Identifying Boosted Objects with N-subjettiness
read the original abstract
We introduce a new jet shape -- N-subjettiness -- designed to identify boosted hadronically-decaying objects like electroweak bosons and top quarks. Combined with a jet invariant mass cut, N-subjettiness is an effective discriminating variable for tagging boosted objects and rejecting the background of QCD jets with large invariant mass. In efficiency studies of boosted W bosons and top quarks, we find tagging efficiencies of 30% are achievable with fake rates of 1%. We also consider the discovery potential for new heavy resonances that decay to pairs of boosted objects, and find significant improvements are possible using N-subjettiness. In this way, N-subjettiness combines the advantages of jet shapes with the discriminating power seen in previous jet substructure algorithms.
This paper has not been read by Pith yet.
Forward citations
Cited by 12 Pith papers
-
Event isotropy in perturbative QCD
First pQCD predictions for event isotropy distributions at LO, NLO, and NLL+NLO accuracy in e+e- collisions.
-
Centauric 1-Jettiness in DIS and Universal Power Corrections
Introduces Centauric 1-jettiness in DIS, derives N3LL resummation matched to NLO, and establishes universal non-perturbative power corrections scaling as 1/R via reduction to rescaled hemisphere soft function.
-
Reweighting Adversarial Networks for Unbinned Unfolding
RANs generalize moment unfolding to full phase-space unbinned unfolding via detector-level Wasserstein critics without requiring support overlap or multiple iterations.
-
Neural Scaling Laws for Jet Generation
Scaling laws hold logarithmically for model size in autoregressive jet generation, with next-token loss correlating to physical metrics via sliced Wasserstein distance, but show weaker scaling for dataset size and com...
-
Geometric algebra as the input language of collider foundation models
Collider events are represented as multivectors in Cl(1,3) ⊗ V_flav whose grade projections recover standard observables, intended as input for equivariant foundation models.
-
Low-Multiplicity Jets as Probes of GeV-Scale Light-Quark-Coupled Particles
A proposed LHC search using low-multiplicity jets plus a photon can extend sensitivity to GeV-scale particles that couple to light quarks.
-
What Do Lorentz-Equivariant Jet Taggers Learn?
Equivariant jet taggers suppress frame-dependent pseudorapidity while encoding jet mass and N-subjettiness strongly, with bivector channels negligible and vector channels dominant for top tagging.
-
Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane
Explainability techniques applied to LundNet show that assigned node importance correlates with classical jet substructure observables such as N-subjettiness ratios and energy correlation functions, with shifts across...
-
Kitchen Sink Anomaly Detection
A combined kitchen sink observable set of Energy Flow Polynomials and subjettiness variables outperforms standard baselines in sensitivity to a wide range of resonant signals, with new public benchmarks released and a...
-
LHC signatures of a light pseudoscalar in a flipped two-Higgs scenario: the usefulness of boosted $b{\bar b}$ pairs
Boosted di-b-jet tagging plus BDT analysis yields 5-10 sigma significance for a light pseudoscalar in flipped 2HDM with 3 ab^{-1} including 10% systematics.
-
KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging
E-PCN reaches 94.67% macro-accuracy on 10-class jet tagging by weighting graphs with angular separation, transverse momentum, momentum fraction, and invariant mass, with Grad-CAM showing the first two account for 76% ...
- Looking inside jets: an introduction to jet substructure and boosted-object phenomenology
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.