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Proceedings of Corfu Summer Institute 2018 "School and Workshops on Elementary Particle Physics and Gravity" — PoS(CORFU2018) 2019
DOI: 10.22323/1.347.0050
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Matrix norms and search for sterile neutrinos

Abstract: Matrix norms can be used to measure the "distance" between two matrices which translates naturally to the problem of calculating the unitary deviation of the neutrino mixing matrices. Variety of matrix norms opens a possibility to measure such deviations on different structural levels of the mixing matrix.

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Cited by 3 publications
(3 citation statements)
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References 43 publications
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“…Moreover, matrix norms can be used to measure deviation from unitarity on the different levels of the mixing matrix. More details about the matrix norms applied to neutrino mixings can be found in [32,44]. Further, the number of singular values less than one determines a minimal number of additional neutrinos.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, matrix norms can be used to measure deviation from unitarity on the different levels of the mixing matrix. More details about the matrix norms applied to neutrino mixings can be found in [32,44]. Further, the number of singular values less than one determines a minimal number of additional neutrinos.…”
Section: Introductionmentioning
confidence: 99%
“…• Symmetric gauge functions are strictly connected to the unitary invariant norms. We use unitary invariant norms in our study of the mixing matrices [36,37,98]. The symmetric gauge functions can provide a new perspective into the mixing analysis.…”
Section: Discussionmentioning
confidence: 99%
“…The rest of the eigenvalues of correspond to those of the submatrix. Our approach will be based on the Davis-Kahan theorem (Theorem C2), which is valid for the CP-conserving case (a generalization to the CP-violating case seems to be possible [91], but it requires a separate study). It allows us to estimate the sine of the angle between subspaces, denoted as , spanned by the eigenvectors.…”
Section: Separation Between Eigenspaces In the Seesaw Scenariomentioning
confidence: 99%