Thesis (Ph.D. 1978) from the Department of Mathematical Physics, University of Adelaide.

Thesis (Ph. D.)--Ohio State University, 2005. / Title from first page of PDF file. Document formatted into pages; contains xviii, 319 p.; also includes graphics. Includes bibliographical references (p. 310-319). Available online via OhioLINK's ETD Center

In this thesis I construct various models to interpret measurements of the clustering of dusty star-forming galaxies through the angular power spectrum statistic. The goals of this work are, firstly, to facilitate the separation of the dusty galaxy contribution from the cosmic microwave background background (CMB) power spectrum, and, secondly, to improve our understanding of the physical properties of these galaxies. I present analysis of the first cross-correlation of millimeter and submillimeter sky maps, using data from the Atacama Cosmology Telescope (ACT) and the Balloon-borne Large-Aperture Submillimeter Telescope (BLAST), which revealed that the dusty galaxies that dominate the submillimeter sky are, to a significant extent, those same sources that are a nuisance contaminant for CMB cosmology. I then perform a joint fit to the ACT and BLAST power spectra as well as early results from the Planck Surveyor to construct a simple phenomenological template for the frequency and angular scale dependence of the contribution from clustered dusty galaxies to the total power spectrum. This template may be used to assist in extracting the CMB signal from future ACT and other data sets. The correlation between dusty galaxies and the thermal Sunyaev Zel'dovich effect leads to an additional contribution to the measured angular power spectrum that further hampers constraining quantities of cosmological interest. I present the first physically-motivated model for this correlation, and make predictions for its frequency and scale dependence as a CMB foreground. Finally, I combine angular power spectrum measurements from ACT, Planck and other instruments with deep far-infrared and submillimeter source number counts and constrain a model for the emission properties of these dusty galaxies. I demonstrate that the power spectrum carries significant constraining power and can improve our understanding of dust emission and star formation from unresolved objects at high redshift.

We quantify the structure and scale of the Universe using redshift surveys of galaxies and QSOs and observations of Galactic open star clusters. We obtain the galaxy power spectrum from the Durham/UKST Galaxy Redshift Survey. By comparing the shape of the observed power spectrum to the APM real space power spectrum, we quantify the size of the redshift space distortions and find β = Ω(^0.6)/b=0.60±0.35. We also apply counts-in-cells analysis to the Durham/UKST and Stromlo-APM Surveys and measure the skewness directly out to 20h(^-1)Mpc. We find that the skewness measured from CDM models can only be reconciled with that of galaxies if bias is non-linear. We make predictions for the clustering in the 2dF QSO Survey by constructing mock catalogues from the Hubble Volume N-body simulation, with geometry, selection function and clustering matching those expected in the completed Survey. We predict that the correlation function will be reliably measured out to ~ 1, 000h(^-1)Mpc and the power spectrum out to 500h(^-1)Mpc. We measure the power spectrum from the 2dF QSOs observed by January 2000 and find it has a shape of F ~ 0.1. We also find little evolution in the clustering amplitude as a function of redshift. We obtain constraints on the cosmo- logical parameters Ωn and β by combining results from modeling geometric distortions introduced into the clustering pattern due to inconsistent cosmological assumptions and results from the QSO-mass bias. Finally, we consider the scale of the Universe. We check the calibration of the Cepheid Period-Luminosity relation using U,B,V and K'band imaging of Galactic Open Clusters containing Cepheids and measure the distance modulus to the LMC to be 18.51 ±0.10. However, we find anomalous colour-colour diagrams for two clusters and suggest that the effects of metallicity may be greater than previously considered.

Thesis (Ph. D.)--University of Chicago, Department of Astronomy & Astrophysics, August 2002. / Includes bibliographical references. Also available on the Internet.

In this thesis, I investigate the spatial distribution of radio sources, and quantify their clustering strength over a range of redshifts, up to z _ 2:2, using various forms of the correlation function measured with data from several multi-wavelength surveys. I present the optical spectra of 30 radio AGN (S1:4 > 100 mJy) in the GAMA/H-ATLAS fields, for which emission line redshifts could be deduced, from observations of 79 target sources with the EFOSC2 spectrograph on the NTT. The mean redshift of these sources is z = 1:2; 12 were identified as quasars (40 per cent), and 6 redshifts (out of 24 targets) were found for AGN hosts to multiple radio components. While obtaining spectra for hosts of these multi-component sources is possible, their lower success rate highlights the difficulty in acheiving a redshift-complete radio sample. Taking an existing spectroscopic redshift survey (GAMA) and radio sources from the FIRST survey (S1:4 > 1 mJy), I then present a cross-matched radio sample with 1,635 spectroscopic redshifts with a median value of z = 0:34. The spatial correlation function of this sample is used to find the redshiftspace (s0) and real-space correlation lengths (r0 _ 8:2 h 1Mpc), and a mass bias of _1.9. Insight into the redshift-dependence of these quantities is gained by using the angular correlation function and Limber inversion to measure the same spatial clustering parameters. Photometric redshifts from SDSS/UKIDSS are incorporated to produce a larger matched radio sample at z ' 0:48 (and low- and high-redshift subsamples at z ' 0:30 and z ' 0:65), while their redshift distribution is subtracted from that taken from the SKADS radio simulations to estimate the redshift distribution of the remaining unmatched sources (z ' 1:55). The observed bias evolution over this redshift range is compared with model predictions based on the SKADS simulations, with good agreement at low redshift. The bias found at high redshift significantly exceeds these predictions, however, suggesting a more massive population of galaxies than expected, either due to the relative proportions of different radio sources, or a greater typical halo mass for the high-redshift sources. Finally, the reliance on a model redshift distribution to reach to higher redshifts is removed, as the angular cross-correlation function is used with deep VLA data (S1:4 > 90 _Jy) and optical/IR data from VIDEO/CFHTLS (Ks < 23:5) over 1 square degree. With high-quality photometric redshifts up to z _ 4, and a high signal-to-noise clustering measurement (due to the _100,000 Ks-selected galaxies), I am able to find the bias of a matched sample of only 766 radio sources (as well as of v vi the VIDEO sources), divided into 4 redshift bins reaching a median bias at z ' 2:15. Again, at high redshift, the measured bias appears to exceed the prediction made from the SKADS simulations. Applying luminosity cuts to the radio sample at L > 1023 WHz 1 and higher (removing any non-AGN sources), I find a bias of 8–10 at z _ 1:5, considerably higher than for the full sample, and consistent with the more numerous FRI AGN having similar mass to the FRIIs (M _ 1014 M_), contrary to the assumptions made in the SKADS simulations. Applying this adjustment to the model bias produces a better fit to the observations for the FIRST radio sources cross-matched with GAMA/SDSS/UKIDSS, as well as for the high-redshift radio sources in VIDEO. Therefore, I have shown that we require a more robust model of the evolution of AGN, and their relation to the underlying dark matter distribution. In particular, understanding these quantities for the abundant FRI population is crucial if we are to use such sources to probe the cosmological model as has been suggested by a number of authors (e.g. Raccanelli et al., 2012; Camera et al., 2012; Ferramacho et al., 2014).