Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash 89 tok/s
Gemini 2.5 Pro 54 tok/s Pro
GPT-5 Medium 27 tok/s
GPT-5 High 22 tok/s Pro
GPT-4o 89 tok/s
GPT OSS 120B 457 tok/s Pro
Kimi K2 169 tok/s Pro
2000 character limit reached

Experimental search for neutron-antineutron oscillation with use of ultra-cold neutrons revisited (2508.07525v1)

Published 11 Aug 2025 in hep-ex

Abstract: Neutron-antineutron oscillation (nnbar-osc) is a baryon-number-violating process and a sensitive probe for physics beyond the Standard Model. Ultra-cold neutrons (UCNs) are attractive for nnbar-osc searches because of their long storage time, but earlier analyses indicated that phase shifts on wall reflection differ for neutron and antineutron, leading to severe decoherence and loss of sensitivity. Here we revisit this problem by numerically solving the time-dependent Schroedinger equation for the two-component n/nbar wave function, explicitly including wall interactions. We show that decoherence can be strongly suppressed by selecting a wall material whose neutron and antineutron optical potentials are nearly equal. Using coherent scattering length data and estimates for antineutrons, we identify a Ni-Al alloy composition that matches the potentials within a few percent while providing a high absolute value, enabling long UCN storage. With such a bottle and an improved UCN source, the sensitivity could reach an oscilla-tion period tau_nnbar of order 1010 s, covering most of the range predicted by certain grand-unified models. This approach revives the feasibility of high-sensitivity nnbar-osc searches using stored UCNs and offers a clear path to probe baryon-number violation far beyond existing limits.

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

Collections

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

Summary

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

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run prompts on this paper using GPT-5.

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

Follow-up Questions

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

Authors (1)

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