Diagnosing the top-quark angular asymmetry using LHC intrinsic charge asymmetries

TL;DR

This paper introduces new charge asymmetry variables in top-antitop plus jet events at the LHC to detect flavor-violating new physics models, offering a data-driven background method and demonstrating potential for model discrimination.

Contribution

It proposes novel charge asymmetry variables and a background estimation method to improve detection of new physics in top-quark events at the LHC.

Findings

Charge asymmetry variables can help exclude Standard Model in certain parameter ranges.

The method reduces systematic errors by minimizing Monte Carlo reliance.

Variables are useful for distinguishing different new physics models.

Abstract

Flavor-violating interactions involving new heavy particles are among proposed explanations for the $t\bar t$ forward-backward asymmetry observed at the Tevatron. Many of these models generate a $t\bar t$-plus-jet signal at the LHC. In this paper we identify several new charge asymmetric variables in $t\bar tj$ events that can contribute to the discovery of such models at the LHC. We propose a data-driven method for the background, largely eliminating the need for a Monte Carlo prediction of $t\bar t$-plus-jets, and thus reducing systematic errors. With a fast detector simulation, we estimate the statistical sensitivity of our variables for one of these models, finding that charge-asymmetric variables could materially assist in the exclusion of the Standard Model across much of the mass and coupling range, given 5 inverse fb of data. Should any signal appear, our variables will be useful in distinguishing classes of models from one another.