Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 180

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Modular A4 invariance and neutrino mixing

Open access
Kobayashi, Tatsuo, Omoto, Naoya, Shimizu, Yusuke, Takagi, Kenta, Tanimoto, Morimitsu, Tatsuishi, Takuya H.·2018·Journal of High Energy Physics

Abstract

We study the phenomenological implications of the modular symmetry Γ(3) ≃ A 4 of lepton flavors facing recent experimental data of neutrino oscillations. The mass matrices of neutrinos and charged leptons are essentially given by fixing the expectation value of modulus τ, which is the only source of modular invariance breaking. We introduce no flavons in contrast with the conventional flavor models with A 4 symmetry. We classify our neutrino models along with the type I seesaw model, the Weinberg operator model and the Dirac neutrino model. In the normal hierarchy of neutrino masses, the seesaw model is available by taking account of recent experimental data of neutrino oscillations and the cosmological bound of sum of neutrino masses. The predicted sin 2 θ 23 is restricted to be larger than 0.54 and δ CP = ±(50°-180°). Since the correlation of sin 2 θ 23 and δ CP is sharp, the prediction is testable in the future. It is remarkable that the effective mass m ee of the neutrinoless double beta decay is around 22 meV while the sum of neutrino masses is predicted to be 145 meV. On the other hand, for the inverted hierarchy of neutrino masses, only the Dirac neutrino model is consistent with the experimental data.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/jhep11(2018)196

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Metadata

Authors
Kobayashi, T., Omoto, N., Shimizu, Y., Takagi, K., Tanimoto, M., & Tatsuishi, T. H.
Venue
Journal of High Energy Physics
Published
2018-11
Volume
2018
Issue
11
ISSN
1029-8479 (ISSN-L)
OpenAlex
W2886260056
Cited by
180
References
1
FWCI
12.94
Type
journal article
Language
en
Open access
diamond

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Modular A4 invariance and neutrino mixing. https://app.cochat.ai/papers/10.1007/jhep11(2018)196
The paper
Kobayashi, T., Omoto, N., Shimizu, Y., Takagi, K., Tanimoto, M., & Tatsuishi, T. H. (2018). Modular A4 invariance and neutrino mixing. Journal of High Energy Physics. https://doi.org/10.1007/jhep11(2018)196

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.