Science data products

Many KiDS papers are accompanied by the release of high-level scientific data, such as MCMC chains, specific catalogs, or software code. This page provides links to such data products as well as accompanying information.

Acknowledgements

Users of any KiDS data must include proper acknowledgements in their publications. In the tables below the Acknowledgements section indicates which papers/data sets should be acknowledged, and the exact text to use is specified on the Acknowledgements page.

Cosmological analyses

KiDS-1000 Cosmology: Constraints beyond flat ΛCDM

Tröster et al., 2021, A&A 649, A88

We present constraints derived from the KiDS-1000 cosmic shear and 3x2pt data on models beyond flat ΛCDM. The links to the paper along with the associated data products can be found below.

Links Paper on arXiv
Data MultiNest nested sampling chains for the extended cosmological models considered in the paper, as well the chains for the joint analyses with SNe and CMB lensing. gzipped tarball (126 MB)
README
Software KiDS Cosmology Analysis Pipeline KCAP
Acknowledge Tröster et al., 2021, A&A 649, A88

The Weak Lensing Radial Acceleration Relation: Constraining Modified Gravity and Cold Dark Matter theories with KiDS-1000

Brouwer et al., 2021, A&A, 650, A113

We present measurements of the radial gravitational acceleration around isolated galaxies, comparing the expected gravitational acceleration given the baryonic matter in the system (g_bar) with the observed gravitational acceleration (g_obs), using weak lensing measurements from the fourth data release of the Kilo-Degree Survey (KiDS-1000). These measurements extend the radial acceleration relation (RAR), traditionally measured using galaxy rotation curves, by 2 decades in g_obs into the low acceleration regime beyond the outskirts of the observable galaxy.

In this data release, each text file contains one Excess Surface Density (ESD) profile obtained using weak gravitational lensing with KiDS-1000. These ESD profiles correspond to the lensing Radial Acceleration Relation (RAR) results shown in the respective figures of Brouwer et al. (2021) as explained in the README file.

Links Paper on arXiv
Data Weak lensing ESD profiles corresponding to the RAR results of Brouwer et al. (2021). tarball (2.3 MB)
README
Software The KiDS Galaxy-Galaxy Lensing (GGL) pipeline (for access contact Cristóbal Sifón: cristobal_._sifon_at_pucv_._cl) KiDS-GGL
Acknowledge See Acknowledgements section of Brouwer et al. (2021)

KiDS-1000 cosmology: Cosmic shear constraints and comparison between two point statistics

Asgari, et al., 2020, A&A, 645, A104

We present cosmological constraints from a cosmic shear analysis of the fourth data release of the Kilo-Degree Survey (KiDS-1000). The links to the paper along with the associated data products can be found below.

Links Paper on arXiv
KiDS-1000 cosmic shear constraints webpage
Data Sampled posteriors in the form of Multinest chains; data vectors, covariance matrices and redshift distribution of galaxies; covariance matrix of the uncertainty in the redshift distributions; configuration files and plotting script compressed tarball (16 MB)
Software KiDS Cosmology Analysis Pipeline KCAP
Plotting script chainconsumer
Acknowledge Asgari, et al., 2020, A&A, 645, A104
KiDS-1000 Weak lensing data

KiDS-1000 Cosmology: Multi-probe weak gravitational lensing and spectroscopic galaxy clustering constraints

Heymans, et al., 2021, A&A, 646, A140

In this paper we present the 3x2pt analysis of KiDS-1000 with BOSS and 2dFLenS. The links to the paper along with the associated data products can be found below.

Links Paper on arXiv
3x2pt cosmology with KiDS-1000, BOSS and 2dFLenS webpage
Data sampled posteriors in the form of Multinest chains for the KiDS-1000 bandpower cosmic shear analysis; BOSS-DR12 galaxy clustering analysis; different 2x2pt combinations and the fiducial 3x2pt analysis gzipped tarball (51 MB)
README
Software Open source software and data repository KiDS-WL
Acknowledge Heymans, et al., 2020, A&A, 646, A140
KiDS-1000 Weak lensing data

KiDS+VIKING-450 and DES-Y1 combined: Cosmology with cosmic shear

Joudaki, et al., 2020, A&A, 638, L1

We present a combined tomographic weak gravitational lensing analysis of the Kilo Degree Survey (KV450) and the Dark Energy Survey (DES-Y1). This includes homogenizing the analysis framework by adopting consistent priors, nonlinear modeling, and calibration of the redshift distributions. The links to the paper along with the associated data products can be found below.

