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A. H. Wright

Publications and source records attributed to A. H. Wright.

At least 19 recordsLinked to original sources

The PAU Survey and Euclid: Analysing photometric redshifts from realistically simulated narrow-band photometry with Flagship 2

The study of the large-scale structure of the Universe and the distribution of galaxies has been greatly advanced by the application of various types of photometric redshift estimation techniques. The Physics of the Accelerating Universe Survey (PAUS) is a state-of-the-art imaging survey, designed to provide high-quality photometric data in 40 optical narrow-band filters. In this paper, we present an in-depth analysis of the photometric redshifts obtained from PAUS using realistic simulations. Based on the Euclid Flagship 2 catalogue, we generate PAUS-like simulations with realistic photometric noise and target selection. The mock catalogue is used to explore the accuracy and precision of photometric redshifts of PAUS, investigating the impact of noise and depth, and combinations of broad- and narrow-band data. The simulations reproduce the observed PAUS performance well, with a robust photometric redshift scatter of $σ_{NMAD}/(1+z)\!=\!0.011$ for a mock subsample resembling the spectroscopic validation sample of the data. For the complete PAUS-like sample, which can only be evaluated in the simulation, we find $σ_{NMAD}/(1+z)\!=\!0.028$ for $i_{\rm AB}\!\lesssim\!23$ and outlier fractions below 10%. Forecasts indicate that including Euclid photometry in a joint analysis could further reduce scatter and outlier fractions, especially for faint galaxy populations. The hypothetical case of deeper PAUS observations over a limited sky area, forecasting the potential for future narrow- or medium-band surveys, in combination with Euclid's deep photometry, achieves scatter as low as $σ_{NMAD}/(1+z)\!=\!0.011$ and outlier fractions below 4% for $i_{\rm AB}\!<\!23.5$.

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KiDS-Legacy: Joint analysis of second- and third-order cosmic shear

Weak lensing by large-scale structure is a powerful cosmological probe. While most analyses rely on second-order correlations, these are primarily sensitive to the parameter combination $S_8 = σ_8 (Ω_m/0.3)^{0.5}$, limiting their ability to constrain $Ω_m$ and other cosmological parameters independently. Higher-order statistics capture non-Gaussian features of the density field and can therefore break parameter degeneracies and extract more cosmological information from weak lensing surveys. We present a joint analysis of second- and third-order cosmic shear in the final data release of the Kilo-Degree Survey (KiDS-Legacy). We combine COSEBIs (Complete Orthogonal Sets of E-/B-mode Integrals) at scales between 2' and 300' with third-order aperture mass moments at scales between 4' and 32' to perform a joint analysis of second- and third-order statistics. Compared to previous KiDS analyses, we implement several methodological advances: an intrinsic alignment model with redshift and mass dependence, a baryon correction model validated on multiple hydrodynamical simulations, and corrections for reduced shear and source clustering. Combining COSEBIs with third-order aperture mass statistics in KiDS-Legacy yields $Ω_m = 0.297^{+0.056}_{-0.040}$ and $S_8 = 0.806^{+0.025}_{-0.023}$, significantly tightening the $Ω_m$ constraints and more than doubling the figure of merit in the $Ω_m$--$S_8$ plane compared to the two-point analysis alone. The third-order measurements pass stringent internal consistency tests, are fully compatible with the KiDS-Legacy 2-point constraints, other 2+3-point lensing results and with Planck CMB measurements within $1σ$, providing no evidence for an $S_8$ tension and demonstrating the maturity of 3-point cosmic shear as a key probe for forthcoming surveys.

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UNIONS-3500 Weak Lensing: IV. 2D cosmological constraints in harmonic space

