Redshift Distribution Of Galaxies Research Articles

Simulation-based inference of deep fields: galaxy population model and redshift distributions

Accurate redshift calibration is required to obtain unbiased cosmological information from large-scale galaxy surveys. In a forward modelling approach, the redshift distribution n(z) of a galaxy sample is measured using a parametric galaxy population model constrained by observations. We use a model that captures the redshift evolution of the galaxy luminosity functions, colours, and morphology, for red and blue samples. We constrain this model via simulation-based inference, using factorized Approximate Bayesian Computation (ABC) at the image level. We apply this framework to HSC deep field images, complemented with photometric redshifts from COSMOS2020. The simulated telescope images include realistic observational and instrumental effects. By applying the same processing and selection to real data and simulations, we obtain a sample of n(z) distributions from the ABC posterior. The photometric properties of the simulated galaxies are in good agreement with those from the real data, including magnitude, colour and redshift joint distributions. We compare the posterior n(z) from our simulations to the COSMOS2020 redshift distributions obtained via template fitting photometric data spanning the wavelength range from UV to IR. We mitigate sample variance in COSMOS by applying a reweighting technique. We thus obtain a good agreement between the simulated and observed redshift distributions, with a difference in the mean at the 1σ level up to a magnitude of 24 in the i band. We discuss how our forward model can be applied to current and future surveys and be further extended. The ABC posterior and further material will be made publicly available at https://cosmology.ethz.ch/research/software-lab/ufig.html.

Investigating Gravitationally Lensed Quasars Observable by Nancy Grace Roman Space Telescope

In this work, we investigate the possibility of observing quasars, particularly lensed quasars, by the Nancy Grace Roman Space Telescope (Roman). To this aim, based on the capabilities of the Roman Space Telescope and the results from the quasar luminosity function (QLF) in the infrared band of the Spitzer Space Telescope imaging survey, we calculated the number of quasars expected to be in its field of view. In order to estimate the number of lensed quasars, we develop a Monte Carlo simulation to estimate the probability that a quasar is lensed once or more times by foreground galaxies. Using the mass–luminosity distribution function of galaxies and the redshift distributions of galaxies and quasars, we find that 1 per 180 observed quasars will be lensed by foreground galaxies. Further on, adopting a singular isothermal sphere (SIS) model for lens galaxies, we calculate the time delay between lensed images for single and multiple lensing systems and present their distributions. We emphasize that detailed studies of these lensing systems will provide a powerful probe of the physical properties of quasars and may allow testing the mass distribution models of galaxies in addition to being extremely helpful for constraining the cosmological parameters.

Forward Modeling of Galaxy Populations for Cosmological Redshift Distribution Inference

We present a forward-modeling framework for estimating galaxy redshift distributions from photometric surveys. Our forward model is composed of: a detailed population model describing the intrinsic distribution of the physical characteristics of galaxies, encoding galaxy evolution physics; a stellar population synthesis model connecting the physical properties of galaxies to their photometry; a data model characterizing the observation and calibration processes for a given survey; and explicit treatment of selection cuts, both into the main analysis sample and for the subsequent sorting into tomographic redshift bins. This approach has the appeal that it does not rely on spectroscopic calibration data, provides explicit control over modeling assumptions and builds a direct bridge between photo-z inference and galaxy evolution physics. In addition to redshift distributions, forward modeling provides a framework for drawing robust inferences about the statistical properties of the galaxy population more generally. We demonstrate the utility of forward modeling by estimating the redshift distributions for the Galaxy And Mass Assembly (GAMA) survey and the Vimos VLT Deep Survey (VVDS), validating against their spectroscopic redshifts. Our baseline model is able to predict tomographic redshift distributions for GAMA and VVDS with respective biases of Δz ≲ 0.003 and Δz ≃ 0.01 on the mean redshift—comfortably accurate enough for Stage III cosmological surveys—without any hyperparameter tuning (i.e., prior to doing any fitting to those data). We anticipate that with additional hyperparameter fitting and modeling improvements, forward modeling will provide a path to accurate redshift distribution inference for Stage IV surveys.