Links Paper on arXiv
Data Primary Monte Carlo Markov Chains gzipped tarball (399 MB)
README
Software Likelihood code KiDS+DES
Acknowledge Joudaki, et al., 2020, A&A, 638, L1
KiDS-450

KiDS+VIKING-450: Cosmic shear tomography with optical+infrared data

Hildebrandt et al. 2020, A&A, 633, A69

The first combined cosmological measurements of KiDS and VIKING were published in Hildebrandt et al. (2019), based on 450 sq.deg. of KiDS+VIKING data. Based on greatly enhanced 9-band photometric redshifts and new image simulations (Kannawadi et al. 2018) this measurement updates the results from Hildebrandt et al. (2017) and significantly increases the systematic robustness.

Links KiDS-VIKING-450 Cosmic Shear webpage
Paper on arXiv
Data Primary Monte Carlo Markov Chains gzipped tarball (1.7 MB)
FITS (1.8 MB)

README
Data Vector (tomographic two-point correlation function), Covariance Matrix, different versions of the redshift distribution gzipped tarball (1.1 MB)

README
Software Likelihood code kv450_cf_likelihood_public
Acknowledge See Acknowledgements section on KiDS+VIKING-450: Cosmic shear tomography with optical+infrared data

Euclid-era cosmology for everyone: Neural net assisted MCMC sampling for the joint 3x2 likelihood

Manrique-Yus & Sellentin, 2020, MNRAS, 491, 2655

We develop a fully non-invasive use of machine learning in order to enable open research on Euclid-sized data sets. Our algorithm leaves complete control over theory and data analysis, unlike many black-box like uses of machine learning. Focusing on a `3x2 analysis' which combines cosmic shear, galaxy clustering and tangential shear at a Euclid-like sky coverage, we arrange a total of 348000 data points into data matrices whose structure permits not only an easy prediction by neural nets, but it additionally permits the essential removal from the data of patterns which the neural nets could not `understand'. The latter provides an often lacking mechanism to control and debias the inference of physics. The theoretical backbone to our neural net training can be any conventional (deterministic) theory code, where we chose CLASS. After training, we infer the seven parameters of a wCDM cosmology by Monte Carlo Markov sampling posteriors at Euclid-like precision within a day. We publicly provide the neural nets which memorise and output all 3x2 power spectra at a Euclid-like sky coverage and redshift binning.

Links Paper on ADS
Data Trained models gzipped tarball (452 MB)
Reference power spectra refeuclid.npy

Software Loading explanatory module to use the trained models and plot power spectra Load_Models.py
Acknowledge See Acknowledgements section in Manrique-Yus & Sellentin (2020)

KiDS+VIKING-450 and DES-Y1 combined: Mitigating baryon feedback uncertainty with COSEBIs

Asgari et al. 2020, A&A 634, 127

Cosmological constraints from a joint cosmic shear analysis of the Kilo-Degree Survey (KV450) and the Dark Energy Survey (DES-Y1), using Complete Orthogonal Sets of E/B-Integrals (COSEBIs). With COSEBIs we isolate any B-modes which have a non-cosmic shear origin and demonstrate the robustness of our cosmological E-mode analysis as no significant B-modes are detected. We highlight how COSEBIs are fairly insensitive to the amplitude of the non-linear matter power spectrum at high k-scales, mitigating the uncertain impact of baryon feedback in our analysis. COSEBIs, therefore, allow us to utilise additional small-scale information, improving the DES-Y1 joint constraints on S8=σ8(Ωm/0.3)0.5 and Ωm by 20%. Adopting a flat ΛCDM model we find S8=0.755+0.019−0.021, which is in 3.2σ tension with the Planck Legacy analysis of the cosmic microwave background.

Links Paper on ADS
Data Primary chains (multinest and emcee)
Data, Covariance matrix and redshift distributions
Plotting script for the chains
gzipped tarball (205 MB)

README
Acknowledge Asgari et al., 2020, A&A 634, 127
KiDS-450

A Bayesian quantification of consistency in correlated datasets

Köhlinger et al. 2019, MNRAS, 484, 3126

We present a novel suite of Bayesian consistency tests for correlated datasets. Without loss of generality we focus on mutually exclusive, correlated subsets of the same dataset in this work. An example for such a dataset are the two-point weak lensing shear correlation functions measured from KiDS-450 data (see Hildebrandt et al. 2017 below). Applying these consistency tests then to the KiDS-450 data, we do not find any evidence for significant internal tension, with significances below 3 σ in all cases.

