We have performed a statistical study of the properties of the broadband continuum of Narrow Line Seyfert 1 galaxies (NLS1s) by collecting ratio,infrared, optical and X-ray continuum data from various databases and comparedthe results with control samples of Broad Line Seyfert 1 galaxies (BLSls). We findthat the fraction (~ 6%) of Radio Loud (RL) NLSls is significantly less than thatof BLS1s (~ 13%), which is caused by the lack of radio-very-loud sources in theformer. The rarity of RL NLS1s, especially radio-very-loud ones, is consistent withthe scenario of small black hole and high accretion rate for NLSls. Six new radio loudNLSls are found and five RL NLS1 candidates are presented. In comparison withthe BLS1s, the NLS1s tend to have stronger far infrared emission, cooler infraredcolors and redder B- K color, which suggests that NLS1s are hosted by dust-richernuclei. The NLS1s also show steeper soft X-ray spectrum and large soft X-rayto optical flux ratio, while a significant fraction show fiat soft X-ray spectra. Atleast two factors can account for this, absorption and spectral variability. We alsoperform a correlation analysis between various broad band data. It is found thatmost correlations identified for NLS1s are also valid for radio quiet BLS1s: (1) theoptical colors are anti-correlated with X-ray spectral index; (2) higher optical, X-ray and NIR luminosity objects show bluer optical colors and red H - K color; (3)higher luminosity objects show warmer IRAS color; (4) the radio loudness correlateswith B - K and X-ray to optical flux ratio. Radio loud objects behave somewhatdifferently in a few correlations. 相似文献
It is an objective fact that there exists error in the satellite dynamic model and it will be transferred to satellite orbit determination algorithm, forming a part of the connotative model error. Mixed with the systematic error and random error of the measurements, they form the unitive model error and badly restrict the precision of the orbit determination. We deduce in detail the equations of orbit improvement for a system with dynamic model error, construct the parametric model for the explicit part of the model and nonparametric model for the error that can not be explicitly described. We also construct the partially linear orbit determination model, estimate and fit the model error using a two-stage estimation and a kernel function estimation, and finally make the corresponding compensation in the orbit determination. Beginning from the data depth theory, a data depth weight kernel estimator for model error is proposed for the sake of promoting the steadiness of model error estimation. Simulation experiments of SBSS are performed. The results show clearly that the model error is one of the most important effects that will influence the precision of the orbit determination. The kernel function method can effectively estimate the model error, with the window width as a major restrict parameter. A data depth-weight-kernel estimation, however, can improve largely the robustness of the kernel function and therefore improve the precision of orbit determination. 相似文献
Science China Earth Sciences - Helium gas is a scarce but important strategic resource, which is usually associated with natural gas. Presently, only one extra-large helium-rich gas field has been... 相似文献