The Ultraviolet Near Infrared Optical Northern Survey (UNIONS) is a photometric survey in the northern sky. The quality of the data in the $r$ band provides precise shape measurements to measure the growth of structures using cosmic shear. This work aims to constrain cosmological parameters using a harmonic-space estimator of the cosmic shear signal, known as pseudo-$C_\ell$, in a non-tomographic analysis. We perform our analysis in the context of the standard $Λ$CDM cosmology. We model astrophysical systematic effects such as baryonic feedback and intrinsic alignments of galaxies. We verify that the point spread function systematic contribution does not affect our results. We assess the impact of different scale cuts and modelling choices on the constraints. We find $S_8 \equiv σ_8 \sqrt{Ω_{\rm m}/0.3} = 0.891^{+0.057}_{-0.084}$, consistent at the $0.79 \, σ$ level with \emph{Planck} and between $0.87$ to $1.51 \, σ$ with other weak lensing surveys. Our results are robust to analysis choices, and we use lognormal simulations to assess the consistency between configuration and harmonic space results, finding a $2.18 \, σ$ agreement between the two statistics. The degeneracy between $S_8$ and the amplitude of the intrinsic alignment, $A_{\rm IA}$, sampled from a prior obtained from direct measurements, is one of the largest sources of uncertainty. This work is part of the first cosmological analysis of the UNIONS survey using cosmic shear and paves the way for future tomographic and $3 \times 2$ point cross-correlation analyses, exploiting the unique overlap of UNIONS with deep spectroscopic surveys in the northern hemisphere.

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Euclid: Photometric redshift calibration with the clustering redshifts technique

Aims: The precision of cosmological constraints from imaging surveys hinges on accurately estimating the redshift distribution $ n(z) $ of tomographic bins, especially their mean redshifts. We assess the effectiveness of the clustering redshifts technique in constraining Euclid tomographic redshift bins to meet the target uncertainty of $ σ( \langle z \rangle ) < 0.002 (1 + z) $. In this work, these mean redshifts are inferred from the small-scale angular clustering of Euclid galaxies, which are distributed into bins with spectroscopic samples localised in narrow redshift slices. Methods: We generate spectroscopic mocks from the Flagship2 simulation for the Baryon Oscillation Spectroscopic Survey (BOSS), the Dark Energy Spectroscopic Instrument (DESI), and Euclid's Near-Infrared Spectrometer and Photometer (NISP) spectroscopic survey. We evaluate and optimise the clustering redshifts pipeline, introducing a new method for measuring photometric galaxy bias (clustering), which is the primary limitation of this technique. Results: We have successfully constrained the means and standard deviations of the redshift distributions for all of the tomographic bins (with a maximum photometric redshift of 1.6), achieving precision beyond the required thresholds. We have identified the main sources of bias, particularly the impact of the 1-halo galaxy distribution, which imposed a minimal separation scale of 1.5 Mpc for evaluating cross-correlations. These results demonstrate the potential of clustering redshifts to meet the precision requirements for Euclid, and we highlight several avenues for future improvements.

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UNIONS-3500 Weak Lensing: III. 2D Cosmological Constraints in Configuration Space

We present the first cosmological constraints from the cosmic shear analysis of the UNIONS-3500 weak lensing galaxy catalogue in configuration space. The Ultraviolet Near Infrared Optical Northern Survey (UNIONS) is the largest and deepest photometric survey of the northern hemisphere to date, with the UNIONS-3500 catalogue using high-quality $r$-band imaging across 3500 deg2 of the sky. We perform a 2D cosmic shear analysis with a single tomographic bin, using the two-point correlation function (2PCF) statistic. Assuming a flat LCDM model, we obtain constraints on the clustering amplitude of S_8 = 0.831^{+0.067}_{-0.078}, which is consistent with constraints from Planck CMB measurements and precedent cosmic shear results within 1sigma. We outline the construction of our cosmological inference pipeline, including the estimation of the source redshift distribution, shear calibration, and covariance matrix, and describe methodologies for the mitigation of systematic effects arising from PSF systematics and B-modes. We demonstrate that our results are robust to variations in analysis choices, including scale cuts, prior ranges, and nonlinear modelling. This paper is part of a coordinated release which collectively demonstrates the maturity and readiness of UNIONS to deliver competitive cosmological results, positioning it as a key stepping stone towards the forthcoming era of Stage IV weak lensing experiments.

