Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 83 tok/s
Gemini 2.5 Pro 51 tok/s Pro
GPT-5 Medium 24 tok/s Pro
GPT-5 High 20 tok/s Pro
GPT-4o 83 tok/s Pro
Kimi K2 109 tok/s Pro
GPT OSS 120B 460 tok/s Pro
Claude Sonnet 4 38 tok/s Pro
2000 character limit reached

Heavy-flavor hadro-production with heavy-quark masses renormalized in the ${\overline{\rm MS}}$, MSR and on-shell schemes (2009.07763v2)

Published 16 Sep 2020 in hep-ph and hep-ex

Abstract: We present predictions for heavy-quark production at the Large Hadron Collider making use of the ${\overline{\rm MS}}$ and MSR renormalization schemes for the heavy-quark mass as alternatives to the widely used on-shell renormalization scheme. We compute single and double differential distributions including QCD corrections at next-to-leading order and investigate the renormalization and factorization scale dependence as well as the perturbative convergence in these mass renormalization schemes. The implementation is based on publicly available programs, ${\texttt{MCFM}}$ and ${\texttt{xFitter}}$, extending their capabilities. Our results are applied to extract the top-quark mass using measurements of the total and differential $t\bar{t}$ production cross-sections and to investigate constraints on parton distribution functions, especially on the gluon distribution at low $x$ values, from available LHC data on heavy-flavor hadro-production.

Summary

We haven't generated a summary for this paper yet.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube