REVIEW 3 cited by
Convolved Substructure: Analytically Decorrelating Jet Substructure Observables
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
Signed reviews
abstract
A number of recent applications of jet substructure, in particular searches for light new particles, require substructure observables that are decorrelated with the jet mass. In this paper we introduce the Convolved SubStructure (CSS) approach, which uses a theoretical understanding of the observable to decorrelate the complete shape of its distribution. This decorrelation is performed by convolution with a shape function whose parameters and mass dependence are derived analytically. We consider in detail the case of the $D_2$ observable and perform an illustrative case study using a search for a light hadronically decaying $Z'$. We find that the CSS approach completely decorrelates the $D_2$ observable over a wide range of masses. Our approach highlights the importance of improving the theoretical understanding of jet substructure observables to exploit increasingly subtle features for performance.
Forward citations
Cited by 3 Pith papers
-
Higgs Signal Strength Estimation with Machine Learning under Systematic Uncertainties
SAGE, a dual-branch GNN trained under nuisance fluctuations, estimates the Higgs signal strength with near-nominal coverage (0.662-0.683) but wider intervals than the top FAIR-HUC leaderboard methods.
-
Mass Agnostic Jet Taggers
A systematic comparison shows that data-augmentation jet taggers (planing and PCA scaling) achieve background-preserving performance similar to adversarial networks and uBoost, with much lower training cost.
-
Exploring the Space of Jets with CMS Open Data
The authors apply the energy mover's distance to 1.69 million jets from CMS open data and show that track-based jet studies, including visualizations and anomaly scoring, work on real collider data.
Discussion (0). Continue with ORCID to comment.