Photo-z Errors Research Articles

Measuring the Conditional Luminosity and Stellar Mass Functions of Galaxies by Combining the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 Data

In this investigation, we leverage the combination of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 data sets to estimate the conditional luminosity functions and conditional stellar mass functions (CLFs and CSMFs) of galaxies across various halo mass bins and redshift ranges. To support our analysis, we utilize a realistic DESI mock galaxy redshift survey (MGRS) generated from a high-resolution Jiutian simulation. An extended halo-based group finder is applied to both MGRS catalogs and DESI observation. By comparing the r- and z-band luminosity functions (LFs) and stellar mass functions (SMFs) derived using both photometric and spectroscopic data, we quantified the impact of photometric redshift (photo-z) errors on the galaxy LFs and SMFs, especially in the low-redshift bin at the low-luminosity/mass end. By conducting prior evaluations of the group finder using MGRS, we successfully obtain a set of CLF and CSMF measurements from observational data. We find that at low redshift, the faint-end slopes of CLFs and CSMFs below ∼109 h −2 L ⊙ (or h −2 M ⊙) evince a compelling concordance with the subhalo mass functions. After correcting the cosmic variance effect of our local Universe following Chen et al., the faint-end slopes of the LFs/SMFs turn out to also be in good agreement with the slope of the halo mass function.

Making the leap. Part I. Modelling the reconstructed lensing convergence PDF from cosmic shear with survey masks and systematics

The last few years have seen the development of a promising theoretical framework for statistics of the cosmic large-scale structure — the theory of large deviations (LDT) for modelling weak-lensing one-point statistics in the mildly nonlinear regime. The goal of this series of papers is to make the leap and lay out the steps to perform an actual data analysis with this theoretical tool. Building upon the LDT framework, in this work (paper I) we demonstrate how to accurately model the Probability Distribution Function (PDF) of a reconstructed Kaiser-Squires convergence field under a realistic mask, that of the third data release of the Dark Energy Survey (DES). We also present how weak lensing systematics and higher-order lensing corrections due to intrinsic alignments, shear biases, photo-z errors and baryonic feedback can be incorporated in the modelling of the reconstructed convergence PDF. In an upcoming work (paper II) we will then demonstrate the robustness of our modelling through simulated likelihood analyses, the final step required before applying our method to actual data.

Fisher forecast for the BAO measurements from the CSST spectroscopic and photometric galaxy clustering

ABSTRACT The China Space Station Telescope (CSST) is a forthcoming Stage IV galaxy survey. It will simultaneously undertake the photometric redshift (photo-z) and slitless spectroscopic redshift (spec-z) surveys mainly for weak lensing and galaxy clustering studies. The two surveys cover the same sky area and overlap on the redshift range. At z > 1, due to the sparse number density of the spec-z sample, it limits the constraints on the scale of baryon acoustic oscillations (BAO). By cross-correlating the spec-z sample with the high density photo-z sample, we can effectively enhance the constraints on the angular diameter distances DA(z) from the BAO measurement. Based on the Fisher matrix, we forecast a >30 per cent improvement on constraining DA(z) from the joint analysis of the spec-z and cross galaxy power spectra at 1.0 < z < 1.2. Such improvement is generally robust against different systematic effects including the systematic noise and the redshift success rate of the spec-z survey, as well as the photo-z error. We also show the BAO constraints from other Stage-IV spectroscopic surveys for the comparison with CSST. Our study can be a reference for the future BAO analysis on real CSST data. The methodology can be applied to other surveys with spec-z and photo-z data in the same survey volume.