Constraining the galaxy-halo connection of infrared-selected unWISE galaxies with galaxy clustering and galaxy-CMB lensing power spectra

We present the first detailed analysis of the connection between galaxies and their dark matter halos for the unWISE galaxy catalog -- a full-sky, infrared-selected sample built from WISE data, containing over 500 million galaxies. Using unWISE galaxy-galaxy auto-correlation and Planck CMB lensing-galaxy cross-correlation measurements down to 10 arcmin angular scales, we constrain the halo occupation distribution (HOD), a model describing how central and satellite galaxies are distributed within dark matter halos, for three unWISE} galaxy samples at mean redshifts $\bar{z} \approx 0.6$, $1.1$, and $1.5$. We constrain the characteristic minimum halo mass to host a central galaxy, $M_\mathrm{min}^\mathrm{HOD} = 1.83^{+0.41}_{-1.63} \times 10^{12} M_\odot/h$, $5.22^{+0.34}_{-4.80} \times 10^{12} M_\odot/h$, $6.60 ^{+0.30}_{-1.11} \times 10^{13} M_\odot/h$ for the unWISE samples at $\bar{z}\approx 0.6$, $1.1$, and $1.5$, respectively. We find that all three samples are dominated by central galaxies, rather than satellites. Using our constrained HOD models, we infer the effective linear galaxy bias for each unWISE sample, and find that it does not evolve as steeply with redshift as found in previous perturbation-theory-based analyses of these galaxies. We discuss possible sources of systematic uncertainty in our results, the most significant of which is the uncertainty on the galaxy redshift distribution. Our HOD constraints provide a detailed, quantitative understanding of how the unWISE galaxies populate the underlying dark matter halo distribution. These constraints will have a direct impact on future studies employing the unWISE galaxies as a cosmological and astrophysical probe, including measurements of ionized gas thermodynamics and dark matter profiles via Sunyaev-Zel'dovich and lensing cross-correlations.

Mapping variations of redshift distributions with probability integral transforms

ABSTRACT We present a method for mapping variations between probability distribution functions and apply this method within the context of measuring galaxy redshift distributions from imaging survey data. This method, which we name PITPZ for the probability integral transformations it relies on, uses a difference in curves between distribution functions in an ensemble as a transformation to apply to another distribution function, thus transferring the variation in the ensemble to the latter distribution function. This procedure is broadly applicable to the problem of uncertainty propagation. In the context of redshift distributions, for example, the uncertainty contribution due to certain effects can be studied effectively only in simulations, thus necessitating a transfer of variation measured in simulations to the redshift distributions measured from data. We illustrate the use of PITPZ by using the method to propagate photometric calibration uncertainty to redshift distributions of the Dark Energy Survey Year 3 weak lensing source galaxies. For this test case, we find that PITPZ yields a lensing amplitude uncertainty estimate due to photometric calibration error within 1 per cent of the truth, compared to as much as a 30 per cent underestimate when using traditional methods.

Optical selection bias and projection effects in stacked galaxy cluster weak lensing

ABSTRACT Cosmological constraints from current and upcoming galaxy cluster surveys are limited by the accuracy of cluster mass calibration. In particular, optically identified galaxy clusters are prone to selection effects that can bias the weak lensing mass calibration. We investigate the selection bias of the stacked cluster lensing signal associated with optically selected clusters, using clusters identified by the redMaPPer algorithm in the Buzzard simulations as a case study. We find that at a given cluster halo mass, the residuals of redMaPPer richness and weak lensing signal are positively correlated. As a result, for a given richness selection, the stacked lensing signal is biased high compared with what we would expect from the underlying halo mass probability distribution. The cluster lensing selection bias can thus lead to overestimated mean cluster mass and biased cosmology results. We show that the lensing selection bias exhibits a strong scale dependence and is approximately 20–60 per cent for ΔΣ at large scales. This selection bias largely originates from spurious member galaxies within ±20–60 $h^{-1}\, \rm Mpc$ along the line of sight, highlighting the importance of quantifying projection effects associated with the broad redshift distribution of member galaxies in photometric cluster surveys. While our results qualitatively agree with those in the literature, accurate quantitative modelling of the selection bias is needed to achieve the goals of cluster lensing cosmology and will require synthetic catalogues covering a wide range of galaxy–halo connection models.

