We define an iterative error-minimizing secret key adapting method for multicarrier CVQKD. A multicarrier CVQKD protocol uses Gaussian subcarrier quantum continuous variables (CVs) for the transmission. The proposed method allows for the parties to reach a given target secret key rate with minimized error rate through the Gaussian subchannels by a sub-channel adaption procedure. The adaption al...

this paper proposes a hybrid method to find cumulative distribution function (cdf) of completion time of gert-type networks (gtn) which have no loop and have only exclusive-or nodes. proposed method is cre-ated by combining an analytical transformation with gaussian quadrature formula. also the combined crude monte carlo simulation and combined conditional monte carlo simulation are developed a...

By means of N-body simulations, we study the evolution of gravity-dominated systems from an early relaxation to a collapse, focusing on the velocity distributions and thermodynamic properties. To simulate the dynamical evolution, we consider self-gravitating small N-body systems enclosed in a spherical container with adiabatic or semipermeable walls. It is demonstrated that in the early relaxat...

We study a new class of matrix models, formulated on a lattice. On each site are N states with random energies governed by a Gaussian random matrix Hamiltonian. The states on different sites are coupled randomly. We calculate the density of and correlation between the eigenvalues of the total Hamiltonian in the large N limit. We find that this correlation exhibits the same type of universal beh...

Here I introduce package cmvnorm, a complex generalization of the mvtnorm package. A complex generalization of the Gaussian process is suggested and numerical results presented using the package. An application in the context of approximating the Weierstrass σ-function using a complex Gaussian process is given.

We propose two nonlinear Kalman smoothers that rely on Student’s t distributions. The T-Robust smoother finds the maximum a posteriori likelihood (MAP) solution for Gaussian process noise and Student’s t observation noise, and is extremely robust against outliers, outperforming the recently proposed `1-Laplace smoother in extreme situations (e.g. 50% or more outliers). The second estimator, whi...

Frequency-magnitude distributions, and their associated uncertainties, are of key importance in statistical seismology. When fitting these distributions , the assumption of Gaussian residuals is invalid since event numbers are both discrete and of unequal variance. In general, the observed number in any given magnitude range is described by a binomial distribution which, given a large total num...

We study learning curves for Gaussian process regression which characterise performance in terms of the Bayes error averaged over datasets of a given size. Whilst learning curves are in general very difficult to calculate we show that for discrete input domains, where similarity between input points is characterised in terms of a graph, accurate predictions can be obtained. These should in fact...

The range distributions of low-energy nitrogen and oxygen (2-3 keV) ions is silicon are measured and compared with these available in theories. The nitrogen distribution is very close to a Gaussian distribution as predicted by theory. The oxygen profile however, indicates a surface localized peak along with a shoulder and a long tail into the sample. The surface peak is beleived to he the resul...