Forecast of cross-correlation of Chinese Survey Space Telescope cosmic shear tomography with Ali CMB Polarization Telescope cosmic microwave background lensing

ABSTRACT We present a forecast study on the cross-correlation between cosmic shear tomography from the Chinese Survey Space Telescope (CSST) and cosmic microwave background (CMB) lensing from Ali CMB Polarization Telescope (AliCPT-1) in Tibet. The correlated galaxy and CMB lensing signals were generated from Gaussian realizations based on inputted auto and cross-spectra. To account for the error budget, we considered the CMB lensing reconstruction noise based on the AliCPT-1 lensing reconstruction pipeline; shape noise of the galaxy lensing measurement; CSST photo-z error; photo-z bias; intrinsic alignment (IA) effect; and multiplicative bias. The AliCPT-1 CMB lensing mock data were generated according to two experimental stages, namely the ‘4 modules*yr’ and ‘48 modules*yr’ cases. We estimate the cross-spectra in four tomographic bins according to the CSST photo-z distribution in the range of z ∈ [0, 4). After reconstructing the pseudo-cross-spectra from the realizations, we calculate the signal-to-noise ratio (SNR). By combining the four photo-z bins, the total cross-correlation SNR ≈ 15 (AliCPT-1 ‘4 modules*yr’) and SNR ≈ 22 (AliCPT-1 ‘48 modules*yr’). Finally, we study the cosmological application of this cross-correlation signal. Excluding IA in the template fitting would lead to roughly a 0.6σ increment in σ8 due to the negative IA contribution to the galaxy lensing data. For AliCPT-1 first and second stages, the cross-correlation of CSST cosmic shear with CMB lensing gives errors on the clustering amplitude $\sigma _{\sigma _8}=^{+0.043}_{-0.038}$ or $\sigma _{S_8}=\pm 0.031$ and $\sigma _{\sigma _8}=^{+0.030}_{-0.027}$ or $\sigma _{S_8}=\pm 0.018$, respectively.

J-NEP: 60-band photometry and photometric redshifts for the James Webb Space Telescope North Ecliptic Pole Time-Domain Field

The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will observe approximately one-third of the northern sky with a set of 56 narrow-band filters using the dedicated 2.55 m Javalambre Survey Telescope (JST) at the Javalambre Astrophysical Observatory. Prior to the installation of the main camera, in order to demonstrate the scientific potential of J-PAS, two small surveys were performed with the single-CCD Pathfinder camera: miniJPAS (~1 deg2 along the Extended Groth Strip), and J-NEP (~0.3 deg2 around the JWST North Ecliptic Pole Time Domain Field), including all 56 J-PAS filters as well as u, g, r, and i. J-NEP is ~0.5–1.0 mag deeper than miniJPAS, providing photometry for 24,618 r-band-detected sources and photometric redshifts (photo-z) for the 6662 sources with r < 23. In this paper, we describe the photometry and photo-z of J-NEP and demonstrate a new method for the removal of systematic offsets in the photometry based on the median colours of galaxies, which we call ‘galaxy locus recalibration’. This method does not require spectroscopic observations except in a few reference pointings and, unlike previous methods, is directly applicable to the whole J-PAS survey. We use a spectroscopic sample of 787 galaxies to test the photo-z performance for J-NEP and in comparison to miniJPAS. We find that the deeper J-NEP observations result in a factor ~1.5–2 decrease in σNMAD (a robust estimate of the standard deviation of the photo-z error) and η (the outlier rate) relative to miniJPAS for r > 21.5 sources, but no improvement in brighter ones, which is probably because of systematic uncertainties. We find the same relation between σNMAD and odds in J-NEP and miniJPAS, which suggests that we will be able to predict the σNMAD of any set of J-PAS sources from their odds distribution alone, with no need for additional spectroscopy to calibrate the relation. We explore the causes of photo-z outliers and find that colour-space degeneracy at low S/N, photometry artefacts, source blending, and exotic spectra are the most important factors.