Photometric Redshifts for Next-Generation Surveys

Photometric redshifts are essential in studies of both galaxy evolution and cosmology, as they enable analyses of objects too numerous or faint for spectroscopy. The Rubin Observatory, Euclid, and Roman Space Telescope will soon provide a new generation of imaging surveys with unprecedented area coverage, wavelength range, and depth. To take full advantage of these data sets, further progress in photometric redshift methods is needed. In this review, we focus on the greatest common challenges and prospects for improvement in applications of photometric redshifts to the next generation of surveys: ▪ Gains in performance (i.e., the precision of redshift estimates for individual galaxies) could greatly enhance studies of galaxy evolution and some probes of cosmology. ▪ Improvements in characterization (i.e., the accurate recovery of redshift distributions of galaxies in the presence of uncertainty on individual redshifts) are urgently needed for cosmological measurements with next-generation surveys. To achieve both of these goals, improvements in the scope and treatment of the samples of spectroscopic redshifts that make high-fidelity photometric redshifts possible will also be needed. For the full potential of the next generation of surveys to be reached, the characterization of redshift distributions must improve by roughly an order of magnitude compared with the current state of the art, requiring progress on a wide variety of fronts. We conclude by presenting a speculative evaluation of how photometric redshift methods and the collection of the necessary spectroscopic samples may improve by the time near-future surveys are completed.

Interpreting the Statistical Properties of High-z Extragalactic Sources Detected by the South Pole Telescope Survey

The results of the recently published spectroscopically complete survey of dusty star-forming galaxies detected by the South Pole Telescope over 2500 deg2 proved to be challenging for galaxy formation models that generally underpredict the observed abundance of high-z galaxies. In this paper we interpret these results in the light of a physically grounded model for the evolution of spheroidal galaxies. The model accurately reproduces the measured redshift distribution of galaxies without any adjustment of the parameters. The data do not support the indications of an excess of z > 4 dusty galaxies reported by some analyses of Herschel surveys.

Multiband gravitational wave cosmology with stellar origin black hole binaries

Massive stellar origin black hole binaries (SBHBs), originating from stars above the pair-instability mass gap, are primary candidates for multiband gravitational wave (GW) observations. Here we study the possibility to use them as effective dark standard sirens to constrain cosmological parameters. The long lasting inspiral signal emitted by these systems is accessible by the future $Laser \; Interferometer \; Space \; Antenna$ (LISA), while the late inspiral and merger are eventually detected by third generation ground-based telescopes such as the $Einstein \; Telescope$ (ET). The direct measurement of the luminosity distance and the sky position to the source, together with the inhomogeneous redshift distribution of possible host galaxies, allow us to infer cosmological parameters by probabilistic means. The efficiency of this statistical method relies in high parameter estimation performances. We show that this multiband approach allows a precise determination of the Hubble constant H$_0$ with just ${\cal O}(10)$ detected sources. For selected SBHB population models, assuming $4$ ($10$) years of LISA observations, we find that H$_0$ is typically determined at $\sim 2\%$ ($\sim 1.5\%$), whereas $\Omega_m$ is only mildly constrained with a typical precision of $30\%$ ($20\%$). We discuss the origin of some outliers in our final estimates and we comment on ways to reduce their presence.

The impact of tomographic redshift bin width errors on cosmological probes

ABSTRACT Systematic errors in the galaxy redshift distribution n(z) can propagate to systematic errors in the derived cosmology. We characterize how the degenerate effects in tomographic bin widths and galaxy bias impart systematic errors on cosmology inference using observational data from the Deep Lens Survey. For this we use a combination of galaxy clustering and galaxy–galaxy lensing. We present two end-to-end analyses from the catalogue level to parameter estimation. We produce an initial cosmological inference using fiducial tomographic redshift bins derived from photometric redshifts, then compare this with a result where the redshift bins are empirically corrected using a set of spectroscopic redshifts. We find that the derived parameter S8 ≡ σ8(Ωm/.3)1/2 decreases from $0.841^{+0.062}_{-0.061}$ to $0.781^{0.061}_{0.054}$ upon correcting the n(z) errors in the second method.

