scispace - formally typeset
V

Vyacheslav Klyukhin

Researcher at Moscow State University

Publications -  1178
Citations -  80905

Vyacheslav Klyukhin is an academic researcher from Moscow State University. The author has contributed to research in topics: Large Hadron Collider & Lepton. The author has an hindex of 117, co-authored 1042 publications receiving 72406 citations. Previous affiliations of Vyacheslav Klyukhin include CERN & University of Trento.

Papers
More filters
Journal ArticleDOI

Search for supersymmetry with photons in pp collisions at √s=8 TeV

Vardan Khachatryan, +2321 more
- 19 Oct 2015 - 
TL;DR: In this article, two searches for physics beyond the standard model in events containing photons are presented, and the results are interpreted in the context of general gauge-mediated supersymmetry, with the next-to-lightest supersymmetric particle either a bino- or wino-like neutralino.
Journal ArticleDOI

Commissioning of the CMS High-Level Trigger with Cosmic Rays

S. Chatrchyan, +2464 more
- 19 Mar 2010 - 
TL;DR: An overview of the CMS High-Level Trigger is given and its commissioning using cosmic rays is focused on, with the average time taken for the HLT selection and its dependence on detector and operating conditions presented.
Journal ArticleDOI

Search for a W' or Techni-ρ decaying into WZ in pp collisions at √s=7TeV

S. Chatrchyan, +2255 more
- 02 Oct 2012 - 
TL;DR: In this article, a search is performed in pp collisions at 7 TeV for exotic particles decaying via WZ to final states with electrons and muons, and upper bounds at 95% confidence level are set on the production cross section of the W' boson described by the sequential standard model.

Search for Higgs Boson Pair Production in Events with Two Bottom Quarks and Two Tau Leptons in Proton–proton Collisions at √s = 13 TeV

Albert M. Sirunyan, +2213 more
TL;DR: Doser et al. as mentioned in this paper presented a survey of the state of the art in the field of cyber-physical cyber-warrior networks and proposed a method to improve it.
Journal ArticleDOI

A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution.

Albert M. Sirunyan, +2276 more
- 30 Oct 2020 - 
TL;DR: A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet, to improve the sensitivity of analyses that make use of b jets in the final state.