{\it Hubble Space Telescope} Observations of the Galaxy Population of a Rich Cluster at $z=0.9$

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Session 53 -- Clusters of Galaxies I
Display presentation, Tuesday, 10, 1995, 9:20am - 6:30pm

[53.10] {\it Hubble Space Telescope} Observations of the Galaxy Population of a Rich Cluster at $z=0.9$

S.C. Trager, S.M. Faber (UCO/Lick Observatory), Edward J.\ Groth (Princeton), Jon A.\ Holtzman (Lowell Observatory), Roger Lynds, Earl J.\ O'Neil, Jr. (KPNO), WF/PC IDT (vaious institutions)

We present first results from an extremely deep (16 orbit) Hubble Space Telescope\/ WFPC-2 image of the $z=0.9$ cluster Cl1603+4313, taken as part of the GTO program of the WFPC IDT. All 16 images were taken in the F814W ($I_{814}$) filter, which has a rest-frame bandpass response of roughly Johnson B at the redshift of this cluster. The cluster center lies slightly outside of the area covered by the image, so we can sample the cluster density profile and galaxy morphologies in the outer regions of the cluster. The $3\sigma$ surface brightness limit is $I_{814} \approx 25.3$ mag arcsec$^{-2}$, corresponding to a rest-frame surface brightness limit of $\mu_B\approx 23.5$ mag arcsec$^{-2}$. This is faint enough to discern spiral structure in member galaxies and even to sample the bright end of a dwarf galaxy population comparable to that in present-day clusters, if such a population exists at $z=0.9$. Similarly to studies of lower-redshift ($z\approx 0.3$--$0.4$) clusters, we find a dearth of elliptical-like galaxies, the major component of present-day clusters. These galaxies seem to have been replaced by spiral and morphologically-disturbed galaxies in this very distant cluster. Furthermore, a significant number of interacting galaxies is readily identified. Also, large populations of faint, clumpy objects and very-low-surface-brightness objects are present in the image. These populations may give us hints about the formation of galaxies in this cluster. Further work will include studies of galaxy surface brightnesses and length scales and nearest-neighbor clustering.

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