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Euclid: Improving redshift distribution reconstruction using a deep-to-wide transfer function

The Euclid mission seeks to understand the Universe expansion history and the nature of dark energy, which requires a very accurate estimate of redshift distribution. Achieving this accuracy relies on reference samples with spectroscopic redshifts, together with a procedure to match them to survey sources for which only photometric redshifts are available. One important source of systematic uncertainty is the mismatch in photometric properties between galaxies in the Euclid survey and the reference objects. We develop a method to degrade the photometry of objects with deep photometry to match the properties of any shallower survey in the multi-band photometric space, preserving all the correlations between the fluxes and their uncertainties. We compare our transfer method with more demanding image-based methods, such as Balrog from the Dark Energy Survey Collaboration. According to metrics, our method outperforms Balrog. We implement it in the redshift distribution reconstruction, based on the self-organising map approach of arXiv:1509.03318, and test it using a realistic sample from the Euclid Flagship Simulation. We find that the key ingredient is to ensure that the reference objects are distributed in the colour space the same way as the wide-survey objects, which can be efficiently achieved with our transfer method. In our best implementation, the mean redshift biases are consistently reduced across the tomographic bins, bringing a significant fraction of them within the Euclid accuracy requirements in all tomographic bins. Equally importantly, the tests allow us to pinpoint which step in the calibration pipeline has the strongest impact on achieving the required accuracy. Our approach also reproduces the overall redshift distributions, which are crucial for applications such as angular clustering.

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Euclid: Photometric redshift calibration with self-organising maps

The Euclid survey aims to trace the evolution of cosmic structures up to redshift $z$ $\sim$ 3 and beyond. Its success depends critically on obtaining highly accurate mean redshifts for ensembles of galaxies $n(z)$ in all tomographic bins, essential for deriving robust cosmological constraints. However, photometric redshifts (photo-$z$s) suffer from systematic biases arising from various sources of uncertainty. To address these challenges, we utilised self-organising maps (SOMs) with mock samples resembling the Euclid Wide Survey (EWS), to validate Euclid's uncertainty requirement of $|Δ\langle z \rangle| = \langle z_{\text{est}} \rangle - \langle z \rangle \leq 0.002 (1+z)$ per tomographic bin, assuming DR3-level data. We observe that defining the redshift tomography using the mean spectroscopic redshift (spec-$z$) per SOM cell, results in none of the ten tomographic redshift bins satisfying the requirement. In contrast, the redshift tomography on the photo-$z$s of the EWS-like sample yields superior results, with eight out of ten bins [$0 < z\leq 2.5$] meeting the Euclid requirement. To enhance the realism of our study, we morph our calibration sample to mimic the C3R2 survey in incremental steps. In this context, a maximum of six out of ten bins meet the requirement, strongly advocating the adoption of a redshift tomography defined by the photo-$z$s of individual galaxies rather than the commonly used mean spec-$z$ of SOM cells. To examine the impact on the expected biases for $Ω_{\text{m}}$, $σ_{8}$, and $Δw_{0}$ measured by Euclid, we perform a Fisher forecast for cosmic shear only, based on our redshift uncertainties. Here, we find that even under an evaluation of the uncertainty where the impact of the redshift bias is substantial, most absolute biases remain below 0.1$σ$ in the idealised scenario and below 0.3$σ$ in the more realistic case.

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AMICO galaxy clusters in KiDS-1000: cosmological constraints and mass calibration from counts and weak lensing

We present the joint modelling of weak-lensing and count measurements of the galaxy clusters detected with the AMICO code, in the fourth data release of the Kilo Degree Survey (KiDS-1000). The analysed sample comprises about 8000 clusters, covering an effective area of 839 deg$^{2}$ and extending up to a redshift of $z = 0.8$. Stacked cluster weak-lensing and count measurements have been derived in bins of redshift and intrinsic richness, $λ^*$. Based on self-organising maps, we reconstructed the true redshift distributions of the background galaxy samples. We accounted for the systematic uncertainties arising from impurities in the background and cluster samples, biases in the cluster $z$ and $λ^*$, projection effects, halo orientation and miscentring, truncation of cluster halo mass distributions, matter correlated with cluster haloes, multiplicative shear bias, baryonic matter, geometric distortions in the lensing profiles, uncertainties in the theoretical halo mass function, and super-sample covariance. We also employed a blinding strategy based on perturbing the cluster sample completeness. The improved statistics and photometry compared to the previous KiDS data release, KiDS-DR3, have led to a halving of the uncertainties on $Ω_{\rm m}$ and $σ_8$, as we obtained $Ω_{\rm m}=0.22\pm0.02$ and $σ_8=0.86\pm0.03$. The constraint on $S_8 \equiv σ_8(Ω_{\rm m}/0.3)^{0.5}$, $S_8=0.74\pm0.03$, is in excellent agreement with recent cluster count and KiDS-1000 cosmic shear analyses, while it shows a $2.8σ$ tension with Planck cosmic microwave background results. The constraints on the $\logλ^*-\log M_{200}$ relation imply a mass precision of 8%, on average. In addition, the result on the intrinsic scatter of the $\logλ^*-\log M_{200}$ relation, $σ_{\rm intr}=0.05\pm0.02$, confirms that $λ^*$ is an excellent mass proxy.

