy Physics — PoS(EPS-HEP 2009)

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In this contribution we present results from the NLO computation of the production of a W boson in association with three jets in hadronic collisions. The results are obtained by combining two programs: BlackHat for the virtual one-loop matrix elements and Sherpa for the realemission contributions. We present results for the Tevatron and the LHC, and address the issue of the choice of a common factorization and renormalization scale for this process.

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“…The most used jet algorithm at CDF is called JETCLU [58]. It belongs to the family of iterative fixed cone jet reconstruction algorithm and it is based only on calorimetric information.…”

Section: Jetsmentioning

confidence: 99%

Measurement of WW + WZ production cross section and study of the dijet mass spectrum in the ℓν + jets final state at CDF

Cavaliere

2010

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Topology of three-jet events inp¯pcollisions ats=<

Cited by 300 publications

References 18 publications

Precision Top-Quark Mass Measurement at CDF

Precision Top-Quark Mass Measurement at CDF

Multi-jet processes at NLO

Measurement of WW + WZ production cross section and study of the dijet mass spectrum in the ℓν + jets final state at CDF

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