Data Preparation
We need a lens and a source catalog to calculate the galaxy-galaxy lensing signal. Fortunately, many data sets are publicly available, such as data from HSC or CFHTLenS. Once we have obtained the data, we need to convert it into a format understandable by dsigma
.
Generally, dsigma
expects all lens, source, and calibration catalogs to be astropy
tables with data stored in specific, pre-defined columns.
Lens Catalog
The following columns are required for lens catalogs.
ra
: right ascension in degreesdec
: declination in degreesz
: best-fit redshiftw_sys
: systematic weight \(w_{\mathrm{sys}}\)
The weight \(w_{\mathrm{sys}}\) is often used to mitigate systematics in the lens selection.
Source Catalog
The following columns are required for source catalogs.
ra
: right ascension in degreesdec
: declination in degreesz
: best-fit photometric redshiftw
: inverse variance weight for galaxy shapee_1
: + component of ellipticitye_2
: x component of ellipticity
Additionally, the following columns may be used in the analysis.
m
: multiplicative shear biase_rms
: root mean square ellipticityR_2
: HSC resolution factor (0=unresolved, 1=resolved)R_11
,R_22
,R_12
,R_21
: METACALIBRATION shear responsez_bin
: tomographic redshift bin, non-negative and starts at 0
Calibration Catalog
The following columns are required in (optional) calibration catalogs.
z
: best-fit photometric redshiftz_true
: “true” redshiftw
: inverse variance weight for galaxy shapew_sys
: systematic weight \(w_{\mathrm{sys}}\)
The weight \(w_{\mathrm{sys}}\) is used to offset, for example, color differences between the source and the calibration catalog. Additionally, the columns z_low
and z_err
may also be present in the calibration catalog with the same meaning as in the source catalog.