Асосий контентга ўтиш
AkademIndex

Маҳсулотлар

Ишлаб чиқувчилар учун

AkademBaseЭкотизим учун очиқ API
← Ишга қайтиш

Ушбу иш иқтибос қилган ишлар

109 та иш

Иш: Measurement of the differential $\hbox {t}\overline{\hbox {t}}$ production cross section as a function of the jet mass and extraction of the top quark mass in hadronic decays of boosted top quarks

  1. Geant4—a simulation toolkit

    S. Agostinelli, John E. Allison, B. R. Ko +97

    Мақола2003139 иқтибос
    ABI

  2. An introduction to PYTHIA 8.2

    Torbjörn Sjöstrand, Stefan Ask, J. Christiansen +7

    Мақола2015116 иқтибос
    ABI

  3. The anti-<i>k</i><sub><i>t</i></sub>jet clustering algorithm

    Matteo Cacciari, Gavin P Salam, Gregory Soyez

    Мақола2008105 иқтибос
    ABI

  4. The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations

    Johan Alwall, Rikkert Frederix, Stefano Frixione +7

    Мақола201499 иқтибос
    ABI

  5. FastJet user manual

    Matteo Cacciari, Gavin P. Salam, Gregory Soyez

    Мақола201299 иқтибос
    ABI

  6. A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG BOX

    Simone Alioli, Paolo Nason, Carlo Oleari +1

    Мақола201084 иқтибос
    ABI

  7. Parton distributions from high-precision collider data

    Richard D. Ball, Valerio Bertone, Stefano Carrazza +12

    Мақола201784 иқтибос
    ABI

  8. Matching NLO QCD computations with parton shower simulations: the POWHEG method

    Stefano Frixione, Paolo Nason, Carlo Oleari

    Мақола200783 иқтибос
    ABI

  9. A New Method for Combining NLO QCD with Shower Monte Carlo Algorithms

    Paolo Nason

    Мақола200473 иқтибос
    ABI

  10. Merging meets matching in MC@NLO

    Rikkert Frederix, Stefano Frixione

    Мақола201259 иқтибос
    ABI

  11. Parton distributions for the LHC run II

    Richard D. Ball, Valerio Bertone, Stefano Carrazza +8

    Мақола201554 иқтибос
    ABI

  12. Comparative study of various algorithms for the merging of parton showers and matrix elements in hadronic collisions

    Johan Alwall, Stefan Höche, Frank Krauss +11

    Мақола200750 иқтибос
    ABI

  13. PDF4LHC recommendations for LHC Run II

    J. M. Butterworth, Stefano Carrazza, A. M. Cooper-Sarkar +13

    Мақола201648 иқтибос
    ABI

  14. Jet flavour classification using DeepJet

    E. S. Bols, J. Kieseler, M. Verzetti +2

    Мақола202047 иқтибос
    ABI

  15. A positive-weight next-to-leading-order Monte Carlo for heavy flavour hadroproduction

    Stefano Frixione, Giovanni Ridolfi, Paolo Nason

    Мақола200738 иқтибос
    ABI

  16. Top++: A program for the calculation of the top-pair cross-section at hadron colliders

    M. Czakon, Alexander Mitov

    Мақола201436 иқтибос
    ABI

  17. Single-top Wt-channel production matched with parton showers using the POWHEG method

    Emanuele Re

    Мақола201133 иқтибос
    ABI

  18. Сарлавҳасиз

    Бошқа32 иқтибос
    ABI

  19. The CMS experiment at the CERN LHC

    S. Chatrchyan, G. Hmayakyan, V. Khachatryan +97

    Мақола200830 иқтибос
    ABI

  20. The CMS trigger system

    V. Khachatryan, A. M. Sirunyan, A. Tumasyan +97

    Мақола201728 иқтибос
    ABI

  21. NLO single-top production matched with shower in POWHEG:<i>s</i>- and<i>t</i>-channel contributions

    Simone Alioli, Paolo Nason, Carlo Oleari +1

    Мақола200927 иқтибос
    ABI

  22. Tuning PYTHIA 8.1: the Monash 2013 tune

    P. Skands, S. Carrazza, J. Rojo

    Мақола201427 иқтибос
    ABI

  23. Particle-flow reconstruction and global event description with the CMS detector

    A. M. Sirunyan, A. Tumasyan, W. Adam +97

    Мақола201725 иқтибос
    ABI

  24. Performance of the CMS Level-1 trigger in proton-proton collisions at √<i>s</i> = 13 TeV

    A. M. Sirunyan, A. Tumasyan, W. Adam +97

    Мақола202023 иқтибос
    ABI

  25. Extraction and validation of a new set of CMS pythia8 tunes from underlying-event measurements

    A. M. Sirunyan, A. Tumasyan, W. Adam +97

    Мақола202021 иқтибос
    ABI