Links Full paper at ADS
Data Data Vector (tomographic two-point correlation function), Covariance Matrix, DIR and CC redshift distributions gzipped tarball (3.8 MB)

README
Software Likelihood module to be used within MONTE PYTHON kids450_cf_likelihood_public
Modified '2cosmos' MONTE PYTHON (incl. '2cosmos' likelihood for KiDS-450 correlation function data) montepython_2cosmos_public
Acknowledge For the software: Köhlinger et al. 2019 (arXiv:1809.01406)
For the data: Hildebrandt et al. 2017 (MNRAS, 465, 1454)
KiDS-450

KiDS+GAMA: Cosmology constraints from a joint analysis of cosmic shear, galaxy-galaxy lensing and angular clustering

van Uitert et al. 2018, MNRAS, 476, 4662

Based on 450 square degrees of survey data, this is a joint cosmological analysis of cosmic shear, galaxy-galaxy lensing, and angular galaxy clustering. All probes are measured in terms of tomographic band powers integrated over correlation functions. A number of scientific data products are available, including MCMC chains, data vectors, the covariance matrix, and redshift distributions.All data files are accompanied by detailed README files.

Links Paper on ADS
Data Primary Monte Carlo Markov Chains (cosmic shear: ee; galaxy-galaxy lensing: en; angular galaxy clustering: nn) vUitert18_KiDS450_chains_ee.tar.gz
vUitert18_KiDS450_chains_ee_en.tar.gz
vUitert18_KiDS450_chains_ee_en_nn.tar.gz
vUitert18_KiDS450_chains_ee_nn.tar.gz
vUitert18_KiDS450_chains_en_nn.tar.gz

README
Data Vector (tomographic band power spectra), covariance matrix, redshift distributions vUitert18_KiDS450_data.tar.gz

README
Acknowledge van Uitert et al. 2018, MNRAS, 476, 4662
KiDS-450

KiDS-450 + 2dFLenS: Cosmological parameter constraints from weak gravitational lensing tomography and overlapping redshift-space galaxy clustering

Joudaki et al. 2018, MNRAS, 474, 4894

We perform a combined analysis of cosmic shear tomography, galaxy-galaxy lensing tomography, and redshift-space multipole power spectra (monopole and quadrupole) using 450 sq deg of imaging data by KiDS overlapping with two spectroscopic surveys: the 2-degree Field Lensing Survey (2dFLenS) and the Baryon Oscillation Spectroscopic Survey (BOSS). A number of scientific data products are available, including MCMC chains, data vectors, the covariance matrix, redshift distributions, and convolution matrices. The likelihood code is also publicly available. More details can be found in the paper linked below and all data files are accompanied by detailed README files.

Links Paper on ADS
2dFLenS data page
Data Primary Monte Carlo Markov Chains kids2dflenschains.tar.gz (112 MB)

README
Data Vector (tomographic two-point correlation functions, redshift-space multipole power spectra), covariance matrix, redshift distributions, convolution matrices kids2dflensdata.tar.gz (4.3 MB)

README
Software Likelihood code CosmoLSS
Acknowledge Joudaki et al. 2018, MNRAS, 474, 4894
KiDS-450

KiDS-450: weak lensing power spectrum

Köhlinger et al. 2017, MNRAS, 471, 4412

Based on 450 square degrees of survey data, an analysis of the weak gravitational lensing shear power spectrum was published in KiDS-450: the tomographic weak lensing power spectrum and constraints on cosmological parameters (Köhlinger et al. 2017, MNRAS, 471, 4412). A number of scientific data products are available, including MCMC chains, data vectors, the covariance matrix, and redshift distributions, as well as software code specifically written for the analysis. More details can be found in the paper (linked below) and all data files are accompanied by detailed README files.

Links Paper on ADS
Data Primary Monte Carlo Markov Chains 3-z bin analysis:
gzipped tarball (1.9 MB)
FITS (1.9 MB)

2-z bin analysis:
gzipped tarball (1.3 MB)
FITS (1.4 MB)

README
Data Vectors (tomographic E-mode and B-mode band powers for the 2 and 3 z-bin analyses), Covariance Matrices, DIR distributions, and additional calibration data gzipped tarball (5.9 MB)

README
Software Quadratic estimator qe_public
Likelihood module to be used within MONTE PYTHON kids450_qe_likelihood_public
Acknowledge Köhlinger et al. 2017, MNRAS, 471, 4412
KiDS-450

KiDS-450: Cosmological parameter constraints

Hildebrandt & Viola et al. 2017, MNRAS, 465, 1454

Based on 450 square degrees of survey data, the first cosmological parameter constraints from KiDS were published in KiDS-450: Cosmological parameter constraints from tomographic weak gravitational lensing (Hildebrandt & Viola et al. 2017, MNRAS, 465, 1454). A number of scientific data products are available, including MCMC chains, data vectors, the covariance matrix, and redshift distributions. More details can be found on the page linked below and all data files are accompanied by detailed README files.