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Euclid and KiDS-1000: Quantifying the impact of source-lens clustering on cosmic shear analyses

The transition from current Stage-III surveys such as the Kilo-Degree Survey (KiDS) to the increased area and redshift range of Stage IV surveys such as Euclid will significantly increase the precision of weak lensing analyses. However, with increasing precision, the accuracy of model assumptions needs to be evaluated. In this study, we quantify the impact of the correlated clustering of weak lensing source galaxies with the surrounding large-scale structure, known as source-lens clustering (SLC), which is commonly neglected. For this, we use simulated cosmological datasets with realistically distributed galaxies and measure shear correlation functions for both clustered and uniformly distributed source galaxies. Cosmological analyses are performed for both scenarios to quantify the impact of SLC on parameter inference for a KiDS-like and a Euclid-like setting. We find for Stage III surveys, SLC has a minor impact when accounting for nuisance parameters for intrinsic alignments and shifts of tomographic bins, as these nuisance parameters absorb the effect of SLC, thus changing their original meaning. For KiDS (Euclid), the inferred intrinsic alignment amplitude $A_{IA}$ changes from $0.11_{-0.46}^{+0.44}$ ($-0.009_{-0.080}^{+0.079}$) for data without SLC to $0.28_{-0.44}^{+0.42}$ ($0.022_{-0.082}^{+0.081}$) with SLC. However, fixed nuisance parameters lead to shifts in $S_8$ and $Ω_{m}$, emphasizing the need for including SLC in the modelling. For Euclid, we find that $σ_8$, $Ω_m$, and $w_0$ are shifted by $0.19$, $0.12$, and $0.12\, σ$, respectively, when including free nuisance parameters, and by $0.20$, $0.16$, and $0.32\,σ$ when fixing the nuisance parameters. Consequently, SLC on its own has only a small impact on the inferred parameter inference when using uninformative priors for nuisance parameters.

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The PAU Survey: Photometric redshift estimation in deep wide fields

We present photometric redshifts (photo-$z$) for the deep wide fields of the Physics of the Accelerating Universe Survey (PAUS), covering an area of $\sim$50 deg$^{2}$, for $\sim$1.8 million objects up to $i_{\textrm{AB}}<23$. The PAUS deep wide fields overlap with the W1 and W3 fields from CFHTLenS and the G09 field from KiDS/GAMA. Photo-$z$ are estimated using the 40 narrow bands (NB) of PAUS and the broad bands (BB) of CFHTLenS and KiDS. We compute the redshifts with the SED template-fitting code BCNZ, with a modification in the calibration technique of the zero-point between the observed and the modelled fluxes, that removes any dependence on spectroscopic redshift samples. We enhance the redshift accuracy by introducing an additional photo-$z$ estimate ($z_{\textrm{b}}$), obtained through the combination of the BCNZ and the BB-only photo-$z$. Comparing with spectroscopic redshifts estimates ($z_{\textrm{s}}$), we obtain a $σ_{68} \simeq 0.019$ for all galaxies with $i_{\textrm{AB}}<23$ and a typical bias $|z_{\textrm{b}}-z_{\textrm{s}}|$ smaller than 0.01. For $z_{\textrm{b}} \sim (0.10-0.75)$ we find $σ_{68} \simeq (0.003-0.02)$, this is a factor of $10-2$ higher accuracy than the corresponding BB-only results. We obtain similar performance when we split the samples into red (passive) and blue (active) galaxies. We validate the redshift probability $p(z)$ obtained by BCNZ and compare its performance with that of $z_{\textrm{b}}$. These photo-$z$ catalogues will facilitate important science cases, such as the study of galaxy clustering and intrinsic alignment at high redshifts ($z \lesssim 1$) and faint magnitudes.

