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Lessons from the first JUNO results

Esteban, Ivan; Gonzalez-Garcia, M. C.; Maltoni, Michele ; Martinez-Soler, Ivan; Pinheiro, João Paulo; Schwetz, Thomas ORCID iD icon 1
1 Institut für Astroteilchenphysik (IAP), Karlsruher Institut für Technologie (KIT)

Abstract:

First results from the JUNO reactor neutrino experiment already determine with world-leading precision the small neutrino squared-mass splitting ∆m$^2_{2l}$ and the mixing angle θ12. In this article we perform an exploratory study beyond these, taking advantage of the first JUNO data release to discuss its sensitivity to the large squared-mass splitting, ∆m$^2_{3l}$. When combined with constraints from global oscillation data, this may already contain some information on the neutrino mass ordering. Indeed, we find that the combination of the complementary ∆m$^2_{3l}$-determinations gives a slight preference for Normal Ordering, with a p-value for Inverted Ordering of 2%–2.6% (2.2σ–2.3σ). We study the robustness of this result with respect to potential systematic uncertainties and statistical fluctuations. Taken at face value, a full global analysis of oscillation data including the publicly available JUNO information and data leads to a preference for Normal Ordering with ∆χ2 = 4.6 and 9.4 without and with Super-K and IceCube-24 atmospheric neutrino data, respectively.


Verlagsausgabe §
DOI: 10.5445/IR/1000192189
Veröffentlicht am 14.04.2026
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Astroteilchenphysik (IAP)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2026
Sprache Englisch
Identifikator ISSN: 1029-8479
KITopen-ID: 1000192189
HGF-Programm 51.13.05 (POF IV, LK 01) Theoretische Astroteilchenphysik
Erschienen in Journal of High Energy Physics
Verlag Scuola Internazionale Superiore di Studi Avanzati (SISSA)
Band 2026
Heft 4
Seiten Art.Nr: 89
Bemerkung zur Veröffentlichung related DOI

10.48550/arXiv.2601.09791
Vorab online veröffentlicht am 10.04.2026
Schlagwörter Neutrino Mixing, Neutrino Interactions
Nachgewiesen in Scopus
OpenAlex
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