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 77 tok/s
Gemini 2.5 Pro 51 tok/s Pro
GPT-5 Medium 33 tok/s Pro
GPT-5 High 37 tok/s Pro
GPT-4o 95 tok/s Pro
Kimi K2 189 tok/s Pro
GPT OSS 120B 431 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

Measurement of normalized differential $\mathrm{t}\overline{\mathrm{t}}$ cross sections in the dilepton channel from pp collisions at $\sqrt{s} =$ 13 TeV (1708.07638v2)

Published 25 Aug 2017 in hep-ex

Abstract: Normalized differential cross sections for top quark pair production are measured in the dilepton (e$+$e$-$, $\mu+\mu-$, and $\mu\mp$e$\pm$) decay channels in proton-proton collisions at a center-of-mass energy of 13 TeV. The measurements are performed with data corresponding to an integrated luminosity of 2.1 fb${-1}$ using the CMS detector at the LHC. The cross sections are measured differentially as a function of the kinematic properties of the leptons, jets from bottom quark hadronization, top quarks, and top quark pairs at the particle and parton levels. The results are compared to several Monte Carlo generators that implement calculations up to next-to-leading order in perturbative quantum chromodynamics interfaced with parton showering, and also to fixed-order theoretical calculations of top quark pair production up to next-to-next-to-leading order.

Summary

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

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

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

Authors (1)

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