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 150 tok/s
Gemini 2.5 Pro 50 tok/s Pro
GPT-5 Medium 31 tok/s Pro
GPT-5 High 26 tok/s Pro
GPT-4o 105 tok/s Pro
Kimi K2 185 tok/s Pro
GPT OSS 120B 437 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

Revisiting the model for radiative neutrino masses with dark matter in the $\mathrm{U(1)}_{B-L}$ gauge theory (2410.22835v1)

Published 30 Oct 2024 in hep-ph

Abstract: The radiative seesaw model with gauged $\mathrm{U(1)}{B-L}\times\mathbb{Z}_2$ extension is a well-motivated scenario which gives consistent predictions of active neutrino masses and the abundance of dark matter. Majorana masses of right-handed neutrinos, the lightest of which can be identified as dark matter, are given by the spontaneous breaking of the $\mathrm{U(1)}{B-L}$ gauge symmetry. We revisit this model with the latest constraints from dark matter searches, neutrino oscillations, flavor experiments and collider experiments. We explore the feasible parameter space of this model, and find that there are still allowed regions under the latest experimental constraints. We present new viable benchmark scenarios for this model, i.e., the right-handed neutrino dark matter scenario and the scalar dark matter scenario. We also mention the testability of these benchmark scenarios at future experiments.

Summary

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

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb 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.