Cosmological inference from an emulator based halo model. II. Joint analysis of galaxy-galaxy weak lensing and galaxy clustering from HSC-Y1 and SDSS

We present high-fidelity cosmology results from a blinded joint analysis of galaxy-galaxy weak lensing (ΔΣ) and projected galaxy clustering (wp) measured from the Hyper Suprime-Cam Year-1 (HSC-Y1) data and spectroscopic Sloan Digital Sky Survey (SDSS) galaxy catalogs in the redshift range 0.15<z<0.7. We define luminosity-limited samples of SDSS galaxies to serve as the tracers of wp in three spectroscopic redshift bins, and as the lens samples for ΔΣ. For the ΔΣ measurements, we select a single sample of 4×106 source galaxies over 140 deg2 from HSC-Y1 with photometric redshifts (photo z) greater than 0.75, enabling a better handle of photo-z errors by comparing the ΔΣ amplitudes for the three lens redshift bins. The deep, high-quality HSC-Y1 data enable significant detections of the ΔΣ signals, with integrated signal-to-noise ratio S/N∼15 in the range 3≤R/[h−1 Mpc]≤30 for the three lens samples, despite the small area coverage. For cosmological parameter inference, we use an input galaxy-halo connection model built on the dark emulator package (which uses an ensemble set of high-resolution N-body simulations and enables fast, accurate computation of the clustering observables) with a halo occupation distribution that includes nuisance parameters to marginalize over modeling uncertainties. We model the ΔΣ and wp measurements on scales from R≃3 and 2 h−1 Mpc, respectively, up to 30 h−1 Mpc (therefore excluding the baryon acoustic oscillations information) assuming a flat ΛCDM cosmology, marginalizing over about 20 nuisance parameters and demonstrating the robustness of our results to them. With various tests using mock catalogs described in Miyatake et al. [preceding paper, Phys. Rev. D 106, 083519 (2022)], we show that any bias in the clustering amplitude S8≡σ8(Ωm/0.3)0.5 due to uncertainties in the galaxy-halo connection is less than ∼50% of the statistical uncertainty of S8, unless the assembly biaseffect is unexpectedly large. Our best-fit models have S8=0.795−0.042+0.049 (mode and 68% credible interval) for the flat ΛCDM model; we find tighter constraints on the quantity S8(α=0.17)≡σ8(Ωm/0.3)0.17=0.745−0.031+0.039.23 MoreReceived 29 November 2021Accepted 22 August 2022DOI:https://doi.org/10.1103/PhysRevD.106.083520© 2022 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasCosmologyDark energyGravitational lensesGravitation, Cosmology & Astrophysics

The PAU Survey: narrow-band photometric redshifts using Gaussian processes

ABSTRACT We study the performance of the hybrid template machine learning photometric redshift (photo-z) algorithm delight, which uses Gaussian processes, on a subset of the early data release of the Physics of the Accelerating Universe Survey (PAUS). We calibrate the fluxes of the 40 PAUS narrow bands with six broad-band fluxes (uBVriz) in the Cosmic Evolution Survey (COSMOS) field using three different methods, including a new method that utilizes the correlation between the apparent size and overall flux of the galaxy. We use a rich set of empirically derived galaxy spectral templates as guides to train the Gaussian process, and we show that our results are competitive with other standard photometric redshift algorithms. delight achieves a photo-z 68th percentile error of σ68 = 0.0081(1 + z) without any quality cut for galaxies with iauto &amp;lt; 22.5 as compared to 0.0089(1 + z) and 0.0202(1 + z) for the bpz and annz2 codes, respectively. delight is also shown to produce more accurate probability distribution functions for individual redshift estimates than bpz and annz2. Common photo-z outliers of delight and bcnz2 (previously applied to PAUS) are found to be primarily caused by outliers in the narrow-band fluxes, with a small number of cases potentially indicating spectroscopic redshift failures in the reference sample. In the process, we introduce performance metrics derived from the results of bcnz2 and delight, allowing us to achieve a photo-z quality of σ68 &amp;lt; 0.0035(1 + z) at a magnitude of iauto &amp;lt; 22.5 while keeping 50 per cent objects of the galaxy sample.