Dark Energy Survey Year 3 Results: clustering redshifts – calibration of the weak lensing source redshift distributions with redMaGiC and BOSS/eBOSS

ABSTRACT We present the calibration of the Dark Energy Survey Year 3 (DES Y3) weak lensing (WL) source galaxy redshift distributions n(z) from clustering measurements. In particular, we cross-correlate the WL source galaxies sample with redMaGiC galaxies (luminous red galaxies with secure photometric redshifts) and a spectroscopic sample from BOSS/eBOSS to estimate the redshift distribution of the DES sources sample. Two distinct methods for using the clustering statistics are described. The first uses the clustering information independently to estimate the mean redshift of the source galaxies within a redshift window, as done in the DES Y1 analysis. The second method establishes a likelihood of the clustering data as a function of n(z), which can be incorporated into schemes for generating samples of n(z) subject to combined clustering and photometric constraints. Both methods incorporate marginalization over various astrophysical systematics, including magnification and redshift-dependent galaxy-matter bias. We characterize the uncertainties of the methods in simulations; the first method recovers the mean z of tomographic bins to RMS (precision) of ∼0.014. Use of the second method is shown to vastly improve the accuracy of the shape of n(z) derived from photometric data. The two methods are then applied to the DES Y3 data.

Dissecting the Strong-lensing Galaxy Cluster MS 0440.5+0204. II. New Optical Spectroscopic Observations in a Wider Area and Cluster Dynamical State

Abstract We present an optical study of the strong-lensing galaxy cluster MS 0440.5+0204 at z = 0.19593, based on CFHT/MegaCam g′, r′ photometry and GMOS/Gemini and CFHT/MOS/SIS spectroscopy in a broader area than previous works. We have determined new spectroscopic redshifts for the most prominent gravitational arcs surrounding the central galaxy in the cluster. The new redshifts and the information provided by the photometric catalog allow us to perform a detailed weak- and strong-lensing mass reconstruction of the cluster. The large number of member galaxies and the area covered by our observations allow us to estimate more accurately the velocity dispersion and mass of the cluster and to examine in detail the nature of the cluster and surrounding structures. The dynamical mass is in good agreement with the mass inferred from the lensing analysis and X-ray estimates. About 68% of the galaxies are located in the inner ≲0.86 h 70 − 1 Mpc region of the cluster. The galaxy redshift distribution in the inner region of the cluster shows a complex structure with at least three substructures along the line of sight. Other substructures are also identified in the galaxy density map and in the weak-lensing mass map. The member galaxies in the northeast overdensity are distributed in a filament between the clusters MS 0440.5+0204 and ZwCL 0441.1+0211, suggesting that these two structures might be connected. MS 0440.5+0204 appears to be dynamically active, with a cluster core that is likely experiencing a merging process, and with other nearby groups at projected distances of ≲1 h 70 − 1 Mpc that could be being accreted by the cluster.

Emulation of Cosmological Mass Maps with Conditional Generative Adversarial Networks.

Weak gravitational lensing mass maps play a crucial role in understanding the evolution of structures in the Universe and our ability to constrain cosmological models. The prediction of these mass maps is based on expensive N-body simulations, which can create a computational bottleneck for cosmological analyses. Simulation-based emulators of map summary statistics, such as the matter power spectrum and its covariance, are starting to play increasingly important role, as the analytical predictions are expected to reach their precision limits for upcoming experiments. Creating an emulator of the cosmological mass maps themselves, rather than their summary statistics, is a more challenging task. Modern deep generative models, such as Generative Adversarial Networks (GAN), have demonstrated their potential to achieve this goal. Most existing GAN approaches produce simulations for a fixed value of the cosmological parameters, which limits their practical applicability. We propose a novel conditional GAN model that is able to generate mass maps for any pair of matter density Ωm and matter clustering strength σ 8, parameters which have the largest impact on the evolution of structures in the Universe, for a given source galaxy redshift distribution n(z). Our results show that our conditional GAN can interpolate efficiently within the space of simulated cosmologies, and generate maps anywhere inside this space with good visual quality high statistical accuracy. We perform an extensive quantitative comparison of the N-body and GAN -generated maps using a range of metrics: the pixel histograms, peak counts, power spectra, bispectra, Minkowski functionals, correlation matrices of the power spectra, the Multi-Scale Structural Similarity Index (MS-SSIM) and our equivalent of the Fréchet Inception Distance. We find a very good agreement on these metrics, with typical differences are <5% at the center of the simulation grid, and slightly worse for cosmologies at the grid edges. The agreement for the bispectrum is slightly worse, on the <20% level. This contribution is a step toward building emulators of mass maps directly, capturing both the cosmological signal and its variability. We make the code 1 and the data 2 publicly available.

