Top quark mass determination from the energy peaks of b-jets and B-hadrons at NLO QCD
Kaustubh Agashe, Doojin Kim, Roberto Franceschini, Markus Schulze

TL;DR
This paper proposes and analyzes a method to determine the top quark mass using the energy peaks of b-jets and B-hadrons at NLO QCD, aiming for reduced sensitivity to production details and uncertainties.
Contribution
It introduces an NLO QCD analysis of the energy-peak method for top mass measurement using b-jets and B-hadrons, including assessment of theoretical uncertainties and potential improvements.
Findings
Top quark mass can be extracted with approximately 1.4 GeV total uncertainty from b-jet energy peaks.
Using B-hadron energy peaks can reduce experimental uncertainties related to jet energy scale.
Fragmentation scale dependence is the dominant theoretical uncertainty in B-hadron based extraction.
Abstract
We analyze the energy spectra of b-jets and B-hadrons resulting from the production and decay of top quarks within the SM at the LHC at the NLO QCD. For both hadrons and jets, we calculate the correlation of the peak of the spectrum with the top quark mass, considering the "energy-peak" as an observable to determine the top quark mass. Such a method is motivated by our previous work where we argued that this approach can have reduced sensitivity to the details of the production mechanism of the top quark, whether it is higher-order QCD effects or new physics contributions. As part of the NLO improvement over the original proposal, we assess the residual sensitivity of the extracted top quark mass to perturbative effects both in top quark production and decay. For a 1% jet energy scale uncertainty (and assuming negligible statistical error), the top quark mass can then be…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
