Gravitational Lensing of Distant Field Galaxies by Rich Clusters

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Gravitational Lensing of Distant Field Galaxies by Rich Clusters Mon. Not. R. Astron. Soc. 270, 245-270 (1994) Gravitational lensing of distant field galaxies by rich clusters - I. Faint galaxy redshift distributions 1994MNRAS.270..245S Ian Smail,* Richard S. Ellist and Mike J. Fitchett:j: Downloaded from https://academic.oup.com/mnras/article-abstract/270/2/245/1163474 by California Institute of Technology user on 19 May 2020 Physics Department, University of Durham, South Road, Durham DHJ 3LE Accepted 1994 April 15. Received 1994 April 8; in original form 1993 December 9 ABSTRACT From deep optical images of three clusters, selected by virtue of their X-ray luminosity and/or optical richness (1455 + 22, z = 0.26; 0016 + 16, z = 0.55; 1603 + 43, z = 0.89), we construct statistically complete samples of faint field galaxies (/~25) that are suitable for probing the effects of gravitational lensing. By selecting clusters across a wide redshift range, we separate the effects of the mean redshift of the faint field population well beyond spectroscopic limits and the distribution of dark matter in the lensing clusters. A significant lensing signature is seen in the two lower redshift clusters, whose X-ray properties are well constrained. Based on these and dynamical data, it is straightforward to rule out field redshift distributions for 1~25, which have a significant low-redshift excess compared to the no-evolution prediction, such as would be expected if the number counts at faint limits were dominated by low-z dwarf systems. The degree to which we can constrain any high­ redshift tail to the no-evolution redshift distribution depends on the distribution of mass in the most distant lensing cluster. In the second paper in this series, we demonstrate that the mass distributions in our lensing clusters are well understood, by reconstructing the full two-dimensional distributions from the lensing signal. The principal result is therefore the absence of a dominant low-z dwarf population to 1~25. Key words: galaxies: distances and redshifts - galaxies: evolution - galaxies: formation - galaxies: photometry - cosmology: observations - gravitational lensing. population dominating the counts beyond B - 22 is thus of 1 INTRODUCTION considerable interest and depends critically on its redshift The surface density of faint galaxies is significantly in excess distribution. To the limits attainable with high-throughput of predictions based on extrapolating to large redshift the spectrographs on 4-m class telescopes (B - 24 ), no signifi­ known local properties of field galaxies, under the assump­ cant departure from the predicted no-evolution shape of the tion of no evolution (Kron 1978; Peterson et al. 1979; Tyson redshift distribution for B-selected samples has yet been seen & Jarvis 1979). The deepest optical counts are inconsistent (Broadhurst, Ellis & Shanks 1988; Colless et al. 1990, 1993; with both modest and no evolution, irrespective of the Cowie, Songaila & Hu 1991; Glazebrook et al. 1994). The cosmological geometry (Tyson 1988; Metcalfe et al. 1990; most rigorous statement on the redshift distribution can be Yoshii & Takahara 1990; Lilly, Cowie & Gardner 1991 ), and made to B = 22.5 (Colless et al. 1993 ), where the incomplete­ reveal a gradual bluing with increasing apparent magnitude ness in a sizeable sample is less than 5 per cent. At B - 24 and no convincing turnover to B - 28 (Metcalfe et al. 199 3 ). galaxies, where incompleteness remains "" 15 per cent The high surface density of blue light implies a star forma­ (Glazebrook et al. 1994 ), a proportion could be in a high­ tion rate that is sufficient to yield a significant fraction of the redshift tail with z ~ 1, but it is important to note that the metals in disc galaxies today (Cowie 1991 ). The nature of the incompleteness is negligible compared to the factor of x 4-6 by which the counts exceed the no-evolution prediction. *Present address: Caltech 105-24, Pasadena, CA 91125, USA. Notwithstanding the incompleteness, the bulk of the excess tpresent address: Institute of Astronomy, Madingley Road, population of blue sources, if it exists as a separate entity, Cambridge CB3 OHA. tPresent address: Medical School, University of Newcastle, must lie within a volume that is consistent with the no­ Framlington Place, Newcastle NE2 4HH. evolution prediction. © Royal Astronomical Society • Provided by the NASA Astrophysics Data System 246 I. Smail, R. S. Ellis and M. J. Fitchett Determining the nature of the excess population is hard, several clusters at different distances, but also, significantly, because of the difficulty of identifying representative by verifying the relative distribution of dark matter in the examples for scrutiny. So long as the excess population is lensing clusters, using a new inversion technique developed statistically defined, physical properties such as luminosity by Kaiser & Squires (1992). The latter result forms the basis functions · or clustering scalelengths cannot be reliably of the second paper in this series (Smail et al. 1994, Paper II), determined. Following Broadhurst et al.'s (1988) suggestion which should, ideally, be read in conjunction with this paper. 