Neutrino mixing and masses in a left-right model with mirror fermions

In the framework of a left-right model containing mirror fermions with gauge group SU(3)$_{C} \otimes SU(2)_{L} \otimes SU(2)_{R} \otimes U(1)_{Y^\prime}$, we estimate the neutrino masses, which are found to be consistent with their experimental bounds and hierarchy. We evaluate the decay rates of the Lepton Flavor Violation (LFV) processes $\mu \rightarrow e \gamma$, $\tau \rightarrow \mu \gamma$ and $\tau \rightarrow e\gamma$. We obtain upper limits for the flavor-changing branching ratios in agreement with their present experimental bounds. We also estimate the decay rates of heavy Majorana neutrinos in the channels $N \rightarrow W^{\pm} l^{\mp}$, $N \rightarrow Z \nu_{l}$ and $N \rightarrow H \nu_{l}$, which are roughly equal for large values of the heavy neutrino mass. Starting from the most general Majorana neutrino mass matrix, the smallness of active neutrino masses turns out from the interplay of the hierarchy of the involved scales and the double application of seesaw mechanism. An appropriate parameterization on the structure of the neutrino mass matrix imposing a symmetric mixing of electron neutrino with muon and tau neutrinos leads to Tri-bimaximal mixing matrix for light neutrinos.Comment: Accepted by European Physical Journal

Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN) deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain), while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2) model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation.</p> <p style='line-height: 20px;'><b>Keywords: </b>neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series.</p>

Excitations in the quantum paramagnetic phase of the quasi-one-dimensional Ising magnet CoNb2_2O6_6 in a transverse field: Geometric frustration and quantum renormalization effects

The quasi-one-dimensional (1D) Ising ferromagnet CoNb$_2$O$_6$ has recently been driven via applied transverse magnetic fields through a continuous quantum phase transition from spontaneous magnetic order to a quantum paramagnet, and dramatic changes were observed in the spin dynamics, characteristic of weakly perturbed 1D Ising quantum criticality. We report here extensive single-crystal inelastic neutron scattering measurements of the magnetic excitations throughout the three-dimensional (3D) Brillouin zone in the quantum paramagnetic phase just above the critical field to characterize the effects of the finite interchain couplings. In this phase, we observe that excitations have a sharp, resolution-limited line shape at low energies and over most of the dispersion bandwidth, as expected for spin-flip quasiparticles. We map the full bandwidth along the strongly dispersive chain direction and resolve clear modulations of the dispersions in the plane normal to the chains, characteristic of frustrated interchain couplings in an antiferromagnetic isosceles triangular lattice. The dispersions can be well parametrized using a linear spin-wave model that includes interchain couplings and further neighbor exchanges. The observed dispersion bandwidth along the chain direction is smaller than that predicted by a linear spin-wave model using exchange values determined at zero field, and this effect is attributed to quantum renormalization of the dispersion beyond the spin-wave approximation in fields slightly above the critical field, where quantum fluctuations are still significant.Comment: 11 pages, 6 figures. Updated references. Minor changes to text and figure

Bachia heteropa

Number of Pages: 10Integrative BiologyGeological Science

The Adapted Ordering Method for Lie Algebras and Superalgebras and their Generalizations

In 1998 the Adapted Ordering Method was developed for the representation theory of the superconformal algebras in two dimensions. It allows: to determine maximal dimensions for a given type of space of singular vectors, to identify all singular vectors by only a few coefficients, to spot subsingular vectors and to set the basis for constructing embedding diagrams. In this article we present the Adapted Ordering Method for general Lie algebras and superalgebras, and their generalizations, provided they can be triangulated. We also review briefly the results obtained for the Virasoro algebra and for the N=2 and Ramond N=1 superconformal algebras.Comment: Many improvements in the redaction for pedagogical purposes. Latex, 11 page