arXiv subjects

Joachim Harnois-Déraps

Publications and source records attributed to Joachim Harnois-Déraps.

At least 37 records · Page 2Linked to original sources

arXiv2022

Cosmological forecasts with the clustering of weak lensing peaks

Maximising the information that can be extracted from weak lensing measurements is a key goal for upcoming surveys such as LSST and Euclid. This is typically achieved through statistics that are complementary to the cosmic shear two-point correlation function, the most well established of which is the weak lensing peak abundance. In this work, we study the clustering of weak lensing peaks, and present parameter constraint forecasts for an LSST-like survey. We use the cosmoslics $w$CDM simulations to measure the peak two-point correlation function for a range of cosmological parameters, and use the simulation data to train a Gaussian process regression emulator which is applied to generate likelihood contours and provide parameter constraint forecasts from mock observations. We investigate the dependence of the peak two-point correlation function on the peak height, and find that the clustering of low amplitude peaks is complementary to that of high amplitude peaks. Consequently, their combination gives significantly tighter constraints than the clustering of high peaks alone. The peak two-point correlation function is significantly more sensitive to the cosmological parameters $h$ and $w_0$ than the peak abundance, and when the probes are combined, constraints on $Ω_{\rm m}$, $S_8$, $h$ and $w_0$ improve by at least a factor of two, relative to the peak abundance alone. Finally, we compare the forecasts for weak lensing peaks and weak lensing voids, and show that the two are also complementary; both probes can offer better constraints on $S_8$ and $w_0$ than the shear correlation function by roughly a factor of two.

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arXiv2022

Persistent homology in cosmic shear II: A tomographic analysis of DES-Y1

We demonstrate how to use persistent homology for cosmological parameter inference in a tomographic cosmic shear survey. We obtain the first cosmological parameter constraints from persistent homology by applying our method to the first-year data of the Dark Energy Survey. To obtain these constraints, we analyse the topological structure of the matter distribution by extracting persistence diagrams from signal-to-noise maps of aperture masses. This presents a natural extension to the widely used peak count statistics. Extracting the persistence diagrams from the cosmo-SLICS, a suite of $N$-body simulations with variable cosmological parameters, we interpolate the signal using Gaussian Processes and marginalise over the most relevant systematic effects, including intrinsic alignments and baryonic effects. We find for the structure growth parameter $S_8=0.747^{+0.025}_{-0.031}$, which is in full agreement with other late-time probes. We also constrain the intrinsic alignment parameter to $A=1.54\pm 0.52$, ruling out the case of no intrinsic alignments at a $3σ$-level.

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arXiv2022

Cosmic shear beyond 2-point statistics: Accounting for galaxy intrinsic alignment with projected tidal fields

Developing analysis pipelines based on statistics beyond two-point functions is critical for extracting a maximal amount of cosmological information from current and upcoming weak lensing surveys. In this paper, we study the impact of the intrinsic alignment of galaxies (IA) on three promising probes measured from aperture mass maps -- the lensing peaks, minima and full PDF, in comparison and in combination with the shear two-point correlation functions ($γ$-2PCFs). Our two-dimensional IA infusion method converts the light-cone-projected mass sheets into projected tidal tensors, which are then linearly coupled to an intrinsic ellipticity component with a strength controlled by the coupling parameter $A_{\rm IA}$. We validate our method with the $γ$-2PCFs statistics, recovering well the analytical calculations from the linear alignment model of Bridle \& King in a full tomographic setting, and for different $A_{\rm IA}$ values. We next use our method to infuse at the galaxy catalogue level a non-linear IA model that includes the density-weighting term introduced in \citet{Blazek2015}, and compute the impact on the three aperture mass map statistics. We find that large \snr peaks are maximally affected, with deviations reaching 30\% (10\%) for a {\it Euclid}-like (KiDS-like) survey. Modelling the signal in a $w$CDM cosmology universe with $N$-body simulations, we forecast the cosmological bias caused by unmodelled IA for 100 deg$^2$ of {\it Euclid}-like data, finding very large offsets in $w_0$ (5-10$σ_{\rm stat}$), $Ω_{\rm m}$ (4-6$σ_{\rm stat}$), and $S_8 \equiv σ_8\sqrt{Ω_{\rm m}/0.3}$ ($\sim$3$σ_{\rm stat}$). The method presented in this paper offers a compelling avenue to account for IA in beyond-two-point weak lensing statistics, with a flexibility comparable to that of current $γ$-2PCFs IA analytical models.