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Modeling Strong Lenses from Wide-Field Ground-Based Observations in KiDS and GAMA

Despite the success of galaxy-scale strong gravitational lens studies with Hubble-quality imaging, the number of well-studied strong lenses remains small. As a result, robust comparisons of the lens models to theoretical predictions are difficult. This motivates our application of automated Bayesian lens modeling methods to observations from public data releases of overlapping large ground-based imaging and spectroscopic surveys: Kilo-Degree Survey (KiDS) and Galaxy and Mass Assembly (GAMA), respectively. We use the open-source lens modeling software PyAutoLens to perform our analysis. We demonstrate the feasibility of strong lens modeling with large-survey data at lower resolution as a complementary avenue to studies that utilize more time-consuming and expensive observations of individual lenses at higher resolution. We discuss advantages and challenges, with special consideration given to determining background source redshifts from single-aperture spectra and to disentangling foreground lens and background source light. High uncertainties in the best-fit parameters for the models due to the limits of optical resolution in ground-based observatories and the small sample size can be improved with future study. We give broadly applicable recommendations for future efforts, and with proper application this approach could yield measurements in the quantities needed for robust statistical inference.

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Potential scientific synergies in weak lensing studies between the CSST and Euclid space probes

Aims. With the next generation of large surveys coming to the stage of observational cosmology soon, it is important to explore their potential synergies and to maximise their scientific outcomes. In this study, we aim to investigate the complementarity of the two upcoming space missions Euclid and the China Space Station Telescope (CSST), focusing on weak lensing (WL) cosmology. In particular, we analyse the photometric redshifts (photo-zs) and the galaxy blending effects. For Euclid, WL measurements suffer from chromatic PSF effects. For this, CSST can provide valuable information for Euclid to obtain more accurate PSF, and to calibrate the color and color-gradient biases for WL measurements. Methods. We create image simulations for different surveys, and quantify the photo-z performance. For blending analyses, we employ high-resolution HST/CANDELS data to mock Euclid, CSST, and an LSST-like survey. We analyse the blending fraction for different cases, and the blending effects on galaxy photometry. Furthermore, we demonstrate that CSST can provide a large enough number of high SNR multi-band galaxy images to calibrate the color-gradient biases for Euclid. Results. The sky coverage of Euclid lies entirely within the CSST footprint. The combination of Euclid with CSST data can be done more uniformly than with the various ground-based data. Our studies show that by combining Euclid and CSST, we can reach a photo-z precision of $σ_{\rm NMAD} \approx 0.04$, and an outlier fraction of $η\approx 2.4\%$. Because of the similarly high resolutions, the data combination of Euclid and CSST can be relatively straightforward for photometry. To include ground-based data, however, sophisticated deblending utilizing priors from high-resolution space data is demanded. The color-gradient biases for Euclid can be well calibrated to the level of 0.1% using galaxies from CSST deep survey.

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Consistent lensing and clustering in a low-$S_8$ Universe with BOSS, DES Year 3, HSC Year 1 and KiDS-1000

We evaluate the consistency between lensing and clustering probes of large-scale structure based on measurements of projected galaxy clustering from BOSS combined with overlapping galaxy-galaxy lensing from three surveys: DES Y3, HSC Y1, and KiDS-1000. An intra-lensing-survey study finds good agreement between these lensing data. We model the observations using the Dark Emulator and fit the data at two fixed cosmologies: Planck, with $S_8=0.83$, and a Lensing cosmology with $S_8=0.76$. For a joint analysis limited to scales with $R>5.25h^{-1}$Mpc, we find that both cosmologies provide an acceptable fit to the data. Full utilisation of the small-scale clustering and lensing measurements is hindered by uncertainty in the impact of baryon feedback and assembly bias, which we account for with a reasoned theoretical error budget. We incorporate a systematic scaling parameter for each redshift bin, $A$, that decouples the lensing and clustering to capture any inconsistency. When a wide range of scales ($0.15<R<60h^{-1}$Mpc) are incorporated, we find different results for the consistency of clustering and lensing between the two cosmologies. Limiting the analysis to the bins for which the impact of the selection of the lens sample is expected to be minimal, for the low-$S_8$ Lensing cosmology, the measurements are consistent with $A$=1; $A=0.91\pm0.04$ using DES+KiDS and $A=0.97\pm0.06$ using HSC. For the Planck cosmology case, we find a discrepancy: $A=0.79\pm0.03$ using DES+KiDS and $A=0.84\pm0.05$ using HSC. We demonstrate that a kSZ-based estimate for baryonic effects alleviates some of the discrepancy in the Planck cosmology. This analysis demonstrates the statistical power of these small-scale measurements, but also indicates that caution is still warranted given current uncertainties in modelling baryonic effects, assembly bias, and selection effects in the foreground sample.

