Papers
Topics
Authors
Recent
AI Research 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 62 tok/s
Gemini 2.5 Pro 47 tok/s Pro
GPT-5 Medium 12 tok/s Pro
GPT-5 High 10 tok/s Pro
GPT-4o 91 tok/s Pro
Kimi K2 139 tok/s Pro
GPT OSS 120B 433 tok/s Pro
Claude Sonnet 4 31 tok/s Pro
2000 character limit reached

Vector Boson Fusion Searches for Dark Matter at the LHC (1603.07739v1)

Published 24 Mar 2016 in hep-ph and hep-ex

Abstract: The vector boson fusion (VBF) event topology at the Large Hadron Collider (LHC) allows efficient suppression of dijet backgrounds and is therefore a promising target for new physics searches. We consider dark matter models which interact with the Standard Model through the electroweak sector: either through new scalar and pseudoscalar mediators which can be embedded into the Higgs sector, or via effective operators suppressed by some higher scale, and therefore have significant VBF production cross-sections. Using realistic simulations of the ATLAS and CMS analysis chain, including estimates of major error sources, we project the discovery and exclusion potential of the LHC for these models over the next decade.

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