We present a combined tomographic weak gravitational lensing analysis of the Kilo Degree Survey (KV450) and the Dark Energy Survey (DES-Y1). We homogenize the analysis of these two public cosmic ...shear datasets by adopting consistent priors and modeling of nonlinear scales, and determine new redshift distributions for DES-Y1 based on deep public spectroscopic surveys. Adopting these revised redshifts results in a 0.8
σ
reduction in the DES-inferred value for
S
8
, which decreases to a 0.5
σ
reduction when including a systematic redshift calibration error model from mock DES data based on the MICE2 simulation. The combined KV450+DES-Y1 constraint on
S
8
= 0.762
−0.024
+0.025
is in tension with the
Planck
2018 constraint from the cosmic microwave background at the level of 2.5
σ
. This result highlights the importance of developing methods to provide accurate redshift calibration for current and future weak-lensing surveys.
We present a tomographic cosmic shear analysis of the Kilo-Degree Survey (KiDS) combined with the VISTA Kilo-Degree Infrared Galaxy Survey. This is the first time that a full optical to near-infrared ...data set has been used for a wide-field cosmological weak lensing experiment. This unprecedented data, spanning 450 deg
2
, allows us to significantly improve the estimation of photometric redshifts, such that we are able to include robustly higher-redshift sources for the lensing measurement, and – most importantly – to solidify our knowledge of the redshift distributions of the sources. Based on a flat ΛCDM model we find
S
8
≡ σ
8
Ω
m
/0.3 = 0.737
+0.040
−0.036
in a blind analysis from cosmic shear alone. The tension between KiDS cosmic shear and the Planck-Legacy CMB measurements remains in this systematically more robust analysis, with
S
8
differing by 2.3
σ
. This result is insensitive to changes in the priors on nuisance parameters for intrinsic alignment, baryon feedback, and neutrino mass. KiDS shear measurements are calibrated with a new, more realistic set of image simulations and no significant B-modes are detected in the survey, indicating that systematic errors are under control. When calibrating our redshift distributions by assuming the 30-band COSMOS-2015 photometric redshifts are correct (following the Dark Energy Survey and the Hyper Suprime-Cam Survey), we find the tension with
Planck
is alleviated. The robust determination of source redshift distributions remains one of the most challenging aspects for future cosmic shear surveys.
We present redshift distribution estimates of galaxies selected from the fourth data release of the Kilo-Degree Survey over an area of ∼1000 deg
2
(KiDS-1000). These redshift distributions represent ...one of the crucial ingredients for weak gravitational lensing measurements with the KiDS-1000 data. The primary estimate is based on deep spectroscopic reference catalogues that are re-weighted with the help of a self-organising map (SOM) to closely resemble the KiDS-1000 sources, split into five tomographic redshift bins in the photometric redshift range 0.1 <
z
B
≤ 1.2. Sources are selected such that they only occupy that volume of nine-dimensional magnitude-space that is also covered by the reference samples (‘gold’ selection). Residual biases in the mean redshifts determined from this calibration are estimated from mock catalogues to be ≲0.01 for all five bins with uncertainties of ∼0.01. This primary SOM estimate of the KiDS-1000 redshift distributions is complemented with an independent clustering redshift approach. After validation of the clustering-
z
on the same mock catalogues and a careful assessment of systematic errors, we find no significant bias of the SOM redshift distributions with respect to the clustering-
z
measurements. The SOM redshift distributions re-calibrated by the clustering-
z
represent an alternative calibration of the redshift distributions with only slightly larger uncertainties in the mean redshifts of ∼0.01 − 0.02 to be used in KiDS-1000 cosmological weak lensing analyses. As this includes the SOM uncertainty, clustering-
z
are shown to be fully competitive on KiDS-1000 data.
We present a catalog of quasars with their corresponding redshifts derived from the photometric Kilo-Degree Survey (KiDS) Data Release 4. We achieved it by training machine learning (ML) models, ...using optical
u
g
ri
and near-infrared
Z
Y
J
H
K
s
bands, on objects known from Sloan Digital Sky Survey (SDSS) spectroscopy. We define inference subsets from the 45 million objects of the KiDS photometric data limited to 9-band detections, based on a feature space built from magnitudes and their combinations. We show that projections of the high-dimensional feature space on two dimensions can be successfully used, instead of the standard color-color plots, to investigate the photometric estimations, compare them with spectroscopic data, and efficiently support the process of building a catalog. The model selection and fine-tuning employs two subsets of objects: those randomly selected and the faintest ones, which allowed us to properly fit the bias versus variance trade-off. We tested three ML models: random forest (RF), XGBoost (XGB), and artificial neural network (ANN). We find that XGB is the most robust and straightforward model for classification, while ANN performs the best for combined classification and redshift. The ANN inference results are tested using number counts,
Gaia
parallaxes, and other quasar catalogs that are external to the training set. Based on these tests, we derived the minimum classification probability for quasar candidates which provides the best purity versus completeness trade-off:
p
(QSO
cand
) > 0.9 for
r
< 22 and
p
(QSO
cand
) > 0.98 for 22 <
r
< 23.5. We find 158 000 quasar candidates in the safe inference subset (
r
< 22) and an additional 185 000 candidates in the reliable extrapolation regime (22 <
r
< 23.5). Test-data purity equals 97% and completeness is 94%; the latter drops by 3% in the extrapolation to data fainter by one magnitude than the training set. The photometric redshifts were derived with ANN and modeled with Gaussian uncertainties. The test-data redshift error (mean and scatter) equals 0.009 ± 0.12 in the safe subset and −0.0004 ± 0.19 in the extrapolation, averaged over a redshift range of 0.14 <
z
< 3.63 (first and 99th percentiles). Our success of the extrapolation challenges the way that models are optimized and applied at the faint data end. The resulting catalog is ready for cosmology and active galactic nucleus (AGN) studies.