Links KiDS-450 Cosmic Shear webpage
Paper PDF
Paper on ADS
Data Primary Monte Carlo Markov Chain gzipped tarball  (91 MB)
FITS  (60 MB)

README
Data Vector (tomographic two-point correlation function), Covariance Matrix, DIR and CC redshift distributions gzipped tarball (3.8 MB)

README
Software Likelihood code KiDS-450
Acknowledge Hildebrandt & Viola, 2017, MNRAS, 465, 1454
KiDS-450

Catalogs

High quality strong lens candidates

This catalog combines high quality strong lens candidates from several recent strong lens search projects using KiDS data (Petrillo et al. 2019, Li et al. 2020, Li et al. 2021).

Links KiDS high quality strong lens candidates webpage
Acknowledge Petrillo et al. (2019, MNRAS, 484, 3879)
Li et al. (2020, ApJ, 899, L30)
Li et al. (2021, ApJ, in press, arXiv:2110.01905)
KiDS DR4

KiDS DR4 bright galaxy catalog

This catalog contains galaxies flux-limited to r<20 mag from the ~1000 deg2 KiDS Data Release 4 and provides a highly pure and complete dataset of about 1 million galaxies with photometric redshifts and physical properties.

Links KiDS DR4 bright galaxy catalog webpage
Acknowledge Bilicki et al. (2021, A&A in press, arXiv:2101.06010)
KiDS DR4

KiDS-1000 weak lensing SOM-gold catalogue

The KiDS-1000 data set encompasses 1006 survey tiles. Only galaxies with reliable shape and redshift measurements, our "gold sample", are included in this catalogue. The catalogue contains a total of 21,262,011 sources, and is presented as a single 16GB FITS table.

Links KiDS-1000 weak lensing SOM-gold catalogue webpage
Acknowledge See KiDS-1000 weak lensing SOM-gold catalogue webpage

KiDS DR4 quasar catalog

Based on the KiDS DR4 data a catalog of over 1 million quasar candidates was constructed, using both the optical KiDS and the near-IR VIKING data.

Links KiDS DR4 quasar catalog webpage
Acknowledge Nakoneczny et al. 2021, A&A, 649, A81
KiDS DR4

KiDS+VIKING-450 catalog

The KiDS+VIKING-450 weak lensing shear catalog formed the basis of the first tomographic weak lensing analysis based on a combination of KiDS and VIKING data. Based on the same data set as KiDS DR3, spanning 450 square degrees, although the released shear catalog is filtered to include only sources with reliable shear measurements. Details regarding the catalog can be found on the dedicated webpage linked below.

Links KiDS+VIKING-450 catalog webpage
Acknowledge See KiDS+VIKING-450 catalog webpage

KiDS DR3 quasar catalog

Based on the KiDS DR3 data a catalog of 190,000 quasars was constructed, covering an area of ≈400 sq. degrees.

Links KiDS DR3 quasar catalog webpage
Acknowledge Nakoneczny et al. 2019, A&A, 624, A13
KiDS DR3

KiDS DR2 cluster catalog

Based on the KiDS data released in DR1 and DR2 a catalog of 1543 candidate galaxy clusters was constructed, covering an area of 114 sq. degrees, in the redshift range 0 ≤ z ≤ 0.7.

Links KiDS DR2 cluster catalog webpage
Acknowledge Radovich et al. 2017, A&A, 598, A107
KiDS DR1/DR2

KiDS-450 lensing catalogs

The KiDS-450 weak lensing shear catalog formed the basis of the first tomographic weak lensing analyses from KiDS and the first constraints on cosmological parameters. Based on the same data set as KiDS DR3, spanning 450 square degrees, although the released shear catalog is filtered to include only sources with reliable shear measurements. Details regarding the catalog can be found on the dedicated webpage linked below.

Links KiDS-450 Weak lensing data webpage
Acknowledge KiDS-450

Lensing catalogs 2015

The first KiDS weak lensing results, published in 2015 and 2016, made use of shear catalogs that were based on imaging data from KiDS DR1 and DR2. Some information related to the catalogs and the papers based on them can be found on the webpage linked below.

Links Lensing catalogs 2015 webpage
Acknowledge Lensing catalogs 2015