Although there has been much progress in understanding how galaxies evolve, we still do not understand how and when they stop forming stars and become quiescent. We address this by applying our galaxy spectral energy distribution models, which incorporate physically motivated star formation histories (SFHs) from cosmological simulations, to a sample of quiescent galaxies at 0.2 < z < 2.1. A total of 845 quiescent galaxies with multi-band photometry spanning rest-frame ultraviolet through near-infrared wavelengths are selected from the Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey (CANDELS) data set. We compute median SFHs of these galaxies in bins of stellar mass and redshift. At all redshifts and stellar masses, the median SFHs rise, reach a peak, and then decline to reach quiescence. At high redshift, we find that the rise and decline are fast, as expected, because the universe is young. At low redshift, the duration of these phases depends strongly on stellar mass. Low-mass galaxies (log(M*/M-circle dot) similar to 9.5) grow on average slowly, take a long time to reach their peak of star formation (greater than or similar to 4 Gyr), and then the declining phase is fast (less than or similar to 2 Gyr). Conversely, high-mass galaxies (log(M*/M-circle dot) similar to 11) grow on average fast (less than or similar to 2 Gyr), and, after reaching their peak, decrease the star formation slowly (greater than or similar to 3). These findings are consistent with galaxy stellar mass being a driving factor in determining how evolved galaxies are, with high-mass galaxies being the most evolved at any time (i.e., downsizing). The different durations we observe in the declining phases also suggest that low- and high-mass galaxies experience different quenching mechanisms, which operate on different timescales.

We use the shear catalogue from the CFHT Stripe-82 Survey to measure the subhalo masses of satellite galaxies in redMaPPer clusters. Assuming a Chabrier initial mass function and a truncated NFW model for the subhalo mass distribution, we find that the subhalo mass to galaxy stellar mass ratio increases as a function of projected halo-centric radius r(p), from M-sub/M-star = 4.43(-2.23)(+6.63) at r(p) is an element of [0.1, 0.3] h(-1) Mpc toM(sub)/M-star = 75.40(-19.09)(+19.73) at r(p) is an element of [0.6, 0.9] h(-1) Mpc. We also investigate the dependence of subhalo masses on stellar mass by splitting satellite galaxies into two stellar mass bins: 10 < log (M-star/h(-1) M-circle dot) < 10.5 and 11 < log (M-star/h(-1) M-circle dot) < 12. The best-fitting subhalomass of the more massive satellite galaxy bin is larger than that of the lessmassive satellites: log(M-sub/h(-1) M-circle dot) = 11.14(-0.73)(+0.66) (M-sub/M-star = 19.5(-17.9)(+19.8)) versus log(M-sub/h(-1) M-circle dot) = 12.38(-0.16)(+0.16) (M-sub/M-star = 21.1(-7.7)(+7.4)).

Spatially varying depth and the characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, particularly in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES-SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementary nature of these two approaches by comparing the SV data with BCC-UFig, a synthetic sky catalog generated by forward-modeling of the DES-SV images. We analyze the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and are well-captured by the maps of observing conditions. The combined use of the maps, the SV data, and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak-lensing analyses. However, they will need to be carefully characterized in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented here is relevant to all multi-epoch surveys and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.

Cosmological constraints from galaxy clusters rely on accurate measurements of the mass and internal structure of clusters. An important source of systematic uncertainty in cluster mass and structure measurements is the secure selection of background galaxies that are gravitationally lensed by clusters. This issue has been shown to be particular severe for faint blue galaxies. We therefore explore the selection of faint blue background galaxies, by reference to photometric redshift catalogues derived from the Cosmological Evolution Survey (COSMOS) and our own observations of massive galaxy clusters at z similar or equal to 0.2. We show that methods relying on photometric redshifts of galaxies in/behind clusters based on observations through five filters, and on deep 30-band COSMOS photometric redshifts are both inadequate to identify safely faint blue background galaxies with the same 1 per cent contamination level that we have achieved with red galaxies. This is due to the small number of filters used by the former, and absence of massive galaxy clusters at redshifts of interest in the latter. Nevertheless, our least contaminated blue galaxy sample yields stacked weak-lensing results consistent with our previously published results based on red galaxies, and we show that the stacked clustercentric number density profile of these faint blue galaxies is consistent with expectations from consideration of the lens magnification signal of the clusters. Indeed, the observed number density of blue background galaxies changes by similar to 10-30 per cent across the radial range over which other surveys assume it to be flat.

