Photometric Redshift Uncertainties Research Articles

A Systematic Search of Distant Superclusters with the Subaru Hyper Suprime-Cam Survey

Superclusters, encompassing environments across a wide range of overdensities, can be regarded as unique laboratories for studying galaxy evolution. Although numerous supercluster catalogs have been published, none of them goes beyond redshift z = 0.7. In this work, we adopt a physically motivated supercluster definition, requiring that superclusters should eventually collapse even in the presence of dark energy. Applying a friends-of-friends (FoF) algorithm to the CAMIRA cluster sample constructed using the Subaru Hyper Suprime-Cam survey data, we have conducted the first systematic search for superclusters at z = 0.5–1.0 and identified 673 supercluster candidates over an area of 1027 deg2. The FoF algorithm is calibrated by evolving N-body simulations to the far future to ensure high purity. We found that these high-z superclusters are mainly composed of two to four clusters, suggesting the limit of gravitationally bound structures in the younger Universe. In addition, we studied the properties of the clusters and brightest cluster galaxies (BCGs) residing in different large-scale environments. We found that clusters associated with superclusters are typically richer, but no apparent dependence of the BCG properties on large-scale structures is found. We also compared the abundance of observed superclusters with mock superclusters extracted from halo light cones, finding that photometric redshift uncertainty is a limiting factor in the performance of superclusters detection.

Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic Star Formation Rate Density 300 Myr after the Big Bang

We characterize the earliest galaxy population in the JADES Origins Field, the deepest imaging field observed with JWST. We make use of ancillary Hubble Space Telescope optical images (five filters spanning 0.4–0.9 μm) and novel JWST images with 14 filters spanning 0.8−5 μm, including seven medium-band filters, and reaching total exposure times of up to 46 hr per filter. We combine all our data at >2.3 μm to construct an ultradeep image, reaching as deep as ≈31.4 AB mag in the stack and 30.3–31.0 AB mag (5σ, r = 0.″1 circular aperture) in individual filters. We measure photometric redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts z = 11.5−15. These objects show compact half-light radii of R 1/2 ∼ 50−200 pc, stellar masses of M ⋆ ∼ 107−108 M ☉, and star formation rates ∼ 0.1−1 M ☉ yr−1. Our search finds no candidates at 15 < z < 20, placing upper limits at these redshifts. We develop a forward-modeling approach to infer the properties of the evolving luminosity function without binning in redshift or luminosity that marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the impact of nondetections. We find a z = 12 luminosity function in good agreement with prior results, and that the luminosity function normalization and UV luminosity density decline by a factor of ∼2.5 from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical models for evolution of the dark matter halo mass function.

Cosmology from weak lensing peaks and minima with Subaru Hyper Suprime-Cam Survey first-year data

ABSTRACT We present cosmological constraints derived from peak counts, minimum counts, and the angular power spectrum of the Subaru Hyper Suprime-Cam first-year (HSC Y1) weak lensing shear catalogue. Weak lensing peak and minimum counts contain non-Gaussian information and hence are complementary to the conventional two-point statistics in constraining cosmology. In this work, we forward-model the three summary statistics and their dependence on cosmology, using a suite of N-body simulations tailored to the HSC Y1 data. We investigate systematic and astrophysical effects including intrinsic alignments, baryon feedback, multiplicative bias, and photometric redshift uncertainties. We mitigate the impact of these systematics by applying cuts on angular scales, smoothing scales, signal-to-noise ratio bins, and tomographic redshift bins. By combining peaks, minima, and the power spectrum, assuming a flat-ΛCDM model, we obtain $S_{8} \equiv \sigma _8\sqrt{\Omega _m/0.3}= 0.810^{+0.022}_{-0.026}$, a 35 per cent tighter constraint than that obtained from the angular power spectrum alone. Our results are in agreement with other studies using HSC weak lensing shear data, as well as with Planck 2018 cosmology and recent CMB lensing constraints from the Atacama Cosmology Telescope and the South Pole Telescope.

