Halo detection via large-scale Bayesian inference

We present a proof-of-concept of a novel and fully Bayesian methodology designed to detect halos of different masses in cosmological observations subject to noise and systematic uncertainties. Our methodology combines the previously published Bayesian large-scale structure inference algorithm, HADES, and a Bayesian chain rule (the Blackwell-Rao Estimator), which we use to connect the inferred density field to the properties of dark matter halos. To demonstrate the capability of our approach we construct a realistic galaxy mock catalogue emulating the wide-area 6-degree Field Galaxy Survey, which has a median redshift of approximately 0.05. Application of HADES to the catalogue provides us with accurately inferred three-dimensional density fields and corresponding quantification of uncertainties inherent to any cosmological observation. We then use a cosmological simulation to relate the amplitude of the density field to the probability of detecting a halo with mass above a specified threshold. With this information we can sum over the HADES density field realisations to construct maps of detection probabilities and demonstrate the validity of this approach within our mock scenario. We find that the probability of successful of detection of halos in the mock catalogue increases as a function of the signal-to-noise of the local galaxy observations. Our proposed methodology can easily be extended to account for more complex scientific questions and is a promising novel tool to analyse the cosmic large-scale structure in observations.

Lightcone mock catalogues from semi-analytic models of galaxy formation - I. Construction and application to the BzK colour selection

We introduce a method for constructing end-to-end mock galaxy catalogues using a semi-analytical model of galaxy formation, applied to the halo merger trees extracted from a cosmological N-body simulation. The mocks that we construct are lightcone catalogues, in which a galaxy is placed according to the epoch at which it first enters the past lightcone of the observer, and incorporate the evolution of galaxy properties with cosmic time. We determine the position between the snapshot outputs at which a galaxy enters the observers lightcone by interpolation. As an application, we consider the effectiveness of the BzK colour selection technique, which was designed to isolate galaxies in the redshift interval 1.4<z<2.5. The mock catalogue is in reasonable agreement with the observed number counts of all BzK galaxies, as well as with the observed counts of the subsample of BzKs that are star-forming galaxies. We predict that over 75 per cent of the model galaxies with K_{AB}<=23, and 1.4<z<2.5, are selected by the BzK technique. Interloper galaxies, outside the intended redshift range, are predicted to dominate bright samples of BzK galaxies (i.e. with K_{AB}<=21). Fainter K-band cuts are necessary to reduce the predicted interloper fraction. We also show that shallow B-band photometry can lead to confusion in classifying BzK galaxies as being star-forming or passively evolving. Overall, we conclude that the BzK colour selection technique is capable of providing a sample of galaxies that is representative of the 1.4<z<2.5 galaxy population.