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most citedObservation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC

10.9k citations

Showing 2014Show all

232 papers · 1 filter

hep-ph2014★ 173 cited

HAWK 2.0: A Monte Carlo program for Higgs production in vector-boson fusion and Higgs strahlung at hadron colliders

Ansgar Denner, Stefan Dittmaier, Stefan Kallweit +1

The Monte Carlo integrator HAWK provides precision predictions for Higgs production at hadron colliders in vector-boson fusion and Higgs strahlung, i.e. in production processes whe…

quant-ph2014★ 87 cited

Smooth optimal quantum control for robust solid state spin magnetometry

Tobias Nöbauer, Andreas Angerer, Björn Bartels +5

Nitrogen-vacancy centers in diamond show great potential as magnetic, electric and thermal sensors which are naturally packaged in a bio-compatible material. In particular, NV-base…

hep-ph2014★ 10 cited

Extrapolating W-Associated Jet-Production Ratios at the LHC

Z. Bern, L. J. Dixon, F. Febres Cordero +4

Electroweak vector-boson production, accompanied by multiple jets, is an important background to searches for physics beyond the Standard Model. A precise and quantitative understa…

hep-ph2014★ 42 cited

NLO QCD and electroweak corrections to W+γ production with leptonic W-boson decays

Ansgar Denner, Stefan Dittmaier, Markus Hecht +1

We present a calculation of the next-to-leading-order electroweak corrections to W+γ production, including the leptonic decay of the W boson and taking into account all off-shell e…

hep-ex2014★ 134 cited

Identification and energy calibration of hadronically decaying tau leptons with the ATLAS experiment in collisions at =8 TeV

ATLAS Collaboration

This paper describes the trigger and offline reconstruction, identification and energy calibration algorithms for hadronic decays of tau leptons employed for the data collected fro…

cs.LG2014★ 2.6k cited

Striving for Simplicity: The All Convolutional Net

Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox +1

Most modern convolutional neural networks (CNNs) used for object recognition are built using the same principles: Alternating convolution and max-pooling layers followed by a small…