Robustness of baryon acoustic oscillations measurements with photometric redshift uncertainties

ABSTRACT We investigate the robustness of baryon acoustic oscillations (BAO) measurements with a photometric galaxy sample using mock galaxy catalogues with various sizes of photometric redshift (photo-z) uncertainties. We first conduct the robustness of BAO measurements, assuming we have a perfect knowledge of photo-z uncertainties. We find that the BAO shift parameter α can be constrained in an unbiased manner even for 3 per cent photometric redshift uncertainties up to z ∼ 1. For instance, α = 1.006 ± 0.078 with 95 per cent confidence level is obtained from 3 per cent photo-z uncertainty data at z = 1.03 using the sample of M* ≥ 1010.25 M⊙ h−2. We also find that a sparse galaxy sample, e.g. &amp;lt;2 × 10−4 [h Mpc−1]3, causes additional noise in the covariance matrix calculation and can bias the constraint on α. Following this, we look into the scenario where incorrect photometric redshift uncertainties are assumed in the fitting model. We find that underestimating the photo-z uncertainty leads to a degradation in the constraining power on α. However, the constrained value of α is not biased. We also quantify the constraining power on Ωm0 assuming the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST)-like covariance and find that the 95 per cent confidence level is σ(Ωm0) ∼ 0.03–0.05 corresponding to the photo-z uncertainties of 1–3 per cent, respectively. Finally, we examine whether the skewness in the photometric redshift can bias the constraint on α and confirm that the constraint on α is unbiased, even assuming a Gaussian photo-z uncertainty in our model.

Towards a full wCDM map-based analysis for weak lensing surveys

ABSTRACT The next generation of weak lensing surveys will measure the matter distribution of the local universe with unprecedented precision, allowing the resolution of non-Gaussian features of the convergence field. This encourages the use of higher-order mass-map statistics for cosmological parameter inference. We extend the forward-modelling based methodology introduced in a previous forecast paper to match these new requirements. We provide multiple forecasts for the $w$CDM parameter constraints that can be expected from stage 3 and 4 weak lensing surveys. We consider different survey setups, summary statistics and mass map filters including wavelets. We take into account the shear bias, photometric redshift uncertainties, and intrinsic alignment. The impact of baryons is investigated and the necessary scale cuts are applied. We compare the angular power spectrum analysis to peak and minima counts as well as Minkowski functionals of the mass maps. We find a preference for Starlet over Gaussian filters. Our results suggest that using a survey setup with 10 instead of 5 tomographic redshift bins is beneficial. Adding cross-tomographic information improves the constraints on cosmology and especially on galaxy intrinsic alignment for all statistics. In terms of constraining power, we find the angular power spectrum and the peak counts to be equally matched for stage 4 surveys, followed by minima counts and the Minkowski functionals. Combining different summary statistics significantly improves the constraints and compensates the stringent scale cuts. We identify the most ‘cost-effective’ combination to be the angular power spectrum, peak counts and Minkowski functionals following Starlet filtering.

Cosmology from the integrated shear 3-point correlation function: simulated likelihood analyses with machine-learning emulators

The integrated shear 3-point correlation function ζ ± measures the correlation between the local shear 2-point function ξ ± and the 1-point shear aperture mass in patches of the sky. Unlike other higher-order statistics, ζ ± can be efficiently measured from cosmic shear data, and it admits accurate theory predictions on a wide range of scales as a function of cosmological and baryonic feedback parameters. Here, we develop and test a likelihood analysis pipeline for cosmological constraints using ζ ±. We incorporate treatment of systematic effects from photometric redshift uncertainties, shear calibration bias and galaxy intrinsic alignments. We also develop an accurate neural-network emulator for fast theory predictions in MCMC parameter inference analyses. We test our pipeline using realistic cosmic shear maps based on N-body simulations with a DES Y3-like footprint, mask and source tomographic bins, finding unbiased parameter constraints. Relative to ξ ±-only, adding ζ ± can lead to ≈ 10-25% improvements on the constraints of parameters like As (or σ 8) and w 0. We find no evidence in ξ ± + ζ ± constraints of a significant mitigation of the impact of systematics. We also investigate the impact of the size of the apertures where ζ ± is measured, and of the strategy to estimate the covariance matrix (N-body vs. lognormal). Our analysis solidifies the strong potential of the ζ ± statistic and puts forward a pipeline that can be readily used to improve cosmological constraints using real cosmic shear data.

