Dissipation Efficiency in Turbulent Convective Zones in Low Mass Stars

We extend the analysis of Penev et al. (2007) to calculate effective viscosities for the surface convective zones of three main sequence stars of 0.775Msun, 0.85Msun and the present day Sun. In addition we also pay careful attention to all normalization factors and assumptions in order to derive actual numerical prescriptions for the effective viscosity as a function of the period and direction of the external shear. Our results are applicable for periods that are too long to correspond to eddies that fall within the inertial subrange of Kolmogorov scaling, but no larger than the convective turnover time, when the assumptions of the calculation break down. We find linear scaling of effective viscosity with period and magnitudes at least three times larger than the Zahn (1966, 1989) prescription.Comment: 13 pages, 3 figures Effective viscosity scaling changed by a factor of ~100. More details provided for the numerical model

Free search in multidimensional space

One of the challenges for modern search methods is resolving multidimensional tasks where optimization parameters are hundreds, thousands and more. Many evolutionary, swarm and adaptive methods, which perform well on numerical test with up to 10 dimensions are suffering insuperable stagnation when are applied to the same tests extended to 50, 100 and more dimensions. This article presents an original investigation on Free Search, Differential Evolution and Particle Swarm Optimization applied to multidimensional versions of several heterogeneous real-value numerical tests. The aim is to identify how dimensionality reflects on the search space complexity, in particular to evaluate relation between tasks’ dimensions’ number and corresponding iterations’ number required by used methods for reaching acceptable solution with non-zero probability. Experimental results are presented and analyzed

DERMATOPHYTE FLORA IN THE DISTRICT OF VARNA

No abstract

Image Subtraction Reduction of Open Clusters M35 & NGC 2158 In The K2 Campaign-0 Super-Stamp

Observations were made of the open clusters M35 and NGC 2158 during the initial K2 campaign (C0). Reducing these data to high-precision photometric time-series is challenging due to the wide point spread function (PSF) and the blending of stellar light in such dense regions. We developed an image-subtraction-based K2 reduction pipeline that is applicable to both crowded and sparse stellar fields. We applied our pipeline to the data-rich C0 K2 super-stamp, containing the two open clusters, as well as to the neighboring postage stamps. In this paper, we present our image subtraction reduction pipeline and demonstrate that this technique achieves ultra-high photometric precision for sources in the C0 super-stamp. We extract the raw light curves of 3960 stars taken from the UCAC4 and EPIC catalogs and de-trend them for systematic effects. We compare our photometric results with the prior reductions published in the literature. For detrended, TFA-corrected sources in the 12--12.25 $\rm K_{p}$ magnitude range, we achieve a best 6.5 hour window running rms of 35 ppm falling to 100 ppm for fainter stars in the 14--14.25 $\rm K_{p}$ magnitude range. For stars with $\rm K_{p}> 14$, our detrended and 6.5 hour binned light curves achieve the highest photometric precision. Moreover, all our TFA-corrected sources have higher precision on all time scales investigated. This work represents the first published image subtraction analysis of a K2 super-stamp. This method will be particularly useful for analyzing the Galactic bulge observations carried out during K2 campaign 9. The raw light curves and the final results of our detrending processes are publicly available at \url{http://k2.hatsurveys.org/archive/}.Comment: Accepted for publication in PASP. 14 pages, 5 figures, 2 tables. Light curves available from http://k2.hatsurveys.org/archive

Adaptive intelligence applied to numerical optimisation

The article presents modification strategies theoretical comparison and experimental results achieved by adaptive heuristics applied to numerical optimisation of several non-constraint test functions. The aims of the study are to identify and compare how adaptive search heuristics behave within heterogeneous search space without retuning of the search parameters. The achieved results are summarised and analysed, which could be used for comparison to other methods and further investigation

GeD spline estimation of multivariate Archimedean copulas

A new multivariate Archimedean copula estimation method is proposed in a non-parametric setting. The method uses the so-called Geometrically Designed splines (GeD splines) to represent the cdf of a random variable Wθ, obtained through the probability integral transform of an Archimedean copula with parameter θ. Sufficient conditions for the GeD spline estimator to possess the properties of the underlying theoretical cdf, K(θ,t), of Wθ, are given. The latter conditions allow for defining a three-step estimation procedure for solving the resulting non-linear regression problem with linear inequality constraints. In the proposed procedure, finding the number and location of the knots and the coefficients of the unconstrained GeD spline estimator and solving the constraint least-squares optimisation problem are separated. Thus, the resulting spline estimator View the MathML source is used to recover the generator and the related Archimedean copula by solving an ordinary differential equation. The proposed method is truly multivariate, it brings about numerical efficiency and as a result can be applied with large volumes of data and for dimensions d≥2, as illustrated by the numerical examples presented

High Precision Photometry for K2 Campaign 1

The two reaction wheel K2 mission promises and has delivered new discoveries in the stellar and exoplanet fields. However, due to the loss of accurate pointing, it also brings new challenges for the data reduction processes. In this paper, we describe a new reduction pipeline for extracting high precision photometry from the K2 dataset, and present public light curves for the K2 Campaign 1 target pixel dataset. Key to our reduction is the derivation of global astrometric solutions from the target stamps, from which accurate centroids are passed on for high precision photometry extraction. We extract target light curves for sources from a combined UCAC4 and EPIC catalogue -- this includes not only primary targets of the K2 campaign 1, but also any other stars that happen to fall on the pixel stamps. We provide the raw light curves, and the products of various detrending processes aimed at removing different types of systematics. Our astrometric solutions achieve a median residual of ~ 0.13". For bright stars, our best 6.5 hour precision for raw light curves is ~20 parts per million (ppm). For our detrended light curves, the best 6.5 hour precisions achieved is ~15 ppm. We show that our detrended light curves have fewer systematic effects (or trends, or red-noise) than light curves produced by other groups from the same observations. Example light curves of transiting planets and a Cepheid variable candidate, are also presented. We make all light curves public, including the raw and de-trended photometry, at http://k2.hatsurveys.org.Comment: submitted to MNRA