A framework for measuring weak-lensing magnification using the Fundamental Plane

ABSTRACT Galaxy–galaxy lensing is an essential tool for probing dark matter haloes and constraining cosmological parameters. While galaxy–galaxy lensing measurements usually rely on shear, weak-lensing magnification contains additional constraining information. Using the Fundamental Plane (FP) of elliptical galaxies to anchor the size distribution of a background population is one method that has been proposed for performing a magnification measurement. We present a formalism for using the FP residuals of elliptical galaxies to jointly estimate the foreground mass and background redshift errors for a stacked lens scenario. The FP residuals include information about weak-lensing magnification κ, and therefore foreground mass, since to first order, non-zero κ affects galaxy size but not other FP properties. We also present a modular, extensible code that implements the formalism using emulated galaxy catalogues of a photometric galaxy survey. We find that combining FP information with observed number counts of the source galaxies constrains mass and photo-z error parameters significantly better than an estimator that includes number counts only. In particular, the constraint on the mass is 17.0 per cent if FP residuals are included, as opposed to 27.7 per cent when only number counts are included. The effective size noise for a foreground lens of mass $M_\mathrm{ H}=10^{14}\, \mathrm{M}_\odot$, with a conservative selection function in size and surface brightness applied to the source population, is σκ, eff = 0.250. We discuss the improvements to our FP model necessary to make this formalism a practical companion to shear analyses in weak-lensing surveys.

Cosmological Studies from Tomographic Weak Lensing Peak Abundances and Impacts of Photo-z Errors

Abstract Weak lensing peak abundance analyses have been applied in different surveys and demonstrated to be a powerful statistic in extracting cosmological information complementary to cosmic shear two-point correlation studies. Future large surveys with high number densities of galaxies will enable tomographic peak analyses. Focusing on high peaks, we investigate quantitatively how the tomographic redshift binning can enhance the cosmological gains. We also perform detailed studies about the degradation of cosmological information due to photometric redshift (photo-z) errors. We show that for surveys with a number density of galaxies of ∼40 arcmin−2, a median redshift of ∼1, and a survey area of ∼15,000 deg2, the four-bin tomographic peak analyses can reduce the error contours of (Ωm, σ 8) by a factor of 5 compared to 2D peak analyses in the ideal case of the photo-z error being absent. More redshift bins can hardly lead to significantly better constraints. The photo-z error model here is parameterized by z bias and σ ph and the fiducial values of z bias = 0.003 and σ ph = 0.02 are taken. We find that using tomographic peak analyses can constrain the photo-z errors simultaneously with cosmological parameters. For four-bin analyses, we can obtain σ(z bias)/z bias ∼ 10% and σ(σ ph)/σ ph ∼ 5% without assuming priors on them. Accordingly, the cosmological constraints on Ωm and σ 8 degrade by factors of ∼2.2 and ∼1.8, respectively, with respect to zero uncertainties on photo-z parameters. We find that the uncertainty of z bias plays a more significant role in degrading the cosmological constraints than that of σ ph.

Luminous red galaxies in the Kilo-Degree Survey: selection with broad-band photometry and weak lensing measurements

We use the overlap between multiband photometry of the Kilo-Degree Survey (KiDS) and spectroscopic data based on the Sloan Digital Sky Survey (SDSS) and Galaxy And Mass Assembly (GAMA) to infer the colour-magnitude relation of red-sequence galaxies. We then use this inferred relation to select luminous red galaxies (LRGs) in the redshift range of $0.1<z<0.7$ over the entire KiDS Data Release 3 footprint. We construct two samples of galaxies with different constant comoving densities and different luminosity thresholds. The selected red galaxies have photometric redshifts with typical photo-z errors of $\sigma_z \sim 0.014 (1+z)$ that are nearly uniform with respect to observational systematics. This makes them an ideal set of galaxies for lensing and clustering studies. As an example, we use the KiDS-450 cosmic shear catalogue to measure the mean tangential shear signal around the selected LRGs. We detect a significant weak lensing signal for lenses out to $z \sim 0.7$.

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.

