Determining the Baryon Impact on the Matter Power Spectrum with Galaxy Clusters

The redistribution of baryonic matter in massive halos through processes like active galactic nuclei feedback and star formation leads to a suppression of the matter power spectrum on small scales. This redistribution can be measured empirically via the gas and stellar mass fractions in galaxy clusters, and leaves imprints on their electron density profiles. We constrain two semi-analytical baryon correction models with a compilation of recent Bayesian population studies of galaxy groups and clusters sampling a mass range above $\sim 3 \times 10^{13}$ $M_\odot$, and with cluster gas density profiles derived from deep, high-resolution X-ray observations. We are able to fit all the considered observational data, but highlight some anomalies in the observations. The constraints allow us to place precise, physically informed priors on the matter power spectrum suppression. At a scale of $k=1 h$ Mpc$^{-1}$ we find a suppression of $0.042^{+0.012}_{-0.014}$ ($0.049^{+0.016}_{-0.012}$), while at $k=3h$ Mpc$^{-1}$ we find $0.184^{+0.026}_{-0.031}$ ($0.179^{+0.018}_{-0.020}$), depending on the model used. We also predict at 97.5 percent credibility, that at scales $k<0.37h$ Mpc$^{-1}$ baryon feedback impacts the matter power less than $1\%$. This puts into question if baryon feedback is the driving factor for the discrepancy between cosmic shear and primary CMB results. We independently confirm results on this suppression from small-scale cosmic shear studies, while we exclude some hydro-dynamical simulations with too strong and too weak baryonic feedback. Our empirical prediction of the power spectrum suppression shows that studies of galaxy groups and clusters will be instrumental in unlocking the cosmological constraining power of future cosmic shear experiments like \textit{Euclid} and Rubin-LSST.Comment: 14 pages, 7 figures, submitted to MNRA

What is the super-sample covariance? A fresh perspective for second-order shear statistics

Cosmological analyses of second-order weak lensing statistics require precise and accurate covariance estimates. These covariances are impacted by two sometimes neglected terms: A negative contribution to the Gaussian covariance due to finite survey area and the super-sample covariance (SSC) which for the power spectrum contains the impact by Fourier modes larger than the survey window. We show here that these two effects are connected and can be seen as correction terms to the ``large-field-approximation'', the asymptotic case of an infinitely large survey area. We describe the two terms collectively as ``Finite-Field-Terms''. We derive the covariance of second-order shear statistics from first principles. For this, we use an estimator in real space without relying on an estimator for the power spectrum. The resulting covariance does not scale inversely with the survey area, as naively assumed. This scaling is only correct under the large-field approximation when the contribution of the finite-field terms tends to zero. Furthermore, all parts of the covariance, not only the SSC, depend on the power- and trispectrum at all modes, including those larger than the survey. We also show that it is generally impossible to transform an estimate for the power spectrum covariance into the covariance of a real-space statistic. Such a transformation is only possible in the asymptotic case of the `large-field approximation'. Additionally, we find that the total covariance of a real-space statistic can be calculated using correlation functions estimates on spatial scales smaller than the survey window. Consequently, estimating covariances of real-space statistics, in principle, does not require information on spatial scales larger than the survey area. We demonstrate that this covariance estimation method is equivalent to the standard sample covariance method.Comment: 8 pages + appendix, 3 figures, submitted to Astronomy & Astrophysics, Major revision after comments by referee and communit

KiDS+VIKING+GAMA: Halo occupation distributions and correlations of satellite numbers with a new halo model of the galaxy-matter bispectrum for galaxy-galaxy-galaxy lensing

