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.