Progress in the study of galaxy evolution has traditionally followed from improvements in spectroscopic measurement techniques and subsequent groundbreaking surveys. The advent of large format CCD detectors, coupled with the demonstrated success of the photometric redshift method, has given rise to a new, potentially very powerful alternative. It has, in fact, motivated the present detailed investigation of the potential of photometric redshift surveys to complement, or in some cases, supersede traditional spectroscopic surveys in galaxy evolution studies.
This Thesis describes a new deep, wide-field, multi-colour imaging survey, 10 times deeper and 30 times larger than its spectroscopic predecessor, the Canada-France Redshift Survey (CFRS). Highly accurate photometric redshifts, calibrated using hundreds of spectroscopic CFRS galaxies, were measured for tens of thousands of objects, with typical dispersions of only sigma/(1+z) < 0.06 to I(AB) = 24 for z < 1.3.
A new Bayesian method to measure the galaxy redshift distribution is developed. The accuracy of the method, which incorporates the full redshift likelihood function of each galaxy in an iterative analysis, is demonstrated in extensive Monte Carlo simulations. I(AB) and R(AB) redshift distributions, along with the run of median redshifts, are measured in various magnitude ranges, with special attention given to quantifying both random and systematic errors.
We measure the evolution of galaxy correlations with redshift, a primary observable of the structure formation process, correcting for the dilutive effect of photometric redshift errors on the clustering signal. The high z ~ 3 correlation amplitude seen in this work provides compelling evidence for the biased galaxy formation paradigm. The measured galaxy correlations from 0 < z < 3 are in excellent agreement with the findings of the largest, state-of-the-art spectroscopic studies.
For the 1- and 2-point statistics of the galaxy distribution studied in this Thesis, the measurement accuracy is limited not by the photometric redshift error, but rather by the effect of cosmic variance, whose contribution to the total error budget is dominant. Therefore, future studies will be well served by adopting the photometric redshift approach, the efficiency of which will enable them to survey the hundreds or thousands of square degrees required to obtain a fair sample of the Universe.
Progress in the study of galaxy evolution has traditionally followed from improvements in spectroscopic measurement techniques and subsequent groundbreaking surveys. The advent of large format CCD detectors, coupled with the demonstrated success of the photometric redshift method, has given rise to a new, potentially very powerful alternative. It has, in fact, motivated the present detailed investigation of the potential of photometric redshift surveys to complement, or in some cases, supersede traditional spectroscopic surveys in galaxy evolution studies.
This Thesis describes a new deep, wide-field, multi-colour imaging survey, 10 times deeper and 30 times larger than its spectroscopic predecessor, the Canada-France Redshift Survey (CFRS). Highly accurate photometric redshifts, calibrated using hundreds of spectroscopic CFRS galaxies, were measured for tens of thousands of objects, with typical dispersions of only sigma/(1+z) < 0.06 to I(AB) = 24 for z < 1.3.
A new Bayesian method to measure the galaxy redshift distribution is developed. The accuracy of the method, which incorporates the full redshift likelihood function of each galaxy in an iterative analysis, is demonstrated in extensive Monte Carlo simulations. I(AB) and R(AB) redshift distributions, along with the run of median redshifts, are measured in various magnitude ranges, with special attention given to quantifying both random and systematic errors.
We measure the evolution of galaxy correlations with redshift, a primary observable of the structure formation process, correcting for the dilutive effect of photometric redshift errors on the clustering signal. The high z ~ 3 correlation amplitude seen in this work provides compelling evidence for the biased galaxy formation paradigm. The measured galaxy correlations from 0 < z < 3 are in excellent agreement with the findings of the largest, state-of-the-art spectroscopic studies.
For the 1- and 2-point statistics of the galaxy distribution studied in this Thesis, the measurement accuracy is limited not by the photometric redshift error, but rather by the effect of cosmic variance, whose contribution to the total error budget is dominant. Therefore, future studies will be well served by adopting the photometric redshift approach, the efficiency of which will enable them to survey the hundreds or thousands of square degrees required to obtain a fair sample of the Universe.
This thesis presents the results from a comprehensive study of 26 low-redshift galaxy clusters in order to study the radial dependence of various cluster properties. The observations were acquired using the 8k mosaic camera on the 0.9-m KPNO telescope. This dataset was supplemented by 43 clusters from the survey of Lopez-Cruz (1997), and an additional two clusters from Brown (1997). Thus, a total sample of 71 clusters covering a redshift range from ~0.01 to 0.20 was available for analysis. The dynamical radius of each cluster (r200) was estimated from the photometric measurement of cluster richness (Bgc). The cluster galaxy color-magnitude relation (CMR) was used as a tool to minimize the inclusion of contaminating background galaxies by selecting galaxies relative to this relation. The luminosity function (LF) of individual and composite galaxy samples were constructed via the statistical subtraction of background galaxies. A robust method of comparing LFs for a variety of galaxy samples over a range of cluster-centric radius was presented. The general shape of the LFs were found to correlate with radius in the sense that the faint-end slope was generally steeper in the cluster outskirts. Color selection of galaxies into a red sequence and blue population indicates that the blue galaxies become fainter toward the cluster central region. This result supports the scenario that infalling field galaxies have their star formation truncated by some dynamical process. The construction of a non-parametric dwarf-to-giant ratio (DGR) and the blue-to-red galaxy ratio (BRR), allowed the investigation of the change in these parameters with various cluster properties to be conducted. The radial dependence of the DGR and BRR suggests that blue dwarf galaxies are tidally disrupted in the inner cluster environment or fade and turn red. The red, mainly nucleated, dwarf galaxies remain relatively unchanged with respect to cluster-centric radius, while giant blue galaxies have transformed into their red galaxy counterparts. These results provide support for the model proposed by Lopez-Cruz et al. (1997) to explain the formation of cD and Brightest Cluster Galaxy halos in which dwarf galaxies get tidally disrupted in the inner cluster region.
A new method is presented for producing images from incompletely sampled interferometric data. The method, "smear fitting", models the source with a set of basis functions and then convolves each component with an elliptical Gaussian to account for the uncertainty in its shape and location. This produces much sharper resolution for high signal to noise components than CLEAN without harm to low signal to noise features. It also lends itself to using data from multiple polarizations and/or frequencies to obtain an optimum set of images. Physical insight can also be incorporated by changing the choice of basis function(s).
Smear fitting does not require reweighting or even gridding of the data in the production and display of the model, preserving all of the information in the data both in terms of sensitivity and resolution. It is compared to other methods of producing images in radio interferometry. The comparisons are amply illustrated with both real and simulated data. Smear fitting is found to have sharper resolution than CLEAN, without striping or gridding errors. Although it is similar in principle to maximum entropy deconvolution, by using fewer degrees of freedom it avoids "ringing" artefacts around sharp features embedded in smooth emission. Its processing time is competitive with the other methods and best for objects that require many pixels but can be modeled with relatively few components, such as a set of sharp features superimposed on a smoothly varying background.
Two problems of fitting Gaussians to interferometric data are discussed and solved. These improvements in model fitting made it possible to automate smear fitting, and the details of the process are explained. Smear fitting is applied to study the precession of extragalactic radio jets and measure the thickness of the planetary nebula Vy 2-2, and results from those studies are given.
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