Halo models and halo occupation distributions (HODs) are important tools to model the galaxy and matter distribution. We present and assess a new method for constraining the parameters of HODs using the gravitational lensing shear around galaxy pairs, galaxy-galaxy-galaxy-lensing (G3L). In contrast to galaxy-galaxy-lensing, G3L is sensitive to correlations between the per-halo numbers of galaxies from different populations. We use G3L to probe these correlations and test the default hypothesis that they are negligible. We derive a halo model for G3L and validate it with realistic mock data from the Millennium Simulation and a semi-analytic galaxy model. Then, we analyse public data from the Kilo-Degree Survey (KiDS), the VISTA Infrared Kilo-Degree Galaxy Survey (VIKING) and data from the Galaxy And Mass Assembly Survey (GAMA) to infer the HODs of galaxies at $z<0.5$ in five different stellar mass bins between $10^{8.5}h^{-2} M_\odot$ and $10^{11.5}h^{-2} M_\odot$ and two colours (red and blue), as well as correlations between satellite numbers. The analysis recovers the true HODs in the simulated data within the $68\%$ credibility range. The inferred HODs vary significantly with colour and stellar mass. There is also strong evidence ($>3\sigma$) for correlations, increasing with halo mass, between the numbers of red and blue satellites and galaxies with stellar masses below $10^{10} \Msun. Possible causes of these correlations are the selection of similar galaxies in different samples, the survey flux limit, or physical mechanisms like a fixed ratio between the satellite numbers of distinct populations. The decorrelation for halos with smaller masses is probably an effect of shot noise by low-occupancy halos. The inferred HODs can be used to complement galaxy-galaxy-lensing or galaxy clustering HOD studies or as input to cosmological analyses and improved mock galaxy catalogues.Comment: 20 pages + Appendix, 14 Figures. Submitted to Astronomy & Astrophysics. Abstract is abridge

KiDS-1000 cosmology: Combined second- and third-order shear statistics

This paper performs the first cosmological parameter analysis of the KiDS-1000 data with second- and third-order shear statistics. This work builds on a series of papers that describe the roadmap to third-order shear statistics. We derive and test a combined model of the second-order shear statistic, namely the COSEBIs and the third-order aperture mass statistics $\langle M_\mathrm{ap}^3\rangle$ in a tomographic set-up. We validate our pipeline with $N$-body simulations that mock the fourth Kilo Degree survey data release. To model the second- and third-order statistics, we use the latest version of \textsc{HMcode2020} for the power spectrum and \textsc{BiHalofit} for the bispectrum. Furthermore, we use an analytic description to model intrinsic alignments and hydro-dynamical simulations to model the effect of baryonic feedback processes. Lastly, we decreased the dimension of the data vector significantly by considering for the $\langle M_\mathrm{ap}^3\rangle$ part of the data vector only equal smoothing radii, making a data analysis of the fourth Kilo Degree survey data release using a combined analysis of COSEBIs third-order shear statistic possible. We first validate the accuracy of our modelling by analysing a noise-free mock data vector assuming the KiDS-1000 error budget, finding a shift in the maximum-a-posterior of the matter density parameter $\Delta \Omega_m< 0.02\, \sigma_{\Omega_m}$ and of the structure growth parameter $\Delta S_8 < 0.05\, \sigma_{S_8}$. Lastly, we performed the first KiDS-1000 cosmological analysis using a combined analysis of second- and third-order shear statistics, where we constrained $\Omega_m=0.248^{+0.062}_{-0.055}$ and $S_8=\sigma_8\sqrt{\Omega_m/0.3}=0.772\pm0.022$. The geometric average on the errors of $\Omega_\mathrm{m}$ and $S_8$ of the combined statistics increased compared to the second-order statistic by 2.2.Comment: 19 pages, 15 figures. Updated version with arXiv ID of our companion paper Porth et at. 202

KiDS+VIKING+GAMA:Testing semi-analytic models of galaxy evolution with galaxy-galaxy-galaxy lensing

