An efficient method to identify supernova remnants is provided,in order to iron out the great gap between the predicted number and the observed.We make an attempt to apply D4 wavelet to detect the useful structures bu...An efficient method to identify supernova remnants is provided,in order to iron out the great gap between the predicted number and the observed.We make an attempt to apply D4 wavelet to detect the useful structures buried in radio map,showing that it is an efficient way to separate noises from signals.展开更多
Using the mock galaxy catalogues created from the N-body simulations,various biasing prescriptions for modeling the relative distribution between the galaxies and the underlying dark matter are statistically tested by...Using the mock galaxy catalogues created from the N-body simulations,various biasing prescriptions for modeling the relative distribution between the galaxies and the underlying dark matter are statistically tested by using scale-scale correlation.We found that the scale-scale correlation is capable of breaking the model degeneracy indicated by the low order clustering statistics,and could be taken as an effective discriminant among a variety of biasing models.Particularly,comparing with the APM bright galaxy catalogue,we infer that the two parameter Lagrangian biasing model gives the best fit to the observed clustering features.展开更多
Based on the discrete wavelet transformation (DWT), we prese nt apixelized method of estimating the power spectra of galaxy samples. With lo cal properties of wavelet both in physical and wavenumber spaces, DWT power ...Based on the discrete wavelet transformation (DWT), we prese nt apixelized method of estimating the power spectra of galaxy samples. With lo cal properties of wavelet both in physical and wavenumber spaces, DWT power spec trum is equal to the corresponding band average of Fourier power spectrum. The D WT estimator is optimized in the sense that the spatial resolution is adaptive a utomatically to the perturbation wavelength to be studied. Under the assumption of ergodicity, the spatial average of local DWT fluctuation modes provides a fai r estimation of the ensemble average. We test DWT spectra of four typical cold da rk matter (CDM) structure formation models with numerical simulations. To consid er the infections of various observation effects to the DWT spectra, we introduc e irregular survey geometries, a given sampling rate, radial selection effects a nd redshift distortion effects into our mock samples. The numerical results show that, owing to its local properties, DWT spectrum is less affected by the sampl ing rate, survey geometry, and statistical ensemble fluctuations. With fast wave let decomposition algorithm, DWT can be used to analyze large survey samples, wh i ch is of direct significance in precise measurement of the cosmological paramete rs from the galaxy redshift surveys of next generation.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos.19873009 and 19773017.
文摘An efficient method to identify supernova remnants is provided,in order to iron out the great gap between the predicted number and the observed.We make an attempt to apply D4 wavelet to detect the useful structures buried in radio map,showing that it is an efficient way to separate noises from signals.
基金Supported by the National Natural Science Foundation of China under Grant No.19873009the Chinese Academy of Sciences“Hundred Talents Program”the National Key Basic Research Science Foundation.
文摘Using the mock galaxy catalogues created from the N-body simulations,various biasing prescriptions for modeling the relative distribution between the galaxies and the underlying dark matter are statistically tested by using scale-scale correlation.We found that the scale-scale correlation is capable of breaking the model degeneracy indicated by the low order clustering statistics,and could be taken as an effective discriminant among a variety of biasing models.Particularly,comparing with the APM bright galaxy catalogue,we infer that the two parameter Lagrangian biasing model gives the best fit to the observed clustering features.
基金Feng Longlong and Chu Yaoquan acknowledge the support from the National Natural Science Foundation of China.
文摘Based on the discrete wavelet transformation (DWT), we prese nt apixelized method of estimating the power spectra of galaxy samples. With lo cal properties of wavelet both in physical and wavenumber spaces, DWT power spec trum is equal to the corresponding band average of Fourier power spectrum. The D WT estimator is optimized in the sense that the spatial resolution is adaptive a utomatically to the perturbation wavelength to be studied. Under the assumption of ergodicity, the spatial average of local DWT fluctuation modes provides a fai r estimation of the ensemble average. We test DWT spectra of four typical cold da rk matter (CDM) structure formation models with numerical simulations. To consid er the infections of various observation effects to the DWT spectra, we introduc e irregular survey geometries, a given sampling rate, radial selection effects a nd redshift distortion effects into our mock samples. The numerical results show that, owing to its local properties, DWT spectrum is less affected by the sampl ing rate, survey geometry, and statistical ensemble fluctuations. With fast wave let decomposition algorithm, DWT can be used to analyze large survey samples, wh i ch is of direct significance in precise measurement of the cosmological paramete rs from the galaxy redshift surveys of next generation.
