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Wei Xie

Researcher at Purdue University

Publications -  1527
Citations -  87958

Wei Xie is an academic researcher from Purdue University. The author has contributed to research in topics: Large Hadron Collider & Lepton. The author has an hindex of 128, co-authored 1281 publications receiving 77097 citations. Previous affiliations of Wei Xie include University of Trento & Purdue University Calumet.

Papers
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Journal ArticleDOI

Systematic study of azimuthal anisotropy in Cu + Cu and Au + Au collisions at s NN =62.4 and 200 GeV SYSTEMATIC STUDY of AZIMUTHAL ANISOTROPY in ⋯ A. ADARE et al.

A. Adare, +458 more
- 23 Sep 2015 - 
TL;DR: In this article, the authors studied the dependence of azimuthal anisotropy on collision energy, species, and centrality in Au+$Au and Cu+$Cu collisions.
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Measurement of the production cross section of a W boson in association with two b jets in pp collisions at s?=8TeV

Vardan Khachatryan, +2245 more
TL;DR: The production cross section of a W boson in association with two b jets is measured using a sample of proton–proton collisions collected by the CMS experiment at the CERN LHC.
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Measurement of the cross section ratio σttbb/σttjj in pp collisions at √s = 8 TEV

Vardan Khachatryan, +2145 more
- 30 Jun 2015 - 
TL;DR: The first measurement of the cross section ratio σ_(ttbb)/σ_(ttjj) was presented using a data sample corresponding to an integrated luminosity of 19.6 fb^(−1) collected in pp collisions at √s = 8TeV with the CMS detector at the LHC as discussed by the authors.
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Studies of beauty suppression via nonprompt D-0 mesons in Pb-Pb collisions at root s(NN)=5.02 TeV

Albert M. Sirunyan, +2315 more
TL;DR: The transverse momentum spectra of D-0 mesons from b hadron decays are measured at midrapidity (vertical bar y vertical bar D0 yield is found to be suppressed in the measured p(T) range from 2 to 100 GeV/c as compared to pp collisions as mentioned in this paper.
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A deep neural network to search for new long-lived particles decaying to jets

Albert M. Sirunyan, +2302 more
- 27 Dec 2019 - 
TL;DR: In this article, a deep neural network is used to identify jets that are significantly displaced from the proton-proton (pp) collision region in the CMS detector at the LHC.