Several semi-analytic models (SAMs) try to explain how galaxies form, evolve and interact inside the dark matter large-scale structure. These SAMs can be tested by comparing their predictions for galaxy-galaxy-galaxy-lensing (G3L), which is weak gravitational lensing around galaxy pairs, with observations. We evaluate the SAMs by Henriques et al. (2015; H15) and by Lagos et al. (2012; L12), implemented in the Millennium Run, by comparing their predictions for G3L to observations at smaller scales than previous studies and also for pairs of lens galaxies from different populations. We compare the G3L signal predicted by the SAMs to measurements in the overlap of the Galaxy And Mass Assembly survey (GAMA), the Kilo-Degree Survey (KiDS), and the VISTA Kilo-degree Infrared Galaxy survey (VIKING), splitting lens galaxies into two colour and five stellar-mass samples. Using an improved G3L estimator, we measure the three-point correlation of the matter distribution for mixed lens pairs with galaxies from different samples, and unmixed lens pairs with galaxies from the same sample. Predictions by the H15 SAM agree with the observations for all colour-selected and all but one stellar-mass-selected sample with 95% confidence. Deviations occur for lenses with stellar masses below $9.5h^{-2}\mathrm{M}_\odot$ at scales below $0.2h^{-1}\mathrm{Mpc}$. Predictions by the L12 SAM for stellar-mass selected samples and red galaxies are significantly higher than observed, while the predicted signal for blue galaxy pairs is too low. The L12 SAM predicts more pairs of small stellar-mass and red galaxies than the H15 SAM and the observations, as well as fewer pairs of blue galaxies. Likely explanations are different treatments of environmental effects by the SAMs and different models of the initial mass function. We conclude that G3L provides a stringent test for models of galaxy formation and evolution.Comment: 14 pages, 8 figures, replaced with version accepted to Astronomy & Astrophysics after considering referees comment

Brad Scheuffele snowboarding at Brighton [05]

Photo of Brad Scheuffele snowboarding at Brighton, Utah, in 199

A roadmap to cosmological parameter analysis with third-order shear statistics

In this work, which is the first of a series to prepare a cosmological parameter analysis with third-order cosmic shear statistics, we model both the shear three-point correlation functions Γ(i) and the third-order aperture statistics ${{\langle{{\mathcal{M}^3_\mathrm{ap}}}\rangle}}$ from the B 

KiDS-1000 cosmology: Combined second- and third-order shear statistics

International audienceThis paper performs the first cosmological parameter analysis of the KiDS-1000 data with second- and third-order shear statistics. This work builds on a series of papers that describe the roadmap to third-order shear statistics. We derive and test a combined model of the second-order shear statistic, namely the COSEBIs and the third-order aperture mass statistics $\langle M_\mathrm{ap}^3\rangle$ in a tomographic set-up. We validate our pipeline with $N$-body simulations that mock the fourth Kilo Degree survey data release. To model the second- and third-order statistics, we use the latest version of \textsc{HMcode2020} for the power spectrum and \textsc{BiHalofit} for the bispectrum. Furthermore, we use an analytic description to model intrinsic alignments and hydro-dynamical simulations to model the effect of baryonic feedback processes. Lastly, we decreased the dimension of the data vector significantly by considering for the $\langle M_\mathrm{ap}^3\rangle$ part of the data vector only equal smoothing radii, making a data analysis of the fourth Kilo Degree survey data release using a combined analysis of COSEBIs third-order shear statistic possible. We first validate the accuracy of our modelling by analysing a noise-free mock data vector assuming the KiDS-1000 error budget, finding a shift in the maximum-a-posterior of the matter density parameter $\Delta \Omega_m< 0.02\, \sigma_{\Omega_m}$ and of the structure growth parameter $\Delta S_8 < 0.05\, \sigma_{S_8}$. Lastly, we performed the first KiDS-1000 cosmological analysis using a combined analysis of second- and third-order shear statistics, where we constrained $\Omega_m=0.248^{+0.062}_{-0.055}$ and $S_8=\sigma_8\sqrt{\Omega_m/0.3}=0.772\pm0.022$. The geometric average on the errors of $\Omega_\mathrm{m}$ and $S_8$ of the combined statistics increased compared to the second-order statistic by 2.2