Exploiting the IRT-THESEUS Capability to Observe Lensed Quasars

THESEUS is an ESA space based project, which aims to explore the early universe by unveiling a complete census of Gamma-ray Burst (GRB) population in the first billion years. This goal is expected to be realized by the combined observations of its three instruments on board: the Soft X-ray Imager (SXI), the X and Gamma Imaging Spectrometer (XGIS), and the InfraRed Telescope (IRT). This last one will identify, localise, and study the afterglow of the GRBs detected by SXI and XGIS, and about 40% of its time will be devoted to an all-sky photometric survey, which will certainly detect a relevant number of extragalactic sources, including Quasars. In this paper, we focus on the capability of IRT-THESEUS Telescope to observe Quasars and, in particular, Quasars lensed by foreground galaxies. In our analysis we consider the recent results for the Quasar Luminosity Function (QLF) in the infrared band based on the Spitzer Space Telescope imaging survey. In order to estimate the number of lensed Quasars, we develop Monte Carlo simulations using the mass-luminosity distribution function of galaxies and the galaxy and Quasar redshift distributions. We predict about 2.14 × 105 Quasars to be observed during IRT-Theseus sky survey, and approximately 140 of them lensed by foreground galaxies. Detailed studies of these events would provide a powerful probe of the physical properties of Quasars and the mass distribution models of the galaxies.

High-resolution tomography for galaxy spectroscopic surveys with angular redshift fluctuations

In the context of next-generation spectroscopic galaxy surveys, new statistics of the distribution of matter are currently being developed. Among these, we investigated the angular redshift fluctuations (ARF), which probe the information contained in the projected redshift distribution of galaxies. Relying on the Fisher formalism, we show how ARF will provide complementary cosmological information compared to traditional angular galaxy clustering. We tested both the standard ΛCDM model and the wCDM extension. We find that the cosmological and galaxy bias parameters express different degeneracies when inferred from ARF or from angular galaxy clustering. As such, combining both observables breaks these degeneracies and greatly decreases the marginalised uncertainties by a factor of at least two on most parameters for the ΛCDM and wCDM models. We find that the ARF combined with angular galaxy clustering provide a great way to probe dark energy by increasing the figure of merit of the w0 − wa parameter set by a factor of more than ten compared to angular galaxy clustering alone. Finally, we compared ARF to the CMB lensing constraints on the galaxy bias parameters. We show that a joint analysis of ARF and angular galaxy clustering improves constraints by ∼40% on galaxy bias compared to a joint analysis of angular galaxy clustering and CMB lensing.

Towards simulating a realistic data analysis with an optimised angular power spectrum of spectroscopic galaxy surveys

AbstractThe angular power spectrum is a natural tool to analyse the observed galaxy number count fluctuations. In a standard analysis, the angular galaxy distribution is sliced into concentric redshift bins and all correlations of its harmonic coefficients between bin pairs are considered—a procedure referred to as ‘tomography’. However, the unparalleled quality of data from oncoming spectroscopic galaxy surveys for cosmology will render this method computationally unfeasible, given the increasing number of bins. Here, we put to test against synthetic data a novel method proposed in a previous study to save computational time. According to this method, the whole galaxy redshift distribution is subdivided into thick bins, neglecting the cross-bin correlations among them; each of the thick bin is, however, further subdivided into thinner bins, considering in this case all the cross-bin correlations. We create a simulated data set that we then analyse in a Bayesian framework. We confirm that the newly proposed method saves computational time and gives results that surpass those of the standard approach.