Exploring the intrinsic scatter of the star-forming galaxy main sequence at redshift 0.5 to 3.0

ABSTRACT Previous studies have shown that the normalization and scatter of the galaxy ‘main sequence’ (MS), the relation between star formation rate (SFR) and stellar mass (M*), evolves over cosmic time. However, such studies often rely on photometric redshifts and/or only rest-frame UV to near-IR data, which may underestimate the SFR and M* uncertainties. We use MAGPHYS + photo-z to fit the UV to radio spectral energy distributions of 12 380 galaxies in the COSMOS field at 0.5 &amp;lt; z &amp;lt; 3.0, and self-consistently include photometric redshift uncertainties on the derived SFR and M*. We quantify the effect on the observed MS scatter from (1) photometric redshift uncertainties (which are minor) and (2) fitting only rest-frame ultraviolet to near-infrared observations (which are severe). At fixed redshift and M*, we find that the intrinsic MS scatter for our sample of galaxies is 1.4 to 2.6 times larger than the measurement uncertainty. The average intrinsic MS scatter has decreased by 0.1 dex from z = 0.5 to ∼2.0. At low z, the trend between the intrinsic MS scatter and M* follows a functional form similar to an inverse stellar mass-halo mass relation (SMHM; M*/Mhalo versus M*), with a minimum in intrinsic MS scatter at log (M*/M⊙) ∼ 10.25 and larger scatter at both lower and higher M*, while this distribution becomes flatter for high z. The SMHM is thought to be a consequence of feedback effects and this similarity may suggest a link between galaxy feedback and the intrinsic MS scatter. These results favour a slight evolution in the intrinsic MS scatter with both redshift and mass.

KiDS-1000 cosmology: Constraints from density split statistics

Context. Weak lensing and clustering statistics beyond two-point functions can capture non-Gaussian information about the matter density field, thereby improving the constraints on cosmological parameters relative to the mainstream methods based on correlation functions and power spectra. Aims. This paper presents a cosmological analysis of the fourth data release of the Kilo Degree Survey based on the density split statistics, which measures the mean shear profiles around regions classified according to foreground densities. The latter is constructed from a bright galaxy sample, which we further split into red and blue samples, allowing us to probe their respective connection to the underlying dark matter density. Methods. We used the state-of-the-art model of the density splitting statistics and validated its robustness against mock data infused with known systematic effects such as intrinsic galaxy alignment and baryonic feedback. Results. After marginalising over the photometric redshift uncertainty and the residual shear calibration bias, we measured for the full KiDS-bright sample a structure growth parameter of $ S_8\equiv \sigma_8 \sqrt{\Omega_{\mathrm{m}}/0.3}=0.73^{+0.03}_{-0.02} $ that is competitive and consistent with two-point cosmic shear results, a matter density of Ωm = 0.27 ± 0.02, and a constant galaxy bias of b = 1.37 ± 0.10.

Cosmological constraint precision of photometric and spectroscopic multi-probe surveys of China Space Station Telescope (CSST)

ABSTRACT As a Stage IV space-based telescope, the China Space Station Telescope (CSST) can perform photometric and spectroscopic surveys simultaneously to explore the Universe efficiently in extreme precision. In this work, we investigate several powerful CSST cosmological probes, including cosmic shear, galaxy–galaxy lensing, photometric and spectroscopic galaxy clustering, and number counts of galaxy clusters, and study the capability of these probes by forecasting the results of joint constraints on the cosmological parameters. By referring to real observational results, we generate mock data and estimate the measured errors based on CSST observational and instrumental designs. To study systematic effects on the results, we also consider a number of systematics in CSST photometric and spectroscopic surveys, such as the intrinsic alignment, shear calibration uncertainties, photometric redshift uncertainties, galaxy bias, non-linear effects, instrumental effects, etc. The Fisher matrix method is used to derive the constraint results on the cosmological and systematic parameters from individual or joint surveys. We find that the joint constraints achieved by including all these CSST cosmological probes can significantly improve the results from current observations by one order of magnitude at least, which gives Ωm and σ8 &amp;lt;1 per cent accuracy and w0 and wa &amp;lt;5 and 20 per cent accuracy, respectively. This indicates that CSST photometric and spectroscopic multi-probe surveys could provide powerful tools with which to explore the Universe and greatly improve the studies of relevant cosmological problems.

