We built our cluster sample by taking into account existing samples, such as the Abell (Abell et al. 1989) and MACS (Ebeling et al. 2001; Ebeling et al. 2010) cluster catalogs, the LoCuSS and CLASH surveys, the Weighing the Giants and CCCP projects, to build a first extended list of possible cluster targets.
We then mined the CADC and the SMOKA archives to find the publicly available MegaCam@CFHT and SuprimeCam@Subaru exposures within 90 arcmin of these clusters. Given the archival data availability, we performed a first-pass target selection by requiring:
- the cluster redshift to be in the range 0.1 < z < 0.7;
- that data taken in at least two broad-band filters are available;
- that the total exposure time of the available data in the lensing band (either R or I) is at least ~ 4000 s.
We have downloaded the available scientific (and, when necessary, calibration) data for this preliminary cluster sample, and we are currently performing the data reduction (for the SuprimeCam/Subaru data) and quality evaluation (for both the SuprimeCam/Subaru and MegaCam/CFHT data) to assess the amount of available data suitable to perform a weak lensing analysis, and thus define our final cluster sample.
Our preliminary sample of galaxy clusters can be found below:
For an accurate weak lensing analysis, it is crucial to perform a careful data reduction and selection.
Since our analysis is based on a large amount of archival data, we haven’t a direct control of the observational strategy, and an extensive check of all the pre-selected data is impossible.
These issues require some ad-hoc solutions, and some caveats should be kept in mind. For example:
– It is very important to select, among all the available frames, only the observations that are suitable to our analysis, and discard those that would degrade or bias our analysis.
But a visual inspection of the large((It’s really a large number: to give you an idea, we are talking of more than 20.000 SuprimeCam exposures, and more than 3000 MegaCam exposures!)) number of wide-field observations that we are analyzing would not be feasible.
Therefore, the quality check of the science exposures is performed by visual inspection of the SPREAD_MODEL vs the Signal-to-noise ratio (SNR) plot. This plot is proven to be an effective diagnostic tools to identify exposures for which the PSF modeling was problematic (see e.g. Bouy et al., 2013). Both the SPREAD_MODEL and SNR parameters are derived from the object catalogs obtained with SExtractor. The SPREAD_MODEL is defined to be:
- positive for extended sources, such as galaxies;
- negative for detections smaller than the PSF;
- close to zero for point sources.
The movie below, shows this diagnostic plot for a selection of CFHT images”