Combining spectroscopic and photometric surveys using angular cross-correlations – III. Galaxy bias and stochasticity

In the first paper of this series, we studied the effect of baryon acoustic oscillations (BAO), redshift space distortions (RSD) and weak lensing (WL) on measurements of angular cross-correlations in narrow redshift bins. Paper-II presented a multitracer forecast as Figures of Merit (FoM), combining a photometric and spectroscopic stage-IV survey. The uncertainties from galaxy bias, the way light traces mass, is an important ingredient in the forecast. Fixing the bias would increase our FoM equivalent to 3.3 times larger area for the combined constraints. This paper focus on how the modelling of bias affect these results. In the combined forecast, lensing both help and benefit from the improved bias measurements in overlapping surveys after marginalizing over the cosmological parameters. Adding a second lens population in counts-shear does not have a large impact on bias error, but removing all counts-shear information increases the bias error in a significant way. We also discuss the relative impact of WL, magnification, RSD and BAO, and how results change as a function of bias amplitude, photo-z error and sample density. By default we use one bias parameter per bin (with 72 narrow bins), but we show that the results do not change much when we use other parameterizations, with at least 3 parameters in total. Bias stochasticity, even when added as one new free parameter per bin, only produce moderate decrease in the FoM. In general, we find that the degradation in the figure of merit caused by the uncertainties in the knowledge of bias is significantly smaller for overlapping surveys.

Scientific Synergy between LSST and Euclid

Euclid and the Large Synoptic Survey Telescope (LSST) are poised to dramatically change the astronomy landscape early in the next decade. The combination of high cadence, deep, wide-field optical photometry from LSST with high resolution, wide-field optical photometry and near-infrared photometry and spectroscopy from Euclid will be powerful for addressing a wide range of astrophysical questions. We explore Euclid/LSST synergy, ignoring the political issues associated with data access to focus on the scientific, technical, and financial benefits of coordination. We focus primarily on dark energy cosmology, but also discuss galaxy evolution, transient objects, solar system science, and galaxy cluster studies. We concentrate on synergies that require coordination in cadence or survey overlap, or would benefit from pixel-level co-processing that is beyond the scope of what is currently planned, rather than scientific programs that could be accomplished only at the catalog level without coordination in data processing or survey strategies. We provide two quantitative examples of scientific synergies: the decrease in photo-z errors (benefitting many science cases) when high resolution Euclid data are used for LSST photo-z determination, and the resulting increase in weak lensing signal-to-noise ratio from smaller photo-z errors. We briefly discuss other areas of coordination, including high performance computing resources and calibration data. Finally, we address concerns about the loss of independence and potential cross-checks between the two missions and potential consequences of not collaborating.

Reconstructing the integrated Sachs-Wolfe map with galaxy surveys

The Integrated Sachs-Wolfe (ISW) effect is a large-angle modulation of the cosmic microwave background (CMB), generated when CMB photons traverse evolving potential wells associated with large scale structure (LSS). Recent efforts have been made to reconstruct maps of the ISW signal using information from surveys of galaxies and other LSS tracers, but investigation into how survey systematics affect their reliability has so far been limited. Using simulated ISW and LSS maps, we study the impact of galaxy survey properties and systematic errors on the accuracy of reconstructed ISW signal. We find that systematics that affect the observed distribution of galaxies along the line of sight, such as photo-z and bias-evolution related errors, have a relatively minor impact on reconstruction quality. In contrast, however, we find that direction-dependent calibration errors can be very harmful. Specifically, we find that in order to avoid significant degradation of our reconstruction quality statistics, direction-dependent number density fluctuations due to systematics must be controlled so that their variance is smaller than $10^{-6}$ (which corresponds to a 0.1% calibration). Additionally, we explore the implications of our results for attempts to use reconstructed ISW maps to shed light on the origin of large-angle CMB alignments. We find that there is only a weak correlation between the true and reconstructed angular momentum dispersion, which quantifies alignment, even for reconstructed ISW maps which are fairly accurate overall.