Abstract In this thesis we shed light on the formation and evolution of disk galaxies, which often host a stellar bar (about 2/3 of cases). In particular, we address the bar-driven secular evolution, that is, the steady redistribution of stellar and gaseous material through the disk induced by the bar torques and resonances. We characterize the mass distribution of the disks in the Spitzer Survey of Stellar Structure in Galaxies (S4G, Sheth et al. 2010) and study the properties of the different stellar structure components and the interplay between them. We use 3.6µm photometry for ~ 1300 face-on and moderately inclined disk galaxies to analyze the frequency, dimensions, orientations and shapes of stellar bars, spiral arms, rings, (ring)lenses, and barlenses (i.e. lens-like structures embedded in the bars). We calculate the strength of the bars in the S4G via ellipse fitting, Fourier decomposition of the galaxy images, and from the gravitational tangential-to-radial forces. We also estimate the stellar contribution to the circular velocity, allowing us to analyze the coupling between non-baryonic and stellar matter within the optical disk. We average stellar density profiles (1D), the disk(+bulge) component of the rotation curve, and stellar bars (2D) as a function of fundamental galaxy parameters. We complement the study with integral-field unit kinematic data from Seidel et al. (2015b) for a subsample of 16 S4G barred galaxies. We quantify the bar-induced perturbation strengths in the stellar and gaseous disk from the kinematics, and show that they agree with the estimates obtained from the images. We also use Hα Fabry-Perot observations from Erroz-Ferrer et al. (2015) for 29 S4G disk galaxies to study the inner slope of the rotation curves. We provide possible observational evidence for the growth of bars in a Hubble time. We demonstrate the role of bars causing the spreading of the disk and the enhancement of the central stellar concentration. Our observations support the idea that Boxy/Peanut bulges in face-on perspective manifest as barlenses, that are often identfied in early-type galaxies hosting strong bars, and some of them also as inner lenses. We find that the amount of dark matter within the optical disk scales with the total stellar mass, as expected in the ΛCDM models. We also confirm that the observed inner velocity gradient is correlated with the central surface brightness, showing a strong connection between the inner shape of the potential well and the central stellar density. We show that disks and bars in early-type (T &lt; 5 ≡ Sc) and late-type (T ≥ 5) disk galaxies, or alternatively in galaxies having total stellar masses greater or smaller than 1010M☉, are characterized by very distinct properties. Late-type disks are less centrally concentrated (many galaxies are bulge-less) and present a larger halo-to-stellar mass ratio, what probably affects the disk stability properties. The detection of bars in late-type galaxies is strongly dependent on the identification criteria. On average, bars in early-type spirals (T = 0 − 2) are longer (both in physical units and relative to the disk) and have larger density amplitudes than the intermediate-type spirals (T ≈ 5), and the bar lengths among the latest-types in the S4G are also larger. In comparison to earlier types, the bars in late-type systems show larger tangential-to-radial force ratios. This result holds even when the estimated dark halo effect is included.

Theories of how galaxies form and evolve depend greatly on constraints provided by observations. However, when those observations come from different datasets, systematic offsets may occur. This causes difficulties measuring variations in parameters between filters. In this thesis I present the variation in total luminosity density with wavelength in the nearby Universe (z<0.1), produced from a consistent reanalysis of NIR and optical observations, taken from the MGC, UKIDSS and SDSS surveys. I derive luminosity distributions, best-fitting Schechter function parameterisations and total luminosity densities in ugrizYJHK, and compare the variation in luminosity density with cosmic star formation history (CSFH) and initial mass function (IMF) models. I examine the r band luminosity distribution produced using different aperture definitions, the joint luminosity- surface brightness (bivariate brightness) distribution in ugrizYJHK, comparing them to previously derived distributions, and how the total luminosity density varies with wavelength when surface brightness incompleteness is accounted for. I find the following results. (1) The total luminosity density calculated using a non-Sersic (e.g. Kron or Petrosian) aperture is underestimated by at least 15%, (2) Changing the detection threshold has a minor effect on the best-fitting Schecter parameters, but the choice of Kron or Petrosian apertures causes an offset between datasets, regardless of the filter used to define the source list, (3) The decision to use circular or elliptical apertures causes an offset in M* of 0.20 mag, and best-fitting Schechter parameters from total magnitude photometric systems have a flatter faint-end slope than Kron or Petrosian photometry, (4) There is no surface brightness distribution evolution with luminosity for luminous galaxies, but at fainter magnitudes the distribution broadens and the peak surface brightness dims. A Choloniewski function that is modified to account for this surface brightness evolution fits the bivariate-brightness distribution better than an unmodified Choloniewski function, (5) The energy density per unit interval, vf(v) derived using MGC and GAMA samples agrees within 90% confidence intervals, but does not agree with predictions using standard CSFH and IMF models. Possible improvements to the data and alterations to the theory are suggested.