Probing the megaparsec-scale environment of hyperluminous infrared galaxies at 2 &lt; z &lt; 4

Context. Protoclusters are progenitors of galaxy clusters and they serve as an important key in studies of how halo mass and stellar mass assemble in the early universe. Finding the signposts of such overdense regions, such as bright dusty star-forming galaxies (DSFG), is a popular method for identifying protocluster candidates. Aims. Hyperluminous infrared galaxies (HLIRGs) are ultramassive and show extreme levels of dusty star formation and black hole accretion that are expected to reside in overdense regions with massive halos. We study the megaparsec-scale environment of the largest HLIRG sample to date (526 HLIRGs over 26 deg2) and we investigate whether they are, in fact, predominantly located in overdense regions. Methods. We first explored the surface density of Herschel 250 μm sources around HLIRGs and made comparisons with the corresponding values around random positions. Then, we compared the spatial distribution of neighbors around HLIRGs with their counterparts around randomly selected galaxies using a deep IRAC-selected catalog with good-quality photometric redshifts. We also used a redshift-matched quasar sample and submillimeter galaxy (SMG) sample to validate our method, as previous clustering studies have measured the host halo masses of these populations. Finally, we adopted a friends of friends (FoF) algorithm to look for (proto)clusters hosting HLIRGs. Results. We find that HLIRGs tend to have more bright star-forming neighbors (with 250 μm flux density &gt; 10 mJy) within a 100″ projected radius (∼0.8 Mpc at 2 &lt; z &lt; 4), as compared to a random galaxy at a 3.7σ significance. In our 3D analysis, we find relatively weak excess of IRAC-selected sources within 3 Mpc around HLIRGs compared with random galaxy neighbors, mainly influenced by photometric redshift uncertainty and survey depth. We find a more significant difference (at a 4.7σ significance) in the number of Low Frequency Array (LOFAR)-detected neighbors in the deepest ELAIS-N1 (EN1) field. Furthermore, HLIRGs at 3 &lt; z &lt; 4 show stronger excess compared to HLIRGs at 2 &lt; z &lt; 3 (0.13 ± 0.04 and 0.14 ± 0.01 neighbors around HLIRGs and random positions at 2 &lt; z &lt; 3, respectively, and 0.08 ± 0.04 and 0.05 ± 0.01 neighbors around HLIRGs and random positions at 3 &lt; z &lt; 4, respectively), which is consistent with cosmic downsizing. Finally, we present a list of 30 of the most promising protocluster candidates selected for future follow-up observations.

Photometric redshift uncertainties in weak gravitational lensing shear analysis: models and marginalization

ABSTRACT Recovering credible cosmological parameter constraints in a weak lensing shear analysis requires an accurate model that can be used to marginalize over nuisance parameters describing potential sources of systematic uncertainty, such as the uncertainties on the sample redshift distribution n(z). Due to the challenge of running Markov chain Monte Carlo (MCMC) in the high-dimensional parameter spaces in which the n(z) uncertainties may be parametrized, it is common practice to simplify the n(z) parametrization or combine MCMC chains that each have a fixed n(z) resampled from the n(z) uncertainties. In this work, we propose a statistically principled Bayesian resampling approach for marginalizing over the n(z) uncertainty using multiple MCMC chains. We self-consistently compare the new method to existing ones from the literature in the context of a forecasted cosmic shear analysis for the HSC three-year shape catalogue, and find that these methods recover statistically consistent error bars for the cosmological parameter constraints for predicted HSC three-year analysis, implying that using the most computationally efficient of the approaches is appropriate. However, we find that for data sets with the constraining power of the full HSC survey data set (and, by implication, those upcoming surveys with even tighter constraints), the choice of method for marginalizing over n(z) uncertainty among the several methods from the literature may modify the 1σ uncertainties on Ωm–S8 constraints by ∼4 per cent, and a careful model selection is needed to ensure credible parameter intervals.

