Statistics of the Optical Phase of a Gain-Switched Semiconductor Laser for Fast Quantum Randomness Generation

The statistics of the optical phase of the light emitted by a semiconductor laser diode when subject to periodic modulation of the applied bias current are theoretically analyzed. Numerical simulations of the stochastic rate equations describing the previous system are performed to describe the temporal dependence of the phase statistics. These simulations are performed by considering two cases corresponding to random and deterministic initial conditions. In contrast to the Gaussian character of the phase that has been assumed in previous works, we show that the phase is not distributed as a Gaussian during the initial stages of evolution. We characterize the time it takes the phase to become Gaussian by calculating the dynamical evolution of the kurtosis coefficient of the phase. We show that, under the typical gain-switching with square-wave modulation used for quantum random number generation, quantity is in the ns time scale; that corresponds to the time it takes the system to lose the memory of the distribution of the initial conditions. We compare the standard deviation of the phase obtained with random and deterministic initial conditions to show that their differences become more important as the modulation speed is increased.

The generalization of the hyperbolic secant distribution and the logistic distribution in the single distribution with variable kurtosis

The generalization V of the logistic distribution is proposed and investigated. For a random variable having a generalized logistic distribution of type V, the characteristic function is found, the generating function of moments is formed, and the expression of dispersion is obtained. The dependence of the kurtosis coefficient of the generalized logistic distribution on the power parameter is found and investigated. The interval of values of the coefficient of kurtosis of the generalized logistic distribution is determined. It is found that the coefficient of kurtosis depends only on the power parameter.

Impact Assessments of Rainfall–Runoff Characteristics Response Based on Land Use Change via Hydrological Simulation

The hydrology response was studied considering the established fact of land use change in Dapoling basin. The whole period was divided into two (1965–1985 and 1986–2012) according to the major land use and land cover change in this region. Xinanjiang model was used to simulate discharge data in the two periods. The hydrologic response to the change could be evaluated by inspecting the response of model parameters and flood elements. The results show that the lag time varied, and the hydrologic elements including the mean runoff depth, flood peak and kurtosis coefficient varied with the rainfall depth. This result is significant for studying the response of runoff characteristic from land use and land cover change.

Volatility filtering in estimation of kurtosis (and variance)

The kurtosis of the distribution of financial returns characterized by high volatility persistence and thick tails is notoriously difficult to estimate precisely. We propose a simple but effective procedure of estimating the kurtosis coefficient (and variance) based on volatility filtering that uses a simple GARCH model. In addition to an estimate, the proposed algorithm issues a signal of whether the kurtosis (or variance) is finite or infinite. We also show how to construct confidence intervals around the proposed estimates. Simulations indicate that the proposed estimates are much less median biased than the usual method-of-moments estimates, their confidence intervals having much more precise coverage probabilities. The procedure alsoworks well when the underlying volatility process is not the one the filtering technique is based on. We illustrate how the algorithm works using several actual series of returns.

Analysis of Rainfall in the Locality of Babahoyo, for the Programming of Cultivation of Rice (Oryza Sativa L.)

The work was carried out with the objective of knowing the precipitation regime of Babahoyo, Los Ríos in Ecuador and in this way contribute to the improvement of the cropping calendar of “rainfed rice", as this information is commonly required by farmers and agricultural professionals who work as agricultural advisers. A serie of record’s rainfalls were processed in about 35 years belonging to the Babahoyo’s Weather Station of the National Institute of Meteorology and Hydrology situated on the premises of the Faculty of Agricultural Sciences of theTechnical University of Babahoyo (UTB), the methodology applied focuses on the identification of statistics such as the mean, standard deviation, variance, coefficient of variation, asymmetry coefficient and kurtosis coefficient; then on the basis of average is determined dry and wet periods, the frequency and the intensity in which they occur. It was found that in this town from 1980 to 2014 occurred eight dry periods and seven wet periods, that occured with a frequency of 3.4 and 3.7 years respectively. Based on the results, the wet season is defined between the months from December to May and the dry season from June to November. The sheet available average cumulative rainfall, which is determined for wet and dry periods, has the following valuables: 1001,3 mm, 3169 mm and an average of 2167,7 mm. The rainfed rice in the area should be planted from the month of December, to be taken advantage of all the rain of the wet season.

Análisis Del Comportamiento De Las Precipitaciones En Quevedo - Ecuador, Para La Planificación De Cultivos

The work was performed with the aim of knowing the rainfall of the city of Quevedo in Ecuador, to improve the calendars of short-cycle crops, since this information is commonly required by farmers in the area and agricultural professionals who work as technical advisers. Processing a series of recordings of rainfall of 35 years belonging to the Pichilingue Weather Station of the National Institute of Meteorology and Hydrology located on the premises of the National Agricultural Research Institute, the methodology applied was focuses on the determination of statisticians as the average, Standard Deviation, Variance, coefficient of variation, skewness and kurtosis coefficient; then based on the average are determined wet and dry periods the frequency and the intensity with which they occur. That also was detected in this town from 1980 to 2014 there were 10 dry periods and nine wet periods, which are presented with a frequency of 3,8 and 3,6 years respectively. Based on the results, the wet season is defined between the months of December to May and the dry season from June to November. The foil available average rain accumulated determined for the wet and dry periods has the following values: 953,3 mm, 2924,2 mm and an average of 2216,3 mm. Short-cycle crops of the area should be planted since the month of December to be exploited all the rain of the wet season.

W-Peakedness: A Simulation based Study

Kurtosis is a commonly used descriptive statistics. Kurtosis “Coefficient of excess” is critically reviewed in different aspects and is called as, measuring the fatness of the tails of the density functions, concentration towards the central value, scattering away from the target point or degree of peakedness of probability distribution. Kurtosis is referred to the shape of the distribution but many distributions having same kurtosis value may have different shapes while Kurtosis may exist when peak of a distribution is not in existence. Through extensive study of kurtosis on several distributions, Wu (2002) introduced a new measure called “W-Peakedness” that offers a fine capture of distribution shape to provide an intuitive measure of peakedness of the distribution which is inversely proportional to the standard deviation of the distribution. In this paper the work is extended for different others continuous probability distributions. Empirical results through simulation illustrate the proposed method to evaluate kurtosis by W-peakedness

Rapid Temporal Changes of Boundary Layer Winds

The statistical distribution of the magnitude of the vector wind change over 0.25-, 0.5-, 1-, and 2-h periods based on central Florida data from November 1999 through August 2001 is presented. The distributions of the 2-h u and υ wind-component changes are also presented for comparison. The wind changes at altitudes from 500 to 3000 m were measured using the Eastern Range network of five 915-MHz Doppler radar wind profilers. Quality-controlled profiles were produced every 15 min for up to 60 gates, each representing 101 m in altitude over the range from 130 to 6089 m. Five levels, each constituting three consecutive gates, were selected for analysis because of their significance to aerodynamic loads during the space-shuttle-ascent roll maneuver. The distribution of the magnitude of the vector wind change is found to be lognormal, consistent with earlier work in the midtroposphere. The parameters of the distribution vary with time lag, season, and altitude. The component wind changes are symmetrically distributed, with near-zero means, but the kurtosis coefficient is larger than that of a Gaussian distribution.