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 186 tok/s
Gemini 2.5 Pro 48 tok/s Pro
GPT-5 Medium 34 tok/s Pro
GPT-5 High 32 tok/s Pro
GPT-4o 65 tok/s Pro
Kimi K2 229 tok/s Pro
GPT OSS 120B 441 tok/s Pro
Claude Sonnet 4.5 38 tok/s Pro
2000 character limit reached

Testing the Origins of Neutrino Mass with Supernova Neutrino Time Delay (2404.17352v2)

Published 26 Apr 2024 in hep-ph, astro-ph.HE, and hep-ex

Abstract: The origin of neutrino masses remains unknown. Both the vacuum mass and the dark mass generated by the neutrino interaction with dark matter (DM) particles or fields can fit the current oscillation data. The dark mass squared is proportional to the DM number density and therefore varies on the galactic scale with much larger values around the Galactic Center. This affects the group velocity and the arrival time delay of core-collapse supernovae (SN) neutrinos. This time delay, especially for the $\nu_e$ neutronization peak with a sharp time structure, can be used to distinguish the vacuum and dark neutrino masses. For illustration, we explore the potential of DUNE which is sensitive to $\nu_e$. Our simulations show that DUNE can distinguish the two neutrino mass origins at more than $5\sigma\,$C.L., depending on the observed local value of neutrino mass, the neutrino mass ordering, the DM density profile, and the SN location.

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.

X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets

This paper has been mentioned in 6 tweets and received 4 likes.

Upgrade to Pro to view all of the tweets about this paper: