The power spectrum estimator based on the Discrete Wavelet Transfor- mation (DWT) is applied to detect the clustering power in the IRAS Point Source Catalog Redshift Survey (PSCz). Comparison with mock samples extract...The power spectrum estimator based on the Discrete Wavelet Transfor- mation (DWT) is applied to detect the clustering power in the IRAS Point Source Catalog Redshift Survey (PSCz). Comparison with mock samples extracted from N-body simulation shows that the DWT power spectrum estimator could provide a robust measurement of banded fluctuation power over a range of wavenumbers 0.1 ~ 2.0hMpc-1. We have fitted three typical CDM models (SCDM, τCDM and CDM) using the Peacock-Dodds formula including non-linear evolution and redshift distortion. We find that, our results are in good agreement with other statistical measurements of the PSCz.展开更多
基金Supported by the National Natur al Science Foun dation of China.
文摘The power spectrum estimator based on the Discrete Wavelet Transfor- mation (DWT) is applied to detect the clustering power in the IRAS Point Source Catalog Redshift Survey (PSCz). Comparison with mock samples extracted from N-body simulation shows that the DWT power spectrum estimator could provide a robust measurement of banded fluctuation power over a range of wavenumbers 0.1 ~ 2.0hMpc-1. We have fitted three typical CDM models (SCDM, τCDM and CDM) using the Peacock-Dodds formula including non-linear evolution and redshift distortion. We find that, our results are in good agreement with other statistical measurements of the PSCz.
