Photo-z Uncertainty Research Articles

PROBABILITY FRIENDS-OF-FRIENDS (PFOF) GROUP FINDER: PERFORMANCE STUDY AND OBSERVATIONAL DATA APPLICATIONS ON PHOTOMETRIC SURVEYS

(Abridged) In tandem with observational datasets, we utilize realistic mock catalogs, based on a semi-analytic galaxy formation model, constructed specifically for Pan-STARRS1 Medium Deep Surveys in order to assess the performance of the Probability Friends-of-Friends (PFOF, Liu et al.) group finder, and aim to develop a grouping optimization method applicable to surveys like Pan-STARRS1. Producing mock PFOF group catalogs under a variety of photometric redshift accuracies ({\sigma}{\Delta}z/(1+zs)), we find that catalog purities and completenesses from ``good' {\sigma}{\Delta}z/(1+zs)) ~ 0.01) to ``poor' {\sigma}{\Delta}z/(1+zs)) ~ 0.07) photo-zs gradually degrade respectively from 77% and 70% to 52% and 47%. To avoid model dependency of the mock for use on observational data we apply a ``subset optimization' approach, using spectroscopic-redshift group data from the target field to train the group finder for application to that field, as an alternative method for the grouping optimization. We demonstrate this approach using these spectroscopically identified groups as the training set, i.e. zCOSMOS groups for PFOF searches within PS1 Medium Deep Field04 (PS1MD04) and DEEP2 EGS groups for searches in PS1MD07. We ultimately apply PFOF to four datasets spanning the photo-z uncertainty range from 0.01 to 0.06 in order to quantify the dependence of group recovery performance on photo-z accuracy. We find purities and completenesses calculated from observational datasets broadly agree with their mock analogues. Further tests of the PFOF algorithm are performed via matches to X-ray clusters identified within the PS1MD04 and COSMOS footprints. Across over a decade in group mass, we find PFOF groups match ~85% of X-ray clusters in COSMOS and PS1MD04, but at a lower statistical significance in the latter.

General requirements on matter power spectrum predictions for cosmology with weak lensing tomography

Forthcoming projects such as DES, LSST, WFIRST, and Euclid aim to measure weak lensing shear correlations with unprecedented precision, constraining the dark energy equation of state at the percent level. Reliance on photometrically-determined redshifts constitutes a major source of uncertainty for these surveys. Additionally, interpreting the weak lensing signal requires a detailed understanding of the nonlinear physics of gravitational collapse. We present a new analysis of the stringent calibration requirements for weak lensing analyses of future imaging surveys that addresses both photo-z uncertainty and errors in the calibration of the matter power spectrum. We find that when photo-z uncertainty is taken into account the requirements on the level of precision in the prediction for the matter power spectrum are more stringent than previously thought. Including degree-scale galaxy clustering statistics in a joint analysis with weak lensing not only strengthens the survey's constraining power by ∼ 20%, but can also have a profound impact on the calibration demands, decreasing the degradation in dark energy constraints with matter power spectrum uncertainty by a factor of 2-5. Similarly, using galaxy clustering information significantly relaxes the demands on photo-z calibration. We compare these calibration requirements to the contemporary state-of-the-art in photometric redshift estimation and predictions of the power spectrum and suggest strategies to utilize forthcoming data optimally.

Modelling the angular correlation function and its full covariance in photometric galaxy surveys

Near future cosmology will see the advent of wide area photometric galaxy surveys, like the Dark Energy Survey (DES), that extent to high redshifts (z ~ 1 - 2) but with poor radial distance resolution. In such cases splitting the data into redshift bins and using the angular correlation function $w(\theta)$, or the $C_{\ell}$ power spectrum, will become the standard approach to extract cosmological information or to study the nature of dark energy through the Baryon Acoustic Oscillations (BAO) probe. In this work we present a detailed model for $w(\theta)$ at large scales as a function of redshift and bin width, including all relevant effects, namely nonlinear gravitational clustering, bias, redshift space distortions and photo-z uncertainties. We also present a model for the full covariance matrix characterizing the angular correlation measurements, that takes into account the same effects as for $w(\theta)$ and also the possibility of a shot-noise component and partial sky coverage. Provided with a large volume N-body simulation from the MICE collaboration we built several ensembles of mock redshift bins with a sky coverage and depth typical of forthcoming photometric surveys. The model for the angular correlation and the one for the covariance matrix agree remarkably well with the mock measurements in all configurations. The prospects for a full shape analysis of $w(\theta)$ at BAO scales in forthcoming photometric surveys such as DES are thus very encouraging.

Tracing the sound horizon scale with photometric redshift surveys

We propose a new method for cosmological parameters extraction using the baryon acoustic oscillation scale as a standard ruler in deep galaxy surveys with photometric determination of redshifts. The method consists in a simple empirical parametric fit to the angular 2-point correlation function w(theta). It is parametrized as a power law to describe the continuum plus a Gaussian to describe the BAO bump. The location of the Gaussian is used as the basis for the measurement of the sound horizon scale. This method, although simple, actually provides a robust estimation, since the inclusion of the power law and the use of the Gaussian removes the shifts which affect the local maximum. We discuss the effects of projection bias, non-linearities, redshift space distortions and photo-z precision, and apply our method to a mock catalog of the Dark Energy Survey, built upon a large N-body simulation provided by the MICE collaboration. We discuss the main systematic errors associated to our method and show that they are dominated by the photo-z uncertainty.