Constraining the parameters of the LN model with reconstructed power spectrum of Ly-α forest

Astronomy and Astrophysics – Astrophysics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

A sample of three quasar spectra observed by the Keck telescope is selected to reconstruct the perturbations of mass density using the Gaussianization method, with a calculation of the corresponding wavelet power spectra. The two parameters in the lognormal (LN) model, namely the shape factor Γ and the Jeans smoothing factor r, are set as free parameters. Their most probable values are determined by comparing the result of statistical analysis on the observed sample with that on a simulated sample, and they are: Γ0.50 and r0.09. Non-Gaussian features in the quasar spectra can not be excluded using the traditional Gaussianization method. However, on the scales larger than 100 kpc, these features have little or no influence on our results described above. This argument has been verified by comparing the observed sample with the simulated sample as regards their skewness and kurtosis spectra, as well as their scale-scale correlations.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Constraining the parameters of the LN model with reconstructed power spectrum of Ly-α forest does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Constraining the parameters of the LN model with reconstructed power spectrum of Ly-α forest, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Constraining the parameters of the LN model with reconstructed power spectrum of Ly-α forest will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-874402

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.