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How Li and Paczyński Model of Kilonova Fits GW170817 Optical Counterpart

100%

Kruszewski A.

2018

tom Vol. 68, No. 3

205--211

The original Li and Paczyński model of kilonova was compared with the observed bolometric optical light curve of the GW170817 electromagnetic counterpart. Perfect agreement is obtained for early observations up to 1.5 d since the time of merger.

A Simple Method of Correcting Magnitudes for the Errors Introduced by Atmospheric Refraction

63%

Kruszewski A. , Semeniuk I.

2003

tom Vol. 56, No. 3

241--248

We show that the errors due to atmospheric refraction are present in the magnitudes determined with the Difference Images Analysis method. In case of single, unblended stars the size of the effect agrees with the theoretical prediction. But when the blending is strong, what is quite common in a dense field, then the effect of atmospheric refraction can be strongly amplified to the extent that some cases of apparently variable stars with largest amplitudes of variations are solely due to refraction. We present a simple method of correcting for this kind of errors.

On Estimating Non-Uniform Density Distributions Using N Nearest Neighbors

63%

Woźniak P. R. , Kruszewski A.

2012

tom Vol. 62, No. 4

409--417

We consider density estimators based on the nearest neighbors method applied to discrete point distributions in spaces of arbitrary dimensionality. If the density is constant, the volume of a hypersphere centered at a random location is proportional to the expected number of points falling within the hypersphere radius. The distance to the N-th nearest neighbor alone is then a sufficient statistic for the density. In the non-uniform case the proportionality is distorted. We model this distortion by normalizing hypersphere volumes to the largest one and expressing the resulting distribution in terms of the Legendre polynomials. Using Monte Carlo simulations we show that this approach can be used to effectively address the trade-off between smoothing bias and estimator variance for sparsely sampled distributions.

BHP w rolnictwie. Cz. II

51%

Majczak W. , Mizgajski A. , Kruszewski A. , Karaś A.

tom 42

nr 08

Krotkoterminowe przewidywanie skutkow powodzi

51%

Grela J. , Konieczny R. , Kruszewski A.

nr 3

61-71

Przebieg powodzi i oslony hydrologicznej w dorzeczu gornej Wisly

51%

Drezinska B. , Kruszewski A. , Holda I.

nr 6

17-23