Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

The analysis of photometric large-scale structure data is often complicated by the need to account for many observational and astrophysical systematics. The elaborate models needed to describe them often introduce many "nuisance parameters’', which can be a major inhibitor of an efficient parameter inference. In this paper we introduce an approximate method to analytically marginalise over a large number of nuisance parameters based on the Laplace approximation. We discuss the mathematics of the method, its relation to concepts such as volume effects and profile likelihood, and show that it can be further simplified for calibratable systematics by linearising the dependence of the theory on the associated parameters. We quantify the accuracy of this approach by comparing it with traditional sampling methods in the context of existing data from the Dark Energy Survey, as well as futuristic Stage-IV photometric data. The linearised version of the method is able to obtain parameter constraints that are virtually equivalent to those found by exploring the full parameter space for a large number of calibratable nuisance parameters, while reducing the computation time by a factor 3-10. Furthermore, the non-linearised approach is able to analytically marginalise over a large number of parameters, returning constraints that are virtually indistinguishable from the brute-force method in most cases, accurately reproducing both the marginalised uncertainty on cosmological parameters, and the impact of volume effects associated with this marginalisation. We provide simple recipes to diagnose when the approximations made by the method fail and one should thus resort to traditional methods. The gains in sampling efficiency associated with this method enable the joint analysis of multiple surveys, typically hindered by the large number of nuisance parameters needed to describe them.

Abstract:

We have conducted a search for z ≃ 7 Lyman-break galaxies over 8.2 deg² of near-infrared imaging from the Visible and Infrared Survey Telescope for Astronomy (VISTA) Deep Extragalactic Observations (VIDEO) survey in the XMM–Newton-Large Scale Structure (XMM-LSS) and the Extended Chandra Deep Field-South (ECDF-S) fields. Candidate galaxies were selected from a full photometric redshift analysis down to a Y + J depth of 25.3 (5σ), utilizing deep auxiliary optical and Spitzer/Infrared Array Camera (IRAC) data to remove brown dwarf and red interloper galaxy contaminants. Our final sample consists of 28 candidate galaxies at 6.5 ≤ z ≤ 7.5 with −23.5 ≤ M_UV ≤ −21.6. We derive stellar masses of 9.1 ≤ log₁₀(M_⋆/M_⊙) ≤ 10.9 for the sample, suggesting that these candidates represent some of the most massive galaxies known at this epoch. We measure the rest-frame ultraviolet (UV) luminosity function (LF) at z ≃ 7, confirming previous findings of a gradual decline in number density at the bright end (M_UV < −22) that is well described by a double power law (DPL). We show that quasar contamination in this magnitude range is expected to be minimal, in contrast to conclusions from recent pure-parallel Hubble studies. Our results are up to a factor of 10 lower than previous determinations from optical-only ground-based studies at M_UV ≲ −23. We find that the inclusion of YJHK_s photometry is vital for removing brown dwarf contaminants, and z ≃ 7 samples based on red optical data alone could be highly contaminated (≳50 per cent). In comparison with other robust z > 5 samples, our results further support little evolution in the very bright end of the rest-frame UV LF from z = 5–10, potentially signalling a lack of mass quenching and/or dust obscuration in the most massive galaxies in the first Gyr.