Type Ia supernova Hubble diagrams with host galaxy photometric redshifts

Systematic uncertainties associated to type Ia supernova (SN Ia) Hubble diagrams from photometrically selected samples using photometric SN host galaxy redshifts are investigated. The host redshift uncertainties and the contamination by core-collapse SNe are both addressed. As a test case, we use the 3-year photometric SN Ia sample of the SuperNova Legacy Survey (SNLS), consisting of 437 objects between 0.1 and 1.05 in redshift with 4.7% contamination. We combine this sample with non-SNLS objects of the spectroscopic sample from the joint analysis (JLA) of the SDSS-II and SNLS collaborations, consisting of 501 objects mostly below 0.4 in redshift. We study two options for the origin of the redshifts of the photometric sample, either provided entirely from the host photometric redshift catalogue used in the selection or a mixed origin where around 75% of the sample can be assigned spectroscopic redshifts from dedicated measurements or external catalogues. Using light curve simulations subject to the same photometric selection as data, we study the impact of photometric redshift uncertainties and contamination on flatΛCDM fits to Hubble diagrams from such combined samples. Our primary finding is that photometric redshifts and contamination lead to biased cosmological parameters. The magnitude of the bias is found to be similar for both redshift options. This bias can be largely accounted for if photometric redshift uncertainties and contamination are taken into account when computing the SN magnitude bias correction due to selection effects. To reduce the residual cosmological bias, we explore two methods to propagate redshift uncertainties into the cosmological likelihood computation, either by refitting photometric redshifts along with cosmology or by sampling the redshift resolution function. Redshift refitting fails at correcting the cosmological bias whatever the redshift origin, while sampling slightly reduces it in both cases. Finally, for actual data, we find compatible results with those from the JLA diagram for mixed photometric and spectroscopic redshifts, while the full photometric option is biased upwards, but consistent with JLA when all statistical and systematic uncertainties are included.

Forecast of neutrino cosmology from the CSST photometric galaxy clustering and cosmic shear surveys

ABSTRACT China Space Station Telescope (CSST) is a forthcoming powerful Stage IV space-based optical survey equipment. It is expected to explore a number of important cosmological problems in extremely high precision. In this work, we focus on investigating the constraints on neutrino mass and other cosmological parameters under the model of cold dark matter with a constant equation of state of dark energy (wCDM), using the mock data from the CSST photometric galaxy clustering and cosmic shear surveys (i.e. 3 × 2 pt). The systematics from galaxy bias, photometric redshift uncertainties, intrinsic alignment, shear calibration, baryonic feedback, non-linear, and instrumental effects are also included in the analysis. We generate the mock data based on the COSMOS catalogue considering the instrumental and observational effects of the CSST, and make use of the Markov chain Monte Carlo method to perform the constraints. Comparing to the results from current similar measurements, we find that CSST 3 × 2 pt surveys can improve the constraints on the cosmological parameters by one order of magnitude at least. We can obtain an upper limit for the sum of neutrino mass Σmν ≲ 0.36 (0.56) eV at 68 per cent (95 per cent) confidence level (CL), and Σmν ≲ 0.23 (0.29) eV at 68 per cent (95 per cent) CL if we ignore the baryonic effect, which is comparable to the Planck results and much better than the current photometric surveys. This indicates that the CSST photometric surveys can provide stringent constraints on the neutrino mass and other cosmological parameters, and the results also can be further improved by including data from other kinds of CSST cosmological surveys.

Dark Energy Survey Year 3 results: Cosmology from combined galaxy clustering and lensing validation on cosmological simulations

We present a validation of the Dark Energy Survey Year 3 (DES Y3) $3\times2$-point analysis choices by testing them on Buzzard v2.0, a new suite of cosmological simulations that is tailored for the testing and validation of combined galaxy clustering and weak lensing analyses. We show that the Buzzard v2.0 simulations accurately reproduce many important aspects of the DES Y3 data, including photometric redshift and magnitude distributions, and the relevant set of two-point clustering and weak lensing statistics. We then show that our model for the $3\times2$-point data vector is accurate enough to recover the true cosmology in simulated surveys assuming the true redshift distributions for our source and lens samples, demonstrating robustness to uncertainties in the modeling of the non-linear matter power spectrum, non-linear galaxy bias and higher-order lensing corrections. Additionally, we demonstrate for the first time that our photometric redshift calibration methodology, including information from photometry, spectroscopy, clustering cross-correlations, and galaxy-galaxy lensing ratios, is accurate enough to recover the true cosmology in simulated surveys in the presence of realistic photometric redshift uncertainties.

