REVIEW 1 cited by
Measurements of top quark spin observables in tbar{t} events using dilepton final states in sqrt{s} = 8 TeV pp collisions with the ATLAS detector
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Measurements of top quark spin observables in tbar{t} events using dilepton final states in sqrt{s} = 8 TeV pp collisions with the ATLAS detector
read the original abstract
Measurements of top quark spin observables in $t\bar{t}$ events are presented based on 20.2 fb$^{-1}$ of $\sqrt{s} = 8$ TeV proton-proton collisions recorded with the ATLAS detector at the LHC. The analysis is performed in the dilepton final state, characterised by the presence of two isolated leptons (electrons or muons). There are 15 observables, each sensitive to a different coefficient of the spin density matrix of $t\bar{t}$ production, which are measured independently. Ten of these observables are measured for the first time. All of them are corrected for detector resolution and acceptance effects back to the parton and stable-particle levels. The measured values of the observables at parton level are compared to Standard Model predictions at next-to-leading order in QCD. The corrected distributions at stable-particle level are presented and the means of the distributions are compared to Monte Carlo predictions. No significant deviation from the Standard Model is observed for any observable.
Forward citations
Cited by 1 Pith paper
-
Neural Posterior Unfolding
A normalizing-flow-based Bayesian unfolding method (NPU) plus a modern Python implementation of Fully Bayesian Unfolding (FBU) are introduced and validated on Gaussian and simulated LHC jet data.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.