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# Precision neutrino experiments vs the Littlest Seesaw

Ballett, Peter, King, Stephen F., Pascoli, Silvia, Prouse, Nick W. and Wang, TseChun (2017) Precision neutrino experiments vs the Littlest Seesaw. Journal of High Energy Physics, 03.

Record type: Article

## Abstract

We study to what extent upcoming precision neutrino oscillation experiments will be able to exclude one of the most predictive models of neutrino mass and mixing: the Littlest Seesaw. We show that this model provides a good fit to current data, predicting eight observables from two input parameters, and provide new assessments of its predictions and their correlations. We then assess the ability to exclude this model using simulations of upcoming neutrino oscillation experiments including the medium-distance reactor experiments JUNO and RENO-50 and the long-baseline accelerator experiments DUNE and T2HK. We find that an accurate determination of the currently least well measured parameters, namely the atmospheric and solar angles and the CP phase $\delta$, provide crucial independent tests of the model. For $\theta_{13}$ and the two mass-squared differences, however, the model's exclusion requires a combination of measurements coming from a varied experimental programme. Our results show that the synergy and complementarity of future experiments will play a vital role in efficiently discriminating between predictive models of neutrino flavour, and hence, towards advancing our understanding of neutrino oscillations in the context of the flavour puzzle of the Standard Model.

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pdf - Accepted Manuscript

Accepted/In Press date: 12 March 2017
e-pub ahead of print date: 21 March 2017
Additional Information: 27 pages, 13 figures
Keywords: hep-ph, hep-ex
Organisations: Theory Group

## Identifiers

Local EPrints ID: 408282
URI: http://eprints.soton.ac.uk/id/eprint/408282
ISSN: 1029-8479
PURE UUID: 3c7e8eb3-c31d-447f-98ce-515a1eba302f

## Catalogue record

Date deposited: 19 May 2017 04:02

## Contributors

Author: Peter Ballett
Author: Stephen F. King
Author: Silvia Pascoli
Author: Nick W. Prouse
Author: TseChun Wang