Halo detection via largescale Bayesian inference
Abstract
We present a proofofconcept of a novel and fully Bayesian methodology designed to detect haloes of different masses in cosmological observations subject to noise and systematic uncertainties. Our methodology combines the previously published Bayesian largescale structure inference algorithm, HAmiltonian Density Estimation and Sampling algorithm (HADES), and a Bayesian chain rule (the BlackwellRao estimator), which we use to connect the inferred density field to the properties of dark matter haloes. To demonstrate the capability of our approach, we construct a realistic galaxy mock catalogue emulating the widearea 6degree Field Galaxy Survey, which has a median redshift of approximately 0.05. Application of HADES to the catalogue provides us with accurately inferred threedimensional 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 detection of haloes 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 largescale structure in observations.
 Publication:

Monthly Notices of the Royal Astronomical Society
 Pub Date:
 August 2016
 DOI:
 10.1093/mnras/stw948
 arXiv:
 arXiv:1505.03528
 Bibcode:
 2016MNRAS.460.1340M
 Keywords:

 methods: numerical;
 methods: statistical;
 galaxies: haloes;
 galaxies: clusters: general;
 dark matter;
 largescale structure of Universe;
 Astrophysics  Cosmology and Nongalactic Astrophysics;
 Astrophysics  Instrumentation and Methods for Astrophysics
 EPrint:
 17 pages, 13 figures. Accepted for publication in MNRAS following moderate corrections