Weak lensing analysis of MS 1008-1224 with the VLT

Astronomy and Astrophysics – Astrophysics

Scientific paper

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22 pages, submitted to A&A, paper with `big' figures available at ftp://ftp.cita.utoronto.ca/pub/waerbeke/ms1008paper/

Scientific paper

10.1051/0004-6361:20011779

We present a gravitational lensing analysis of the cluster of galaxies MS 1008-1224 (z=0.30), based on very deep observations obtained using the VLT with FORS and ISAAC during the science verification phase. We reconstructed the projected mass distribution from B,V,R,I bands using two different methods independently. The mass maps are remarkably similar, which confirm that the PSF correction worked well. The ISAAC and FORS data were combined to measure the photometric redshifts and constrain the redshift distribution of the lensed sources. The total mass inferred from weak shear is 2.3 10^{14} h^{-1} Mo on large scales, in agreement with the X-ray mass. The measured mass profile is well fit by both Navarro, Frenk and White and isothermal sphere with core radius models although the NFW is slightly better. In the inner regions, the lensing mass is about 2 times higher than the X-ray mass, which supports the view that complex physical processes in the innermost parts of clusters are responsible for the X-ray/lensing mass discrepancy. The central part of the cluster is composed of two mass peaks whose the center of mass is 15 arcsecond north of the cD galaxy. This provides an explanation for the 15 arcsecond offset between the cD and the center of the X-ray map reported elsewhere. The optical, X-ray and the mass distributions show that MS 1008-1224 is composed of many subsystems which are probably undergoing a merger. MS 1008-1224 shows a remarkable case of cluster-cluster lensing. The photometric redshifts show an excess of galaxies located 30 arcseconds south-west of the cD galaxy at a redshift of about 0.9 which is lensed by MS 1008-1224. These results show the importance of getting BVRIJK images silmultenously. The VLT is a unique tool to provide such datasets.

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