Systematic Interpretability and the Likelihood for Boosted Top Quark Identification

TL;DR

This paper develops a theoretically grounded likelihood ratio method for identifying boosted top quarks at the LHC, providing insights into the physics and interpretability of top-tagging algorithms.

Contribution

It introduces a minimal assumption-based likelihood ratio for top quark tagging and a systematic interpretability framework, advancing understanding of discrimination power.

Findings

Derived the optimal likelihood ratio for top vs. bottom jet discrimination.

Validated the likelihood's effectiveness through analytical calculations and simulations.

Established a fundamental limit on discrimination power based on physics constraints.

Abstract

Identification of boosted, hadronically-decaying top quarks is a problem of central importance for physics goals of the Large Hadron Collider. We present a theoretical analysis of top quark tagging, establishing zeroth-order, minimal assumptions that should be satisfied by any purported top-tagged jet, like existence of three hard subjets, a bottom-tagged subjet, total mass consistent with the top quark, and a pairwise subjet mass consistent with the W boson. From these minimal assumptions, we construct the optimal discrimination observable, the likelihood ratio, for the binary discrimination problem of top quark-initiated versus bottom quark-initiated jets through next-to-leading order in the strong coupling. We compare and compute corresponding signal and background efficiencies both analytically and from simulated data, validating an understanding of the relevant physics identified and exploited by the likelihood. In the process, we construct a method for systematic interpretability of the likelihood ratio for this problem, and explicitly establish a hard floor on possible discrimination power. These results can correspondingly be applied to understanding and interpreting machine learning studies of this problem.