1994MNRAS.270..245S that the excess is associated with galaxies with intense [Ou] A plan of this paper follows. In Section 2, we briefly spectral emission, Cole et al. (1993) found the excess review the lensing test proposed. This serves to explain in Downloaded from https://academic.oup.com/mnras/article-abstract/270/2/245/1163474 by California Institute of Technology user on 19 May 2020 population to be cospatial with its quiescent counterpart, and more detail the logic of this paper and its companion article. Colless et al. ( 1994) found that such sources are often double In Section 3, we discuss the new observations, including systems. Such observations are consistent with the idea (but target selection, data acquisition and reduction. Section 4 by no means prove it) that star formation induced by merging presents various statistical tests we have applied to the faint may simultaneously explain the counts and redshift data (cf. catalogues in the context of model redshift distributions. Our Broadhurst, Ellis & Glazebrook 1992). On the other hand, constraints are discussed in Section 5 and our conclusions Efstathiou et al. (1991) and subsequent workers (e.g. Couch, are presented in Section 6. Jurcevic & Boyle 1993) present convincing evidence for a marked decrease in the angular clustering of B"" 26 galaxies, 2 THE LENSING METHOD AND PREVIOUS which may support an alternative viewpoint, which is that the WORK blue light arises in recent star formation in a separate dwarf galaxy population whose present-day counterparts cannot be Our method to determine the mean distance to an /:5.25 found (cf. Babul & Rees 1992). Some support for this model sample works as follows. The gravitational lensing of back­ has come from limited spectroscopic surveys, which have ground galaxies by the cluster potential produces a coherent concluded that there is an excess of dwarf systems at the pattern of image distortions, orthogonal to the cluster radius required redshifts (Cowie et al. 1991; Tresse et al. 199 3 ). vector (Grossman & Narayan 1988). Although the weak The importance of the angular correlation function studies signal is superimposed upon intrinsic ellipticities and of faint field samples lies in the fact that virtually all of the orientations of the population, its coherent nature can be sources, at B = 26 represent the excess population, i.e. diffi­ used to overcome the low signal-to-noise ratio inherent in culties in identifying the excess populations are largely the statistics of faint image shapes. Of course, neither faint removed. If it were possible to determine redshifts and cluster members nor sources foreground to the cluster con­ luminosities for such a faint sample, even if only statistically, tribute to the lensing signal. significant progress could be made. If the counts were The most elementary test measures the proportion of dominated to the faintest limits by a recent era of dwarf objects, to a fixed apparent magnitude limit, aligned tan­ galaxy formation, as proposed by Babul & Rees, it is con­ gentially to the radius vector to the lens centre. In the ceivable that the median redshift would hardly change for idealized case of a sample of identical lenses at different red­ samples fainter than B"" 24. For a simple merger model, the shifts zlens' i= 1 ... n, the variation in the fraction of aligned median redshift closely tracks the no-evolution prediction images with redshift delineates the shape of the field galaxy (cf. Broadhurst et al. 1992), whereas, if a significant fraction redshift distribution N(z). In practice, of course, clusters of B = 26 galaxies originates in a primordial population, have a variety of lensing powers, and the observed fraction is there would be a rapid increase in the median redshift. controlled not only by the combination of the field, N( z) and Unfortunately, conventional optical spectroscopy is Ziens' but also by the amount and concentration of mass in the rapidly approaching a hard faintness limit for two reasons. lens, M( r). To decouple these two factors, more complex State of the art faint object spectrographs, such as IDSS-2 analyses are required. (Allington-Smith et al. 1994) and MOSIS (Le Fevre 1993), The first stage of complexity is to allow some freedom in secure redshifts to B = 24 in 4-6 h exposures. Even with the core radius re (kpc) and the depth of the gravitational 10-m class telescopes, it will be painful to push the limits potential well [parametrized by ac1 (km s - i ), the velocity much beyond B=25. More importantly, Glazebrook et al. dispersion of the clusterJ in a given cluster, according to a (1994) demonstrate convincingly how, as [Ou] 3727 A is simple isothermal model. These parameters can be con­ redshifted beyond 8000 A (for sources with z > 1), no useful strained, to some extent, from X-ray imaging data and galaxy diagnostic features can be seen in the optical region, resulting dynamics.
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