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KiDS & Euclid: Cosmological implications of a pseudo angular power spectrum analysis of KiDS-1000 cosmic shear tomography

We present a tomographic weak lensing analysis of the Kilo Degree Survey Data Release 4 (KiDS-1000), using a new pseudo angular power spectrum estimator (pseudo-$C_{\ell}$) under development for the ESA Euclid mission. Over 21 million galaxies with shape information are divided into five tomographic redshift bins, ranging from 0.1 to 1.2 in photometric redshift. We measured pseudo-$C_{\ell}$ using eight bands in the multipole range $76<\ell<1500$ for auto- and cross-power spectra between the tomographic bins. A series of tests were carried out to check for systematic contamination from a variety of observational sources including stellar number density, variations in survey depth, and point spread function properties. While some marginal correlations with these systematic tracers were observed, there is no evidence of bias in the cosmological inference. B-mode power spectra are consistent with zero signal, with no significant residual contamination from E/B-mode leakage. We performed a Bayesian analysis of the pseudo-$C_{\ell}$ estimates by forward modelling the effects of the mask. Assuming a spatially flat $Λ$CDM cosmology, we constrained the structure growth parameter $S_8 = σ_8(Ω_{\rm m}/0.3)^{1/2} = 0.754_{-0.029}^{+0.027}$. When combining cosmic shear from KiDS-1000 with baryon acoustic oscillation and redshift space distortion data from recent Sloan Digital Sky Survey (SDSS) measurements of luminous red galaxies, as well as the Lyman-$α$ forest and its cross-correlation with quasars, we tightened these constraints to $S_8 = 0.771^{+0.006}_{-0.032}$. These results are in very good agreement with previous KiDS-1000 and SDSS analyses and confirm a $\sim 3σ$ tension with early-Universe constraints from cosmic microwave background experiments.

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KiDS-1000: cosmic shear with enhanced redshift calibration

We present a cosmic shear analysis with an improved redshift calibration for the fourth data release of the Kilo-Degree Survey (KiDS-1000) using self-organising maps (SOMs). Compared to the previous analysis of the KiDS-1000 data, we expand the redshift calibration sample to more than twice its size, now consisting of data of 17 spectroscopic redshift campaigns, and significantly extending the fraction of KiDS galaxies we are able to calibrate with our SOM redshift methodology. We then enhance the calibration sample with precision photometric redshifts from COSMOS2015 and the Physics of the Accelerated Universe Survey (PAUS), allowing us to fill gaps in the spectroscopic coverage of the KiDS data. Finally we perform a Complete Orthogonal Sets of E/B-Integrals (COSEBIs) cosmic shear analysis of the newly calibrated KiDS sample. We find $S_8 = 0.748_{-0.025}^{+0.021}$, which is in good agreement with previous KiDS studies and increases the tension with measurements of the cosmic microwave background to 3.4σ. We repeat the redshift calibration with different subsets of the full calibration sample and obtain, in all cases, agreement within at most 0.5σ in $S_8$ compared to our fiducial analysis. Including additional photometric redshifts allows us to calibrate an additional 6 % of the source galaxy sample. Even though further systematic testing with simulated data is necessary to quantify the impact of redshift outliers, precision photometric redshifts can be beneficial at high redshifts and to mitigate selection effects commonly found in spectroscopically selected calibration samples.

