CBI Data Products on LAMBDA

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Band Powers

A small fraction of the data are common with the deep data set (see the papers). There are two alternate binnings of the power spectrum, which are not independent; in both the bin width is 200 in l except for the first bin.
* Even binning: 14 bins: l = 0-400, 400-600, 600-800, ..., 2800-3000.
* Odd binning: 14 bins: l = 0-300, 300-500, 500-700, ..., 2700-2900.

Band Power Window Functions

The file deep_windows.tar.gz (compressed tar file) contains 14 files, one for each band:
* joint_3deep_std2_best_window_* (7 files).
* joint_3deep_alt2_best_window_* (6 files).
* joint_3deep_bigbin_best_window_5 (1 file).
The window functions are tabulated in bins of width 90 in l, i.e., l = 1-90, 91-180, ...; and the tabulated values should be divided by 90 to get the quantity plotted in Mason et al.(2003), WB(l)/l.

Parameter Covariance Matrices


These files should be interpreted as follows:

qb file
There are 7 (std2) or 6 (alt2) entries, one for each band. Column 1 is the band number; column 2 is the band power qB, and column 3 is the uncertainty on the band power (square root of the diagonal element of the covariance matrix). Band powers are dimensionless; multiply by Tcmb2 to put them in temperature units.

invfish file
Ignore the first 6 lines in this file. The first 7 (std2) or 6 (alt2) columns of the next 7 (std2) or 6 (alt2) lines give the 7 by 7 or 6 by 6 band-power covariance matrix. This is the inverse of the curvature (Hessian) matrix as given in equation 75 of Myers et al., and it can be used directly to give a gaussian approximation to the likelihood function.

otherps file
It is better to use an offset lognormal approximation to the likelihood function (Sievers et al., equation 2), for which you need the offsets qNtB. The offsets are given in the otherps file, which contains 7 (or 6) entries, one for each bin. There are 4 columns giving the component band-powers for noise and discrete sources. You should add all four components to get the required band-power offset.

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