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Masaharu Nomachi

Researcher at Osaka University

Publications -  1102
Citations -  87059

Masaharu Nomachi is an academic researcher from Osaka University. The author has contributed to research in topics: Large Hadron Collider & Higgs boson. The author has an hindex of 129, co-authored 1097 publications receiving 81488 citations. Previous affiliations of Masaharu Nomachi include West University of Timișoara & Saitama University.

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Measurement of the inelastic proton-proton cross section at √s=13 TeV with the ATLAS detector at the LHC

Morad Aaboud, +2901 more
- 26 Oct 2016 - 
TL;DR: In this paper, a measurement of the inelastic proton-proton cross section using 60''μb^{-1} of pp collisions at a center-of-mass energy sqrt[s] of 13'TeV with the ATLAS detector at the LHC is presented.
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Search for squarks and gluinos with the ATLAS detector in final states with jets and missing transverse momentum using 4.7 fb − 1 of s = 7 TeV proton-proton collision data

Georges Aad, +2916 more
- 22 Jan 2013 - 
TL;DR: In this paper, a search for squarks and gluinos in final states containing jets, missing transverse momentum and no high-p(T) electrons or muons is presented.
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Searches for Higgs boson pair production in the hh →bbττ, γγWW∗, γγbb, bbbb channels with the ATLAS detector

Georges Aad, +2911 more
- 05 Nov 2015 - 
TL;DR: In this article, both resonant and nonresonant Higgs boson pair production were performed in the hh -> bb tau tau, gamma gamma WW* final states using 20.3 fb(-1) of collision data at a center-of-m...
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Search for new phenomena in dijet mass and angular distributions from pp collisions at √s= 13 TeV with the ATLAS detector

Georges Aad, +2817 more
- 10 Mar 2016 - 
TL;DR: In this article, the authors describe a model-agnostic search for pairs of jets (dijets) produced by resonant and non-resonant phenomena beyond the Standard Model.
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Search for the Standard Model Higgs boson produced in association with top quarks and decaying into bb¯ in pp collisions at √s = 8 TeV with the ATLAS detector

Georges Aad, +2816 more
- 29 Jul 2015 - 
TL;DR: In this paper, a neural network is used to discriminate between signal and background events, the latter being dominated by +jets production, and an observed (expected) limit of 3.4 (2.2) times the Standard Model cross section is obtained at 95 % confidence level.