The University of Southampton
University of Southampton Institutional Repository

Precision neutrino experiments vs the Littlest Seesaw

Precision neutrino experiments vs the Littlest Seesaw
Precision neutrino experiments vs the Littlest Seesaw
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.
hep-ph, hep-ex
1029-8479
Ballett, Peter
0bbdf25a-b2cc-4f63-9796-d86a1d1a314e
King, Stephen F.
f8c616b7-0336-4046-a943-700af83a1538
Pascoli, Silvia
5cf2d5e5-b9bd-4884-8ba1-2fd4ddf4eb2e
Prouse, Nick W.
00f8d80c-d999-4d43-9d24-22fac2e63916
Wang, TseChun
8dee377d-ee23-4e49-a505-32924b951292
Ballett, Peter
0bbdf25a-b2cc-4f63-9796-d86a1d1a314e
King, Stephen F.
f8c616b7-0336-4046-a943-700af83a1538
Pascoli, Silvia
5cf2d5e5-b9bd-4884-8ba1-2fd4ddf4eb2e
Prouse, Nick W.
00f8d80c-d999-4d43-9d24-22fac2e63916
Wang, TseChun
8dee377d-ee23-4e49-a505-32924b951292

Ballett, Peter, King, Stephen F., Pascoli, Silvia, Prouse, Nick W. and Wang, TseChun (2017) Precision neutrino experiments vs the Littlest Seesaw. The Journal of High Energy Physics, 03. (doi:10.1007/JHEP03(2017)110).

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.

Other
pdf - Accepted Manuscript
Download (2MB)

More information

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: https://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
Last modified: 19 Jul 2019 18:19

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×