Local Hole revisited: evidence for bulk motions and self-consistent outflow

ABSTRACT We revisit our mapping of the ‘Local Hole’, a large underdensity in the local galaxy redshift distribution that extends out to redshift z ≈ 0.05 and a potential source of outflows that may perturb the global expansion rate and thus help mitigate the present ‘H0 tension’. First, we compare local peculiar velocities measured via the galaxy average redshift–magnitude Hubble diagram, $\overline{z}(m)$, with a simple dynamical outflow model based on the average underdensity in the Local Hole. We find that this outflow model is in good agreement with our peculiar velocity measurements from $\overline{z}(m)$ and not significantly inconsistent with Type Ia supernova peculiar velocity measurements from at least the largest previous survey. This outflow could cause an ≈2–3 per cent increase in the local value of Hubble’s constant. Second, considering anisotropic motions, we find that the addition of the outflow model may improve the $\overline{z}(m)$ fit of a bulk flow where galaxies are otherwise at rest in the Local Group frame. We conclude that the Local Hole plus neighbouring overdensities such as the Shapley Supercluster may cause outflow and bulk motions out to ≈150 h−1 Mpc that are cosmologically significant and that need to be taken into account in estimating Hubble’s constant.

Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing

ABSTRACT Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogues from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multiband deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalogue created from N-body simulations. It yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of σΔz = 0.007, which is a 60 per cent improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.

Constraining neutrino mass with weak lensing Minkowski Functionals

The presence of massive neutrinos affects structure formation, leaving imprints on large-scale structure observables such as the weak lensing field. The common lensing analyses with two-point statistics are insensitive to the large amount of non-Gaussian information in the density field. We investigate non-Gaussian tools, in particular the Minkowski Functionals (MFs)—morphological descriptors including area, perimeter, and genus—in an attempt to recover the higher-order information. We use convergence maps from the Cosmological Massive Neutrino Simulations (MassiveNus) and assume galaxy noise, density, and redshift distribution for an LSST-like survey. We show that MFs are sensitive to the neutrino mass sum through non-Gaussian features of the lensing field, with a redshift dependence different from that of the power spectrum. We find that redshift tomography significantly improves the constraints on neutrino mass for MFs, compared to the improvements for the convergence power spectrum. We attribute this to the stronger redshift dependence of neutrino effects on small scales. We then build an emulator to model the power spectrum and MFs, and study the constraints on [Mν, Ωm, As] from the power spectrum, MFs, and their combination. We show that, for weak lensing convergence, MFs significantly outperform the power spectrum in constraining neutrino mass, by more than a factor of four. However, a thorough study of the impact from systematics such as baryon physics, galaxy shape and redshift biases will be important to realize the full potential of MFs.

The impact of photometric redshift errors on lensing statistics in ray-tracing simulations

Abstract Weak lensing surveys are reaching sensitivities at which uncertainties in the galaxy redshift distributions n(z) from photo-z errors degrade cosmological constraints. We use ray-tracing simulations and a simple treatment of photo-z errors to assess cosmological parameter biases from uncertainties in n(z) in an LSST-like survey. We use lensing peak counts and the power spectrum to infer cosmological parameters, and find that the latter is somewhat more resilient to photo-z errors. We place conservative lower limits on the survey size at which different types of photo-z errors significantly degrade (${\sim }50{{\ \rm per\ cent}}$) ΛCDM (cold dark matter, wCDM) parameter constraints. A residual constant photo-z bias of |δz| &amp;lt; 0.003(1 + z), the current LSST requirement, does not significantly degrade surveys smaller than ≈1300 (≈490) deg2 using peaks and ≈6500 (≈4900) deg2 using the power spectrum. Surveys smaller than ≈920 (≈450) deg2 and ≈4600 (≈4000) deg2 avoid 25 per cent degradation. Adopting a recent prediction for LSST’s full photo-z probability distribution function (PDF), we find that simply approximating n(z) with the photo-z galaxy distribution computed from this PDF significantly degrades surveys as small as ≈60 (≈65) deg2 using peaks or the power spectrum. If the centroid bias in each tomographic bin is removed from the photo-z galaxy distribution, using peaks or the power spectrum still significantly degrades surveys larger than ≈200 (≈255) or ≈248 (≈315) deg2; 25 per cent degradations occur at survey sizes of ≈140 (≈180) deg2 or ≈165 (≈210) deg2. These results imply that the expected broad photo-z PDF significantly biases parameters, which must be further mitigated using more sophisticated photo-z treatments.