The physical origin of dark energy constraints from rubin observatory and CMB-S4 lensing tomography

ABSTRACT We seek to clarify the origin of constraints on the dark energy equation of state parameter from CMB lensing tomography, that is the combination of galaxy clustering and the cross-correlation of galaxies with CMB lensing in a number of redshift bins. We focus on the analytic understanding of the origin of the constraints. Dark energy information in these data arises from the influence of three primary relationships: distance as a function of redshift (geometry), the amplitude of the power spectrum as a function of redshift (growth), and the power spectrum as a function of wavenumber (shape). We find that the effects from geometry and growth play a significant role and partially cancel each other out, while the shape effect is unimportant. We also show that Dark Energy Task Force figure of merit forecasts from the combination of LSST galaxies and CMB-S4 lensing are comparable to the forecasts from cosmic shear in the absence of the CMB lensing map, thus providing an important independent check. Compared to the forecasts with the LSST galaxies alone, combining CMB lensing and LSST clustering information increases the FoM by roughly a factor of 3–4 in the optimistic scenario where systematics are fully under control. We caution that achieving these forecasts will likely require a full analysis of higher-order biasing, photometric redshift uncertainties, and stringent control of other systematic limitations, which are outside the scope of this work, whose primary purpose is to elucidate the physical origin of the constraints.

Dark energy survey year 3 results: Cosmology with peaks using an emulator approach

ABSTRACT We constrain the matter density Ωm and the amplitude of density fluctuations σ8 within the ΛCDM cosmological model with shear peak statistics and angular convergence power spectra using mass maps constructed from the first three years of data of the Dark Energy Survey (DES Y3). We use tomographic shear peak statistics, including cross-peaks: peak counts calculated on maps created by taking a harmonic space product of the convergence of two tomographic redshift bins. Our analysis follows a forward-modelling scheme to create a likelihood of these statistics using N-body simulations, using a Gaussian process emulator. We take into account the uncertainty from the remaining, largely unconstrained ΛCDM parameters (Ωb, ns, and h). We include the following lensing systematics: multiplicative shear bias, photometric redshift uncertainty, and galaxy intrinsic alignment. Stringent scale cuts are applied to avoid biases from unmodelled baryonic physics. We find that the additional non-Gaussian information leads to a tightening of the constraints on the structure growth parameter yielding $S_8~\equiv ~\sigma _8\sqrt{\Omega _{\mathrm{m}}/0.3}~=~0.797_{-0.013}^{+0.015}$ (68 per cent confidence limits), with a precision of 1.8 per cent, an improvement of 38 per cent compared to the angular power spectra only case. The results obtained with the angular power spectra and peak counts are found to be in agreement with each other and no significant difference in S8 is recorded. We find a mild tension of $1.5 \, \sigma$ between our study and the results from Planck 2018, with our analysis yielding a lower S8. Furthermore, we observe that the combination of angular power spectra and tomographic peak counts breaks the degeneracy between galaxy intrinsic alignment AIA and S8, improving cosmological constraints. We run a suite of tests concluding that our results are robust and consistent with the results from other studies using DES Y3 data.

Dark Energy Survey Year 3 Results: Galaxy mock catalogs for BAO analysis

The calibration and validation of scientific analysis in simulations is a fundamental tool to ensure unbiased and robust results in observational cosmology. In particular, mock galaxy catalogs are a crucial resource to achieve these goals in the measurement of baryon acoustic oscillation (BAO) in the clustering of galaxies. Here we present a set of 1952 galaxy mock catalogs designed to mimic the Dark Energy Survey Year 3 BAO sample over its full photometric redshift range 0.6 &lt; zphoto &lt; 1.1. The mocks are based upon 488 ICE-COLA fastN-body simulations of full-sky light cones and were created by populating halos with galaxies, using a hybrid halo occupation distribution – halo abundance matching model. This model has ten free parameters, which were determined, for the first time, using an automatic likelihood minimization procedure. We also introduced a novel technique to assign photometric redshift for simulated galaxies, following a two-dimensional probability distribution with VIMOS Public Extragalactic Redshift Survey data. The calibration was designed to match the observed abundance of galaxies as a function of photometric redshift, the distribution of photometric redshift errors, and the clustering amplitude on scales smaller than those used for BAO measurements. An exhaustive analysis was done to ensure that the mocks reproduce the input properties. Finally, mocks were tested by comparing the angular correlation functionw(θ), angular power spectrumCℓ, and projected clusteringξp(r⊥) to theoretical predictions and data. The impact of volume replication in the estimate of the covariance is also investigated. The success in accurately reproducing the photometric redshift uncertainties and the galaxy clustering as a function of redshift render this mock creation pipeline as a benchmark for future analyses of photometric galaxy surveys.

