You are here:

Haojie Xu Thesis Defense 05/02/2018

Thesis Defense

Haojie Xu Wednesday, May 2, 2018 at 9 AM (110 INSCC)

Title: Galaxy Color-Luminosity-Halo Mass Relation From Galaxy Clustering

Understanding how galaxy forms and evolves is one of the most pressing questions in modern astronomy. In the contemporary galaxy formation and evolution theory, galaxy forms and evolves in dark matter halos.

However, the physics connecting the halo to the galaxy remains poorly understood. Since galaxy lives in halo, the galaxy-halo relation can be empirically built by linking the measured galaxy clustering in large redshift sky survey and the well predicted halo clustering. Galaxy clusters differently as a function of its properties, in particularly color and magnitude. Therefore, it enables to build the galaxy color, magnitude and halo mass relation, which in turn will provide the most crucial test on the galaxy formation and evolution theory.

Faint red galaxies in the Sloan Digital Sky Survey show a puzzling clustering pattern in previous measurements. In the two-point correlation function (2PCF), they appear to be strongly clustered on small-scales, indicating a tendency to reside in massive halos as satellite galaxies. However, their weak clustering on large scales suggests that they are more likely to be found in low mass halos. The interpretation of the clustering pattern suffers from the large sample variance in the 2PCF measurements, given the small volume of the volume-limited sample of such faint galaxies. I present improved clustering measurements of faint galaxies by making a full use of a flux-limited sample to obtain volume-limited measurements with an increased effective volume. In the improved 2PCF measurements, the fractional uncertainties on large-scales drop by more than 40 per cent, and the strong contrast between small-scale and large-scale clustering amplitudes seen in previous work is no longer prominent. From halo occupation distribution modeling of the measurements, I find that a considerable fraction of faint red galaxies to be satellites in massive halos, a scenario supported by the strong covariance of small-scale 2PCF measurements and the relative spatial distribution of faint red galaxies and luminous galaxies. However, the satellite fraction is found to be degenerate with the slope of the distribution profile of satellites in inner halos. I compare the modeling results with semi-analytic model predictions and discuss the implications.

In the second part, I formulate a model of the conditional color-magnitude distribution (CCMD) to describe the distribution of galaxy luminosity and color as a function of halo mass. It consists of two populations of different color distributions, dubbed pseudo-blue and pseudo-red, respectively, with each further separated into central and satellite galaxies. I define a global parameterization of these four color-magnitude distributions and their dependence on halo mass, and I infer parameter values by simultaneously fitting the space densities and auto-correlation functions of 79 galaxy samples from the Sloan Digital Sky Survey defined by fine bins in the color-magnitude diagram (CMD). The model deprojects the overall galaxy CMD, revealing its tomography along the halo mass direction. The bimodality of the color distribution is driven by central galaxies at most luminosities, though at low luminosities it is driven by the difference between blue centrals and red satellites. For central galaxies, the two pseudo-color components are distinct and orthogonal to each other in the CCMD: at fixed halo mass, pseudo-blue galaxies have a narrow luminosity range and broad color range, while pseudo-red galaxies have a narrow color range and broad luminosity range. For pseudo-blue centrals, luminosity correlates tightly with halo mass, while for pseudo-red galaxies color correlates more tightly (redder galaxies in more massive halos). The satellite fraction is higher for redder and for fainter galaxies, with color a stronger indicator than luminosity. I discuss the implications of the results and further applications of the CCMD model.

Last Updated: 12/21/18