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A randomly generated Majorana neutrino mass matrix using Adaptive Monte Carlo method

High Energy Physics - Phenomenology 2024-07-30 v3

Abstract

A randomly generated complex symmetric matrix using Adaptive Monte Carlo method, is taken as a general form of Majorana neutrino mass matrix, which is diagonalized by the use of eigenvectors. We extract all the neutrino oscillation parameters i.e. two mass-squared differences (Δm212\Delta m_{21}^2 and Δm322\Delta m_{32}^2 ), three mixing angles (θ12\theta_{12}, θ13\theta_{13}, θ23\theta_{23}) and three phases i.e. one Dirac CP violating phase (δCP\delta_{CP}) and two Majorana phases (α\alpha and β\beta). The charge-parity (CP) violating phases are extracted from the mixing matrix constructed with the eigenvectors of the Hermitian matrix formed by the complex symmetric matrix. All the neutrino oscillation parameters within 3σ\sigma bound are allowed in both normal hierarchy (NH) and inverted hierarchy (IH) consistent with the latest Planck cosmological upper bound, mi<0.12\sum\vert m_i\vert<0.12 eV. This latest cosmological upper bound is allowed only in three cases of zero texture for m11=0m_{11}=0; m11,m12=0m_{11},m_{12}=0 and m11,m13=0m_{11},m_{13}=0 in normal hierarchy whereas none of zero texture is allowed in inverted hierarchy. We also study effective neutrino masses mβm_{\beta} in tritium beta decay and mββm_{\beta\beta} in neutrinoless double beta decay.

Keywords

Cite

@article{arxiv.2405.08495,
  title  = {A randomly generated Majorana neutrino mass matrix using Adaptive Monte Carlo method},
  author = {Y Monitar Singh and Mayengbam Kishan Singh and N Nimai Singh},
  journal= {arXiv preprint arXiv:2405.08495},
  year   = {2024}
}

Comments

23-pages, some text and extra figure are added

R2 v1 2026-06-28T16:26:44.289Z