Exploiting the full potential of photometric quasar surveys: Optimal power spectra through blind mitigation of systematics

We present optimal measurements of the angular power spectrum of the XDQSOz catalogue of photometric quasars from the Sloan Digital Sky Survey. These measurements rely on a quadratic maximum likelihood estimator that simultaneously measures the auto- and cross-power spectra of four redshift samples, and provides minimum-variance, unbiased estimates even at the largest angular scales. Since photometric quasars are known to be strongly affected by systematics such as spatially-varying depth and stellar contamination, we introduce a new framework of extended mode projection to robustly mitigate the impact of systematics on the power spectrum measurements. This technique involves constructing template maps of potential systematics, decorrelating them on the sky, and projecting out modes which are significantly correlated with the data. Our method is able to simultaneously process several thousands of nonlinearly-correlated systematics, and mode projection is performed in a blind fashion. Using our final power spectrum measurements, we find a good agreement with theoretical predictions, and no evidence for further contamination by systematics. Extended mode projection not only obviates the need for aggressive sky and quality cuts, but also provides control over the level of systematics in the measurements, enabling the search for small signals of new physics while avoiding confirmation bias.Comment: 13 pages, 8 figures. v2: version accepted by MNRAS. v3: systematics templates publicly available on www.earlyuniverse.org/code, no change to pape

No new cosmological concordance with massive sterile neutrinos

It has been claimed recently that massive sterile neutrinos could bring about a new concordance between observations of the cosmic microwave background (CMB), the large-scale structure (LSS) of the Universe, and local measurements of the Hubble constant, $H_0$. We demonstrate that this apparent concordance results from combining datasets which are in significant tension, even within this extended model, possibly indicating remaining systematic biases in the measurements. We further show that this tension remains when the cosmological model is further extended to include significant tensor modes, as suggested by the recent BICEP2 results. Using the Bayesian evidence, we show that the minimal $\Lambda$CDM model is strongly favoured over its neutrino extensions by various combinations of datasets. Robust data combinations yield stringent limits of $\sum m_\nu\lesssim0.3$ eV and $m_{\nu,{\rm sterile}}^{\rm eff} \lesssim 0.3$ eV at $95\%$ CL for the sum of active and sterile neutrinos, respectively.Comment: 6 pages, version accepted by PR

Hierarchical Bayesian inference of galaxy redshift distributions from photometric surveys

Accurately characterizing the redshift distributions of galaxies is essential for analysing deep photometric surveys and testing cosmological models. We present a technique to simultaneously infer redshift distributions and individual redshifts from photometric galaxy catalogues. Our model constructs a piecewise constant representation (effectively a histogram) of the distribution of galaxy types and redshifts, the parameters of which are efficiently inferred from noisy photometric flux measurements. This approach can be seen as a generalization of template-fitting photometric redshift methods and relies on a library of spectral templates to relate the photometric fluxes of individual galaxies to their redshifts. We illustrate this technique on simulated galaxy survey data, and demonstrate that it delivers correct posterior distributions on the underlying type and redshift distributions, as well as on the individual types and redshifts of galaxies. We show that even with uninformative priors, large photometric errors and parameter degeneracies, the redshift and type distributions can be recovered robustly thanks to the hierarchical nature of the model, which is not possible with common photometric redshift estimation techniques. As a result, redshift uncertainties can be fully propagated in cosmological analyses for the first time, fulfilling an essential requirement for the current and future generations of surveys.Comment: 10 pages, matches version accepted in MNRAS, including new appendix describing the effect of Bayesian shrinkage in a simplified settin

Spurious correlations between galaxies and multi-epoch image stacks in the DESI Legacy Surveys

A non-negligible source of systematic bias in cosmological analyses of galaxy surveys is the on-sky modulation caused by foregrounds and variable image characteristics such as observing conditions. Standard mitigation techniques perform a regression between the observed galaxy density field and sky maps of the potential contaminants. Such maps are ad-hoc, lossy summaries of the heterogeneous sets of co-added exposures that contribute to the survey. We present a methodology to address this limitation, and extract the spurious correlations between the observed distribution of galaxies and arbitrary stacks of single-epoch exposures. We study four types of galaxies (LRGs, ELGs, QSOs, LBGs) in the three regions of the DESI Legacy Surveys (North, South, DES), which results in twelve samples with varying levels and type of contamination. We find that the new technique outperforms the traditional ones in all cases, and is able to remove higher levels of contamination. This paves the way for new methods that extract more information from multi-epoch galaxy survey data and mitigate large-scale biases more effectively.Comment: 18 pages, 8 figures. To be submitted to APJ