The evolution of the star forming sequence in hierarchical galaxy formation models

It has been argued that the specific star formation rates of star forming galaxies inferred from observational data decline more rapidly below z = 2 than is predicted by hierarchical galaxy formation models. We present a detailed analysis of this problem by comparing predictions from the GALFORM semi-analytic model with an extensive compilation of data on the average star formation rates of star-forming galaxies. We also use this data to infer the form of the stellar mass assembly histories of star forming galaxies. Our analysis reveals that the currently available data favour a scenario where the stellar mass assembly histories of star forming galaxies rise at early times and then fall towards the present day. In contrast, our model predicts stellar mass assembly histories that are almost flat below z = 2 for star forming galaxies, such that the predicted star formation rates can be offset with respect to the observational data by factors of up to 2-3. This disagreement can be explained by the level of coevolution between stellar and halo mass assembly that exists in contemporary galaxy formation models. In turn, this arises because the standard implementations of star formation and supernova feedback used in the models result in the efficiencies of these process remaining approximately constant over the lifetime of a given star forming galaxy. We demonstrate how a modification to the timescale for gas ejected by feedback to be reincorporated into galaxy haloes can help to reconcile the model predictions with the data.Comment: 30 Pages, 16 Figures, MNRAS accepte

Extending the halo mass resolution of NN-body simulations

We present a scheme to extend the halo mass resolution of N-body simulations of the hierarchical clustering of dark matter. The method uses the density field of the simulation to predict the number of sub-resolution dark matter haloes expected in different regions. The technique requires as input the abundance of haloes of a given mass and their average clustering, as expressed through the linear and higher order bias factors. These quantities can be computed analytically or, more accurately, derived from a higher resolution simulation as done here. Our method can recover the abundance and clustering in real- and redshift-space of haloes with mass below $\sim 7.5 \times 10^{13}h^{-1}M_{\odot}$ at $z=0$ to better than 10%. We demonstrate the technique by applying it to an ensemble of 50 low resolution, large-volume $N$-body simulations to compute the correlation function and covariance matrix of luminous red galaxies (LRGs). The limited resolution of the original simulations results in them resolving just two thirds of the LRG population. We extend the resolution of the simulations by a factor of 30 in halo mass in order to recover all LRGs. With existing simulations it is possible to generate a halo catalogue equivalent to that which would be obtained from a $N$-body simulation using more than 20 trillion particles; a direct simulation of this size is likely to remain unachievable for many years. Using our method it is now feasible to build the large numbers of high-resolution large volume mock galaxy catalogues required to compute the covariance matrices necessary to analyse upcoming galaxy surveys designed to probe dark energy.Comment: 11 pages, 7 Figure

Blending bias impacts the host halo masses derived from a cross-correlation analysis of bright sub-millimetre galaxies

Placing bright sub-millimetre galaxies (SMGs) within the broader context of galaxy formation and evolution requires accurate measurements of their clustering, which can constrain the masses of their host dark matter halos. Recent work has shown that the clustering measurements of these galaxies may be affected by a `blending bias,' which results in the angular correlation function of the sources extracted from single-dish imaging surveys being boosted relative to that of the underlying galaxies. This is due to confusion introduced by the coarse angular resolution of the single-dish telescope and could lead to the inferred halo masses being significantly overestimated. We investigate the extent to which this bias affects the measurement of the correlation function of SMGs when it is derived via a cross-correlation with a more abundant galaxy population. We find that the blending bias is essentially the same as in the auto-correlation case and conclude that the best way to reduce its effects is to calculate the angular correlation function using SMGs in narrow redshift bins. Blending bias causes the inferred host halo masses of the SMGs to be overestimated by a factor of $\sim6$ when a redshift interval of $\delta z=3$ is used. However, this reduces to a factor of $\sim2$ for $\delta z=0.5$. The broadening of photometric redshift probability distributions with increasing redshift can therefore impart a mild halo `downsizing' effect onto the inferred host halo masses, though this trend is not as strong as seen in recent observational studies.Comment: 10 pages, 9 figures, 1 table. Accepted to MNRA

Subhalo abundance matching in f(R) gravity

Using the liminality N-body simulations of Shi et al., we present the first predictions for galaxy clustering in f(R) gravity using subhalo abundance matching. We find that, for a given galaxy density, even for an f(R) model with fR0=−10−6, for which the cold dark matter clustering is very similar to the cold dark matter model with a cosmological constant (ΛCDM), the predicted clustering of galaxies in the f(R) model is very different from ΛCDM. The deviation can be as large as 40% for samples with mean densities close to that of L∗ galaxies. This large deviation is testable given the accuracy that future large-scale galaxy surveys aim to achieve. Our result demonstrates that galaxy surveys can provide a stringent test of general relativity on cosmological scales, which is comparable to the tests from local astrophysical observations