  We investigate structures in the D1 CFHTLS deep field in order to test the
method that will be applied to generate homogeneous samples of clusters and
groups of galaxies in order to constrain cosmology and detailed physics of
groups and clusters. Adaptive kernel technique is applied on galaxy catalogues.
This technique needs none of the usual a-priori assumptions (luminosity
function, density profile, colour of galaxies) made with other methods. Its
main drawback (decrease of efficiency with increasing background) is overcame
by the use of narrow slices in photometric redshift space. There are two main
concerns in structure detection. One is false detection and the second, the
evaluation of the selection function in particular if one wants "complete"
samples. We deal here with the first concern using random distributions. For
the second, comparison with detailed simulations is foreseen but we use here a
pragmatic approach with comparing our results to GalICS simulations to check
that our detection number is not totally at odds compared to cosmological
simulations. We use XMM-LSS survey and secured VVDS redshifts up to z~1 to
check individual detections. We show that our detection method is basically
capable to recover (in the regions in common) 100% of the C1 XMM-LSS X-ray
detections in the correct redshift range plus several other candidates.
Moreover when spectroscopic data are available, we confirm our detections, even
those without X-ray data.