Galaxy bias from the Dark Energy Survey Science Verification data: combining galaxy density maps and weak lensing maps

We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a $\sim$116 deg$^{2}$ area of the Dark Energy Survey (DES) Science Verification data. This method was first developed in Amara et al. (2012) and later re-examined in a companion paper (Pujol et al. 2016) with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i$<$22.5 galaxy sample. We find the galaxy bias and 1$\sigma$ error bars in 4 photometric redshift bins to be 1.12$\pm$0.19 (z=0.2-0.4), 0.97$\pm$0.15 (z=0.4-0.6), 1.38$\pm$0.39 (z=0.6-0.8)), and 1.45$\pm$0.56 (z=0.8-1.0). These measurements are consistent at the 2$\sigma$ level with measurements on the same dataset using galaxy clustering and cross-correlation of galaxies with CMB lensing, with most of the redshift bins consistent within the 1{\sigma} error bars. In addition, our method provides the only $\sigma_8$-independent constraint among the three. We forward-model the main observational effects using mock galaxy catalogs by including shape noise, photo-z errors and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Furthermore, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.

Submegaparsec individual photometric redshift estimation from cosmic web constraints

We present a method, PhotoWeb, for estimating photometric redshifts of individual galaxies, and their equivalent distance, with megaparsec and even sub-megaparsec accuracy using the Cosmic Web as a constraint over photo-z estimates. PhotoWeb redshift errors for individual galaxies are of the order of delta_z = 0.0007, compared to errors of delta_z = 0.02 for current photo-z techniques. The mean redshift error is of the order of 0.00005-0.0004 compared to mean errors in the range delta_z =z 0.001-0.01 for the best available photo-z estimates in the literature. Current photo-z techniques based on the spectral energy distribution of galaxies and projected clustering produce redshift estimates with large errors due to the poor constraining power the galaxy's spectral energy distribution and projected clustering can provide. The Cosmic Web, on the other hand, provides the strongest constraints on the position of galaxies. The network of walls, filaments and voids occupy ~%10 of the volume of the Universe, yet they contain ~%95 of galaxies. The cosmic web, being a cellular system with well-defined boundaries, sets a restricted set of intermittent positions a galaxy can occupy along a given line-of-sight. Using the information in the density field computed from spectroscopic redshifts we can narrow the possible locations of a given galaxy along the line of sight from a single broad probability distribution (from photo-z) to one or a few narrow peaks. Our first results improve previous photo-z errors by more than one order of magnitude allowing sub-megaparsec errors in some cases. Such accurate estimates for tens of millions of galaxies will allow unprecedented galaxy-LSS studies. In this work we apply our technique to the SDSS photo-z galaxy sample and discuss its performance and future improvements.

THE SOURCE-LENS CLUSTERING EFFECT IN THE CONTEXT OF LENSING TOMOGRAPHY AND ITS SELF-CALIBRATION

Cosmic shear can only be measured where there are galaxies. This source-lens clustering (SLC) effect has two sources, intrinsic source clustering and cosmic magnification (magnification/size bias). Lensing tomography can suppress the former. However, this reduction is limited by the existence of photo-z error and nonzero redshift bin width. Furthermore, SLC induced by cosmic magnification cannot be reduced by lensing tomography. Through N-body simulations, we quantify the impact of SLC on the lensing power spectrum in the context of lensing tomography. We consider both the standard estimator and the pixel-based estimator. We find that none of them can satisfactorily handle both sources of SLC. (1) For the standard estimator, SLC induced by both sources can bias the lensing power spectrum by O(1)-O(10)%. Intrinsic source clustering also increases statistical uncertainties in the measured lensing power spectrum. However, the standard estimator suppresses intrinsic source clustering in the cross-spectrum. (2) In contrast, the pixel-based estimator suppresses SLC through cosmic magnification. However, it fails to suppress SLC through intrinsic source clustering and the measured lensing power spectrum can be biased low by O(1)-O(10)%. In short, for typical photo-z errors (sigma_z/(1+z)=0.05) and photo-z bin sizes (Delta_z^P=0.2), SLC alters the lensing E-mode power spectrum by 1-10%, with ell~10^3$ and z_s~1 being of particular interest to weak lensing cosmology. Therefore the SLC is a severe systematic for cosmology in Stage-IV lensing surveys. We present useful scaling relations to self-calibrate the SLC effect.

