256,395 research outputs found
Hierarchical majorana neutrinos from democratic mass matrices
In this paper, we obtain the light neutrino masses and mixings consistent
with the experiments, in the democratic texture approach. The essential ansatz
is that are assumed to transform as "right-handed fields" under the symmetry. The symmetry breaking terms
are assumed to be diagonal and hierarchical. This setup only allows the normal
hierarchy of the neutrino mass, and excludes both of inverted hierarchical and
degenerated neutrinos.
Although the neutrino sector has nine free parameters, several predictions
are obtained at the leading order. When we neglect the smallest parameters
and , all components of the mixing matrix are expressed by the masses of light neutrinos and charged leptons. From
the consistency between predicted and observed , we obtain the
lightest neutrino masses = (1.1 1.4) meV, and the effective mass
for the double beta decay \vev{m_{ee}} \simeq 4.5 meV.Comment: 14 pages, 1 table, substantially revised versio
Evolutionary algorithms for dynamic optimization problems: workshop preface
Copyright @ 2005 AC
Flavor structure from misalignment of inner products in noncommutative geometry
In this letter, we consider an idea that induces flavor structure from inner
products in noncommutative geometry. Assuming proper components of vectors
in enlarged representation space for fermions, we can induce the
waterfall texture for Yukawa matrices retaining gauge interactions are
universal. The hierarchy of the Yukawa interactions is a consequence of
"misalignment" between the vectors and .Comment: 6pages, 1 table, the final version to appear in JHE
Explicit memory schemes for evolutionary algorithms in dynamic environments
Copyright @ 2007 Springer-VerlagProblem optimization in dynamic environments has atrracted a growing interest from the evolutionary computation community in reccent years due to its importance in real world optimization problems. Several approaches have been developed to enhance the performance of evolutionary algorithms for dynamic optimization problems, of which the memory scheme is a major one. This chapter investigates the application of explicit memory schemes for evolutionary algorithms in dynamic environments. Two kinds of explicit memory schemes: direct memory and associative memory, are studied within two classes of evolutionary algorithms: genetic algorithms and univariate marginal distribution algorithms for dynamic optimization problems. Based on a series of systematically constructed dynamic test environments, experiments are carried out to investigate these explicit memory schemes and the performance of direct and associative memory schemes are campared and analysed. The experimental results show the efficiency of the memory schemes for evolutionary algorithms in dynamic environments, especially when the environment changes cyclically. The experimental results also indicate that the effect of the memory schemes depends not only on the dynamic problems and dynamic environments but also on the evolutionary algorithm used
Asymmetric vortex solitons in nonlinear periodic lattices
We reveal the existence of asymmetric vortex solitons in ideally symmetric
periodic lattices, and show how such nonlinear localized structures describing
elementary circular flows can be analyzed systematically using the
energy-balance relations. We present the examples of rhomboid, rectangular, and
triangular vortex solitons on a square lattice, and also describe novel
coherent states where the populations of clockwise and anti-clockwise vortex
modes change periodically due to a nonlinearity-induced momentum exchange
through the lattice. Asymmetric vortex solitons are expected to exist in
different nonlinear lattice systems including optically-induced photonic
lattices, nonlinear photonic crystals, and Bose-Einstein condensates in optical
lattices.Comment: 4 pages, 5 figure
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