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High-quality strong lens candidates in the final Kilo Degree survey footprint

We present 97 new high-quality strong lensing candidates found in the final $\sim 350\,\rm deg^2$, that completed the full $\sim 1350\,\rm deg^2$ area of the Kilo-Degree Survey (KiDS). Together with our previous findings, the final list of high-quality candidates from KiDS sums up to 268 systems. The new sample is assembled using a new Convolutional Neural Network (CNN) classifier applied to $r$-band (best seeing) and $g,~r,~i$ color-composited images separately. This optimizes the complementarity of the morphology and color information on the identification of strong lensing candidates. We apply the new classifiers to a sample of luminous red galaxies (LRGs) and a sample of bright galaxies (BGs) and select candidates that received a high probability to be a lens from the CNN ($P_{\rm CNN}$). In particular, setting $P_{\rm CNN}>0.8$ for the LRGs, the $1$-band CNN predicts 1213 candidates, while the $3$-band classifier yields 1299 candidates, with only $\sim$30\% overlap. For the BGs, in order to minimize the false positives, we adopt a more conservative threshold, $P_{\rm CNN} >0.9$, for both CNN classifiers. This results in 3740 newly selected objects. The candidates from the two samples are visually inspected by 7 co-authors to finally select 97 "high-quality" lens candidates which received mean scores larger than 6 (on a scale from 0 to 10). We finally discuss the effect of the seeing on the accuracy of CNN classification and possible avenues to increase the efficiency of multi-band classifiers, in preparation of next-generation surveys from ground and space.

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Galaxy and Mass Assembly (GAMA): Tracing galaxy environment using the marked correlation function

We investigate how different galaxy properties - luminosities in u, g, r, J, K-bands, stellar mass, star formation rate and specific star formation rate trace the environment in the local universe. We also study the effect of survey flux limits on galaxy clustering measurements. We measure the two-point correlation function (2pCF) and marked correlation functions (MCFs) using the aforementioned properties as marks. We use nearly stellar-mass-complete galaxy sample in the redshift range 0.1 < z < 0.16 from the Galaxy And Mass Assembly (GAMA) survey with a flux limit of r < 19.8. Further, we impose a brighter flux limit of r < 17.8 to our sample and repeat the measurements to study how this affects galaxy clustering analysis. We compare our results to measurements from the Sloan Digital Sky Survey (SDSS) with flux limits of r < 17.8 and r < 16.8. We show that the stellar mass is the best tracer of galaxy environment, the K-band luminosity being a good substitute, although such a proxy sample misses close pairs of evolved, red galaxies. We also confirm that the u-band luminosity is a good, but not a perfect proxy of star formation rate in the context of galaxy clustering. We observe an effect of the survey flux limit on clustering studies - samples with a higher flux limit (smaller magnitude) miss some information about close pairs of starburst galaxies.

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Bright galaxy sample in the Kilo-Degree Survey Data Release 4: selection, photometric redshifts, and physical properties

We present a bright galaxy sample with accurate and precise photometric redshifts (photo-zs), selected using $ugriZYJHK_\mathrm{s}$ photometry from the Kilo-Degree Survey (KiDS) Data Release 4 (DR4). The highly pure and complete dataset is flux-limited at $r<20$ mag, covers $\sim1000$ deg$^2$, and contains about 1 million galaxies after artifact masking. We exploit the overlap with Galaxy And Mass Assembly (GAMA) spectroscopy as calibration to determine photo-zs with the supervised machine learning neural network algorithm implemented in the ANNz2 software. The photo-zs have mean error of $|\langle δz \rangle| \sim 5 \times 10^{-4}$ and low scatter (scaled mean absolute deviation of $\sim 0.018(1+z)$), both practically independent of the $r$-band magnitude and photo-z at $0.05 < z_\mathrm{phot} < 0.5$. Combined with the 9-band photometry, these allow us to estimate robust absolute magnitudes and stellar masses for the full sample. As a demonstration of the usefulness of these data we split the dataset into red and blue galaxies, use them as lenses and measure the weak gravitational lensing signal around them for five stellar mass bins. We fit a halo model to these high-precision measurements to constrain the stellar-mass--halo-mass relations for blue and red galaxies. We find that for high stellar mass ($M_\star>5\times 10^{11} M_\odot$), the red galaxies occupy dark matter halos that are much more massive than those occupied by blue galaxies with the same stellar mass. The data presented here are publicly released via the KiDS webpage at http://kids.strw.leidenuniv.nl/DR4/brightsample.php.

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