output
19922026
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 2016Show all

204 papers · 1 filter

physics.atm-clus2016★ 12 cited

Charging dynamics of dopants in helium nanoplasmas

Andreas Heidenreich, Barbara Grüner, Dominik Schomas +3

We present a combined experimental and theoretical study of the charging dynamics of helium nanodroplets doped with atoms of different species and irradiated by intense near-infrar…

cond-mat.mtrl-sci2016

Modulation Doping of Silicon using Aluminium-induced Acceptor States in Silicon Dioxide

Dirk König, Daniel Hiller, Sebastian Gutsch +2

All electronic, optoelectronic or photovoltaic applications of silicon depend on controlling majority charge carriers via doping with impurity atoms. Nanoscale silicon is omniprese…

cs.CV2016★ 48 cited

FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia +3

The FlowNet demonstrated that optical flow estimation can be cast as a learning problem. However, the state of the art with regard to the quality of the flow has still been defined…

quant-ph2016★ 28 cited

Quantum Friction in Arbitrarily Directed Motion

J. Klatt, M. B. Farias, D. A. R. Dalvit +1

Quantum friction, the electromagnetic fluctuation-induced frictional force decelerating an atom which moves past a macroscopic dielectric body, has so far eluded experimental evide…

hep-ex2016★ 53 cited

Final COMPASS results on the deuteron spin-dependent structure function and the Bjorken sum rule

C. Adolph, M. Aghasyan, R. Akhunzyanov +223

Final results are presented from the inclusive measurement of deep-inelastic polarised-muon scattering on longitudinally polarised deuterons using a LiD target. The data were t…

cs.LG2016★ 91 cited

Loss is its own Reward: Self-Supervision for Reinforcement Learning

Evan Shelhamer, Parsa Mahmoudieh, Max Argus +1

Reinforcement learning optimizes policies for expected cumulative reward. Need the supervision be so narrow? Reward is delayed and sparse for many tasks, making it a difficult and…