Based on the established task of identifying boosted, hadronically decaying top quarks, we compare a wide range of modern machine learning approaches. Unlike most established methods they rely on low-level input, for instance calorimeter output. While their network architectures are vastly different, their performance is comparatively similar. In general, we find that these new approaches are extremely powerful and great fun.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Asymmetry observables and the origin of R D ( * ) anomalies

Not Available

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2018

Pulling out all the tops with computer vision and deep learning

We apply computer vision with deep learning — in the form of a convolutional neural network (CNN) — to build a highly effective boosted top tagger. Previous work (the “DeepTop” tagger of Kasieczka et al) has shown that a CNN-based top tagger can achieve comparable performance to state-of-the-art conventional top taggers based on high-level inputs. Here, we introduce a number of improvements to the DeepTop tagger, including architecture, training, image preprocessing, sample size and color pixels. Our final CNN top tagger outperforms BDTs based on high-level inputs by a factor of ~ 2–3 or more in background rejection, over a wide range of tagging efficiencies and fiducial jet selections. As reference points, we achieve a QCD background rejection factor of 500 (60) at 50%top tagging efficiency for fully-merged (non-merged) top jets with pT in the 800–900 GeV (350–450 GeV) range. Our CNN can also be straightforwardly extended to the classification of other types of jets, and the lessons learned here may be useful to others designing their own deep NNs for LHC applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

It’s all right(-handed neutrinos): a new W ' model for the R D ( ∗ ) anomaly

The measured B-meson semi-leptonic branching ratios R D and R D ∗ have long-standing deviations between theory and experiment. We introduce a model which explains both anomalies through a single interaction by introducing a right-handed neutrino as the missing energy particle. This interaction is mediated by a heavy charged vector boson (W ') which couples only to right-handed quarks and leptons of the Standard Model through the mixing of these particles with new vector-like fermions. Previous W ' models for the R D ( ∗ ) anomaly were strongly constrained from flavor changing neutral currents and direct collider searches for Z' → τ τ resonances. We show that relying on right-handed fermion mixing enables us to avoid these constraints, as well as other severe bounds from electroweak precision tests and neutrino mixing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