The Power Spectrum
from the final 2dFGRS catalogue |

The power spectrum of the final galaxy catalogue is now available. For details of the method, see Cole et al. 2005, MNRAS, 363, 505

The power spectrum data, window functions and covariance matrix are available as text files from the links below. We also provide two simple "C" functions designed to demonstrate the use of these data to determine the likelihood of a given cosmological model.

- The power spectrum data (see header for details)

- The power spectrum covariance matrix
- The power spectrum window function
- Recovered C code to demonstrate likelihood
This C code demonstrates the steps necessary to compute the likelihood of a given model power spectrum.

- reading the window function and convolving the model power spectrum, that is to be tested, by the window function
- inverting the covariance matrix and scaling it according to the convolved model power spectrum
- differencing the 2dFGRS and model spectra and computing the likelihood

2dFGRS 2004 Spherical Harmonics analysis

Power Spectrum

The power spectrum data from the more detailed Spherical Harmonics analysis of Percival et al. (2004, MNRAS, 353, 1201) are available via a separate Spherical Harmonics page.

2dFGRS 2001 Data Release

Power Spectrum

The data from the 2001 fourier analysis of the incomplete catalogue 2dFGRS catalogue is also still available here. The power spectrum data and appropriate covariance matrix from Percival et al. (2001, MNRAS, 327, 1297) are available as text files from the links below.

Because of the difficulty of performing a 3D convolution with the appropriate survey window function (given a model power spectrum), a simple C program that demonstrates how this may be achieved for any

k-value is also available (note that this comes with no warranty).Given a sufficiently smooth

P(k), it is possible to speed up this process using the window function in matrix form. Such a matrix is also available from a link below for determining the convolved power spectrum at thek-values of the data. This file is organised as follows: the first line gives thek-values at which the convolvedP(k)is being calculated (chosen to be the same as the data); each subsequent line gives thek-value at which the unconvolvedP(k)should be determined (100 points), and the weights required to calculate the 32 convolvedP(k)values. The simple program given below demonstrates how to use this matrix and compares the result with the numerically convolvedP(k). If you use the matrix method, it is suggested that you check that the power spectra that you wish to convolve are sufficiently smooth that the two methods give the same answer (to the required accuracy).

Brief introduction- Percival et al. (2001, MNRAS, 327, 1297) (
ADS|astro-ph)- The power spectrum
data(see header for details)- The power spectrum
covariance matrix- The power spectrum
window function in matrix formSimple C codeto perform the 3D convolution with the window functionRecovered power spectrumfrom LCDM mock catalogues (see header for details)