English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The reconstruction of top-quark pair-production ($t\bar{t}$) events is aprerequisite for many top-quark measurements. We use a deep neural network,trained with Monte-Carlo simulated events, to reconstruct $t\bar{t}$ decays inthe lepton+jets final state. Comparing our approach to a widely-used kinematicfit, we find significant improvements in the correct assignment of jets to thepartons from the decay, and we study the reconstruction performance of severalkinematic top-quark properties. We document our workflow for the optimisationof the hyperparameters of the deep neural network. This workflow can befollowed by experimental collaborations to retrain the network taking intoaccount their detailed detector simulations.

From the Bottom to the Top -- Reconstruction of $t\bar{t}$ Events with Deep Learning