Spectroscopic failures in photometric redshift calibration: cosmological biases and survey requirements

We use N-body-spectrophotometric simulations to investigate the impact of incompleteness and incorrect redshifts in spectroscopic surveys on photometric redshift training and calibration and the resulting effects on cosmological parameter estimation from weak lensing shear–shear correlations. The photometry of the simulations is modelled after the upcoming Dark Energy Survey and the spectroscopy is based on a low/intermediate-resolution spectrograph with wavelength coverage of 5500 < λ < 9500 Å. Spectroscopic follow-up surveys suffer from both incompleteness (inability to obtain spectroscopic redshifts for certain galaxies) and wrong redshifts. Encouragingly, we find that a neural network-based approach can effectively describe the spectroscopic incompleteness in terms of the galaxies’ colours, so that the spectroscopic selection can be applied to the photometric sample. Hence, we find that spectroscopic incompleteness yields no appreciable biases to cosmology, although the statistical constraints degrade somewhat because the photometric survey has to be culled to match the spectroscopic selection. Unfortunately, wrong redshifts have a more severe impact: the cosmological biases are intolerable if more than a per cent of the spectroscopic redshifts are incorrect. Moreover, we find that incorrect redshifts can substantially degrade the perceived accuracy of training set based photo-z estimators, though the actual accuracy is virtually unaffected. The main problem is the difficulty of obtaining redshifts, either spectroscopically or photometrically, for objects at z > 1.3. We discuss several approaches for reducing the cosmological biases, in particular finding that photo-z error estimators can reduce biases appreciably when the photo-z errors are correlated with the spectroscopic failures, but not otherwise.

Spectroscopic needs for imaging dark energy experiments

Large sets of objects with spectroscopic redshift measurements will be needed for imaging dark energy experiments to achieve their full potential, serving two goals:_training_, i.e., the use of objects with known redshift to develop and optimize photometric redshift algorithms; and_calibration_, i.e., the characterization of moments of redshift (or photo-z error) distributions. Better training makes cosmological constraints from a given experiment stronger, while highly-accurate calibration is needed for photo-z systematics not to dominate errors. In this white paper, we investigate the required scope of spectroscopic datasets which can serve both these purposes for ongoing and next-generation dark energy experiments, as well as the time required to obtain such data with instruments available in the next decade. Large time allocations on kilo-object spectrographs will be necessary, ideally augmented by infrared spectroscopy from space. Alternatively, precision calibrations could be obtained by measuring cross-correlation statistics using samples of bright objects from a large baryon acoustic oscillation experiment such as DESI. We also summarize the additional work on photometric redshift methods needed to prepare for ongoing and future dark energy experiments.

ENVIRONMENTAL EFFECTS ON STAR FORMATION ACTIVITY ATz∼ 0.9 IN THE COSMOS FIELD

We investigated the fraction of [OII] emitters in galaxies at z~0.9 as a function of the local galaxy density in the Hubble Space Telescope (HST) COSMOS 2 square degree field. [OII] emitters are selected by the narrow-band excess technique with the NB711-band imaging data taken with Suprime-Cam on the Subaru telescope. We carefully selected 614 photo-z selected galaxies with M_U3500 < -19.31 at z=0.901-0.920, which includes 195 [OII] emitters, to directly compare results with our previous study at z~1.2. We found that the fraction is almost constant at 0.3 Mpc^-2 < Sigma_10th < 10 Mpc^-2. We also checked the fraction of galaxies with blue rest-frame colors of NUV-R < 2 in our photo-z selected sample, and found that the fraction of blue galaxies does not significantly depend on the local density. On the other hand, the semi-analytic model of galaxy formation predicted that the fraction of star-forming galaxies at z~0.9 decreases with increasing the projected galaxy density even if the effects of the projection and the photo-z error in our analysis were taken into account. The fraction of [OII] emitters decreases from ~60% at z~1.2 to ~30% at z~0.9 independent of the galaxy environment. The decrease of the [OII] emitter fraction could be explained mainly by the rapid decrease of the star formation activity in the universe from z~1.2 to z~0.9.