Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

We analyse the relationships between galaxy morphology, colour, environment and stellar mass using data for over 100,000 objects from Galaxy Zoo, the largest sample of visually classified morphologies yet compiled. We conclusively show that colour and morphology fractions are very different functions of environment. Both are sensitive to stellar mass; however, at fixed stellar mass, while colour is also highly sensitive to environment, morphology displays much weaker environmental trends. Only a small part of both relations can be attributed to variation in the stellar mass function with environment. Galaxies with high stellar masses are mostly red, in all environments and irrespective of their morphology. Low stellar-mass galaxies are mostly blue in low-density environments, but mostly red in high-density environments, again irrespective of their morphology. The colour-density relation is primarily driven by variations in colour fractions at fixed morphology, in particular the fraction of spiral galaxies that have red colours, and especially at low stellar masses. We demonstrate that our red spirals primarily include galaxies with true spiral morphology. We clearly show there is an environmental dependence for colour beyond that for morphology. Before using the Galaxy Zoo morphologies to produce the above results, we first quantify a luminosity-, size- and redshift-dependent classification bias that affects this dataset, and probably most other studies of galaxy population morphology. A correction for this bias is derived and applied to produce a sample of galaxies with reliable morphological type likelihoods, on which we base our analysis.

Abstract:

It is well known that observations of the cosmic microwave background (CMB) are highly sensitive to the spatial curvature of the Universe, k. Here we find that what is in fact being tightly constrained by small angle fluctuations is spatial curvature near the surface of last scattering, and that if we allow k to be a function of position, rather than taking a constant value everywhere, then considerable spatial curvature is permissible within our own locale. This result is of interest for the giant void models that attempt to explain the supernovae observations without Dark Energy. We find voids models with a homogeneous big bang can be compatible with the observed small angle CMB, but only if they exist in a positively curved universe. To be compatible with local measurements of H_0, however, we find that a radially varying bang time is required.

Abstract:

Although a fair amount of work has been devoted to growing Monte-Carlo merger trees which resemble those built from an N-body simulation, comparatively little effort has been invested in quantifying the caveats one necessarily encounters when one extracts trees directly from such a simulation. To somewhat revert the tide, this paper seeks to provide its reader with a comprehensive study of the problems one faces when following this route. The first step to building merger histories of dark matter haloes and their subhaloes is to identify these structures in each of the time outputs (snapshots) produced by the simulation. Even though we discuss a particular implementation of such an algorithm (called AdaptaHOP) in this paper, we believe that our results do not depend on the exact details of the implementation but extend to most if not all (sub)structure finders. We then highlight different ways to build merger histories from AdaptaHOP haloes and subhaloes, contrasting their various advantages and drawbacks. We find that the best approach to (sub)halo merging histories is through an analysis that goes back and forth between identification and tree building rather than one which conducts a straightforward sequential treatment of these two steps. This is rooted in the complexity of the merging trees which have to depict an inherently dynamical process from the partial temporal information contained in the collection of instantaneous snapshots available from the N-body simulation.