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Zhenan Liu

Researcher at National Central University

Publications -  278
Citations -  14558

Zhenan Liu is an academic researcher from National Central University. The author has contributed to research in topics: Large Hadron Collider & Standard Model. The author has an hindex of 54, co-authored 261 publications receiving 12029 citations. Previous affiliations of Zhenan Liu include University of Wisconsin-Madison & University of Zurich.

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Combined results of searches for the standard model Higgs boson in pp collisions at √s = 7 TeV

S. Chatrchyan, +2247 more
TL;DR: In this article, the authors reported results from searches for the standard model Higgs boson in proton-proton collisions at square root(s) = 7 TeV in five decay modes: gamma pair, b-quark pair, tau lepton pair, W pair, and Z pair.
Journal ArticleDOI

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

Albert M. Sirunyan, +2215 more
- 06 Oct 2017 - 
TL;DR: A fully-fledged particle-flow reconstruction algorithm tuned to the CMS detector was developed and has been consistently used in physics analyses for the first time at a hadron collider as mentioned in this paper.
Journal ArticleDOI

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

S. Chatrchyan, +2345 more
- 01 Oct 2012 - 
TL;DR: In this article, the performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at the LHC in 2010.
Journal ArticleDOI

Performance of the CMS muon detector and muon reconstruction with proton-proton collisions at s=13 TeV

Albert M. Sirunyan, +2358 more
- 19 Jun 2018 - 
TL;DR: In this paper, the performance of the modified system is studied using proton-proton collision data at center-of-mass energy √s=13 TeV, collected at the LHC in 2015 and 2016.
Journal ArticleDOI

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

Albert M. Sirunyan, +2251 more
- 03 Jan 2020 - 
TL;DR: For the first time, predictions from pythia8 obtained with tunes based on NLO or NNLO PDFs are shown to reliably describe minimum-bias and underlying-event data with a similar level of agreement to predictions from tunes using LO PDF sets.