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
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.