A composite likelihood approach for inference under photometric redshift uncertainty

ABSTRACTObtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We present an inference methodology that combines the redshift information from the galaxy photometry with constraints from two-point functions, utilizing cross-correlations with spatially overlapping spectroscopic samples, and illustrate the approach on CosmoDC2 simulations. Our likelihood framework is designed to integrate directly into a typical large-scale structure and weak lensing analysis based on two-point functions. We discuss efficient and accurate inference techniques that allow us to scale the method to the large samples of galaxies to be expected in LSST. We consider statistical challenges like the parametrization of redshift systematics, discuss and evaluate techniques to regularize the sample redshift distributions, and investigate techniques that can help to detect and calibrate sources of systematic error using posterior predictive checks. We evaluate and forecast photometric redshift performance using data from the CosmoDC2 simulations, within which we mimic a DESI-like spectroscopic calibration sample for cross-correlations. Using a combination of spatial cross-correlations and photometry, we show that we can provide calibration of the mean of the sample redshift distribution to an accuracy of at least 0.002(1 + z), consistent with the LSST-Y1 science requirements for weak lensing and large-scale structure probes.

Calibration of bias and scatter involved in cluster mass measurements using optical weak gravitational lensing

ABSTRACT Cosmological inference from cluster number counts is systematically limited by the accuracy of the mass calibration, i.e. the empirical determination of the mapping between cluster selection observables and halo mass. In this work we demonstrate a method to quantitatively determine the bias and uncertainties in weak-lensing (WL) mass calibration. To this end, we extract a library of projected matter density profiles from hydrodynamical simulations. Accounting for shear bias and noise, photometric redshift uncertainties, mis-centreing, cluster member contamination, cluster morphological diversity, and line-of-sight projections, we produce a library of shear profiles. Fitting a one-parameter model to these profiles, we extract the so-called WL mass MWL. Relating the WL mass to the halo mass from gravity-only simulations with the same initial conditions as the hydrodynamical simulations allows us to estimate the impact of hydrodynamical effects on cluster number counts experiments. Creating new shear libraries for ∼1000 different realizations of the systematics provides a distribution of the parameters of the WL to halo mass relation, reflecting their systematic uncertainty. This result can be used as a prior for cosmological inference. We also discuss the impact of the inner fitting radius on the accuracy, and determine the outer fitting radius necessary to exclude the signal from neighbouring structures. Our method is currently being applied to different Stage III lensing surveys, and can easily be extended to Stage IV lensing surveys.

The clustering of galaxies in the DESI imaging legacy surveys DR8: I. The luminosity and color dependent intrinsic clustering

In a recent study, we developed a method that models the impact of photometric redshift uncertainty on the two-point correlation function (2PCF). Using this method, we simultaneously obtained both the intrinsic clustering strength and the photometric redshift errors by fitting the projected 2PCF with two integration depths along the line-of-sight. Herein, we apply this method to the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 8 (LS DR8), which is the largest galaxy sample currently available. We separate the galaxies into 20 samples in eight redshift bins, from z = 0.1 to z = 1.0, and several z-band absolute magnitude bins, with Mz ≤ −20. These galaxies are further divided into red and blue subsamples according to their M r 0.5 - M z 0.5 colors. We measure the projected 2PCFs for all these galaxy subsamples and fit them using our photometric redshift 2PCF model. We find that the photometric redshift errors are smaller in the red subsamples than in the overall population. In contrast, some systematic photometric redshift errors exist in the blue subsamples, such that some of the subsamples show a significantly enhanced 2PCF on large scales. Therefore, separately focusing only on the red subsamples and on all the subsamples, we find that the biases of the galaxies in these subsamples exhibit clear color, redshift, and luminosity dependencies; the brighter red galaxies at higher redshift are more biased than their bluer and low-redshift counterparts. Apart from the best-fit set of parameters, σz and b, from this state-of-the-art photometric redshift survey, we obtain high-precision intrinsic clustering measurements for these 40 red- and all-galaxy subsamples. These measurements, on large and small scales, hold important information regarding cosmology and galaxy formation that will be used in our subsequent probes in this series.