We present the methodology for a joint cosmological analysis of weak gravitational lensing from the fourth data release of the ESO Kilo-Degree Survey (KiDS-1000) and galaxy clustering from the ...partially overlapping Baryon Oscillation Spectroscopic Survey (BOSS) and the 2-degree Field Lensing Survey (2dFLenS). Cross-correlations between BOSS and 2dFLenS galaxy positions and source galaxy ellipticities have been incorporated into the analysis, necessitating the development of a hybrid model of non-linear scales that blends perturbative and non-perturbative approaches, and an assessment of signal contributions by astrophysical effects. All weak lensing signals were measured consistently via Fourier-space statistics that are insensitive to the survey mask and display low levels of mode mixing. The calibration of photometric redshift distributions and multiplicative gravitational shear bias has been updated, and a more complete tally of residual calibration uncertainties was propagated into the likelihood. A dedicated suite of more than 20 000 mocks was used to assess the performance of covariance models and to quantify the impact of survey geometry and spatial variations of survey depth on signals and their errors. The sampling distributions for the likelihood and the
χ
2
goodness-of-fit statistic have been validated, with proposed changes for calculating the effective number of degrees of freedom. The prior volume was explicitly mapped, and a more conservative, wide top-hat prior on the key structure growth parameter
S
8
=
σ
8
(Ω
m
/0.3)
1/2
was introduced. The prevalent custom of reporting
S
8
weak lensing constraints via point estimates derived from its marginal posterior is highlighted to be easily misinterpreted as yielding systematically low values of
S
8
, and an alternative estimator and associated credible interval are proposed. Known systematic effects pertaining to weak lensing modelling and inference are shown to bias
S
8
by no more than 0.1 standard deviations, with the caveat that no conclusive validation data exist for models of intrinsic galaxy alignments. Compared to the previous KiDS analyses,
S
8
constraints are expected to improve by 20% for weak lensing alone and by 29% for the joint analysis.
Abstract
We present a weak gravitational lensing analysis of 815 deg2 of i-band imaging from the Kilo-Degree Survey (KiDS-i-800). In contrast to the deep r-band observations, which take priority ...during excellent seeing conditions and form the primary KiDS data set (KiDS‐r‐450), the complementary yet shallower KiDS-i-800 spans a wide range of observing conditions. The overlapping KiDS-i-800 and KiDS‐r‐450 imaging therefore provides a unique opportunity to assess the robustness of weak lensing measurements. In our analysis we introduce two new ‘null’ tests. The ‘nulled’ two-point shear correlation function uses a matched catalogue to show that the calibrated KiDS-i-800 and KiDS‐r‐450 shear measurements agree at the level of 1 ± 4 per cent. We use five galaxy lens samples to determine a ‘nulled’ galaxy–galaxy lensing signal from the full KiDS-i-800 and KiDS‐r‐450 surveys and find that the measurements agree to 7 ± 5 per cent when the KiDS-i-800 source redshift distribution is calibrated using either spectroscopic redshifts, or the 30-band photometric redshifts from the COSMOS survey.
We present a bright galaxy sample with accurate and precise photometric redshifts (photo-zs), selected using ugriZYJHKs photometry from the Kilo-Degree Survey (KiDS) Data Release 4. The highly pure ...and complete dataset is flux-limited at r < 20 mag, covers ∼1000 deg2, and contains about 1 million galaxies after artifact masking. We exploit the overlap with Galaxy And Mass Assembly spectroscopy as calibration to determine photo-zs with the supervised machine learning neural network algorithm implemented in the ANNz2 software. The photo-zs have a mean error of |⟨δz⟩|∼5 × 10−4 and low scatter (scaled mean absolute deviation of ∼0.018(1 + z)); they are both practically independent of the r-band magnitude and photo-z at 0.05 < zphot < 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, used them as lenses, and measured 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⋆ > 5 × 1011 M⊙), the red galaxies occupy dark matter halos that are much more massive than those occupied by blue galaxies with the same stellar mass.
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 enhanced 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 performed a Complete Orthogonal Sets of E/B-Integrals (COSEBIs) cosmic shear analysis of the newly calibrated KiDS sample. We found
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 3.4
σ
. We repeated the redshift calibration with different subsets of the full calibration sample and obtained, in all cases, agreement within at most 0.5
σ
in
S
8
compared to our fiducial analysis. Including additional photometric redshifts allowed 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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