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arXiv2021

On cosmological bias due to the magnification of shear and position samples in modern weak lensing analyses

The magnification of galaxies in modern galaxy surveys induces additional correlations in the cosmic shear, galaxy-galaxy lensing and clustering observables used in modern lensing "3x2pt" analyses, due to sample selection. In this paper, we emulate the magnification contribution to all three observables utilising the SLICS simulations suite, and test the sensitivity of the cosmological model, galaxy bias and redshift distribution calibration to un-modelled magnification in a Stage-IV-like survey using Monte-Carlo sampling. We find that magnification cannot be ignored in any single or combined observable, with magnification inducing $>1σ$ biases in the $w_0-σ_8$ plane, including for cosmic shear and 3x2pt analyses. Significant cosmological biases exist in the 3x2pt and cosmic shear from magnification of the shear sample alone. We show that magnification induces significant biases in the mean of the redshift distribution where a position sample is analysed, which may potentially be used to identify contamination by magnification.

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arXiv2021

FORGE -- the f(R) gravity cosmic emulator project I: Introduction and matter power spectrum emulator

We present a large suite of cosmological simulations, the FORGE (F-of-R Gravity Emulator) simulation suite, which is designed to build accurate emulators for cosmological observables in galaxy clustering, weak gravitational lensing and galaxy clusters, for the $f(R)$ gravity model. The total of 200 simulations explore the cosmological parameter space around the Planck(2018) cosmology with a Latin hypercube, for 50 combinations of $\bar{f}_{R0}$, $Ω_m$, $σ_8$ and $h$ with all other parameters fixed. For each parameter combination, or node, we ran four independent simulations, one pair using $1024^3$ particles in $500 h^{-1} Mpc$ simulation boxes to cover small scales, and another pair using $512^3$ simulation particles in $1500 h^{-1} Mpc$ boxes for larger scales. Each pair of initial conditions are selected such that sample variance on large scales is minimised on average. In this work we present an accurate emulator for the matter power spectrum in $f(R)$ gravity trained on FORGE. We have verified, using the cross-validation technique, that the emulator accuracy is better than $2.5\%$ for the majority of nodes, particularly around the center of the explored parameter space, up to scales of $k = 10 h Mpc^{-1}$. We have also checked the power spectrum emulator against simulations which are not part of our training set and found excellent agreement. Due to its high accuracy on small scales, the FORGE matter power spectrum emulator is well suited for weak lensing analysis and can play a key tool in constraining $f(R)$ gravity using current and future observational data.

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arXiv2021

Constraining cosmology with weak lensing voids

Upcoming surveys such as \LSST{} and \Euclid{} will significantly improve the power of weak lensing as a cosmological probe. To maximise the information that can be extracted from these surveys, it is important to explore novel statistics that complement standard weak lensing statistics such as the shear-shear correlation function and peak counts. In this work, we use a recently proposed weak lensing observable -- weak lensing voids -- to make parameter constraint forecasts for an LSST-like survey. We use the \cosmoslics{} $w$CDM simulation suite to measure void statistics as a function of cosmological parameters. The simulation data is used to train a Gaussian process regression emulator that we use to generate likelihood contours and provide parameter constraints from mock observations. We find that the void abundance is more constraining than the tangential shear profiles, though the combination of the two gives additional constraining power. We forecast that without tomographic decomposition, these void statistics can constrain the matter fluctuation amplitude, $S_8$ within 0.3\% (68\% confidence interval), while offering 1.5, 1.5 and 2.7\% precision on the matter density parameter, $Ω_{\rm m}$, the reduced Hubble constant, $h$, and the dark energy equation of state parameter, $w_0$, respectively. These results are tighter than the constraints from the shear-shear correlation function with the same observational specifications for $Ω_m$, $S_8$ and $w_0$. The constraints from the WL voids also have complementary parameter degeneracy directions to the shear 2PCF for all combinations of parameters that include $h$, making weak lensing void statistics a promising cosmological probe.

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arXiv2021

Cosmic Shear Cosmology Beyond 2-Point Statistics: A Combined Peak Count and Correlation Function Analysis of DES-Y1

We constrain cosmological parameters from a joint cosmic shear analysis of peak-counts and the two-point shear correlation functions, as measured from the Dark Energy Survey (DES-Y1). We find the structure growth parameter $S_8\equiv σ_8\sqrt{Ω_{\rm m}/0.3} = 0.766^{+0.033}_{-0.038}$, which at 4.8% precision, provides one of the tightest constraints on $S_8$ from the DES-Y1 weak lensing data. In our simulation-based method we determine the expected DES-Y1 peak-count signal for a range of cosmologies sampled in four $w$CDM parameters ($Ω_{\rm m}$, $σ_8$, $h$, $w_0$). We also determine the joint covariance matrix with over 1000 realisations at our fiducial cosmology. With mock DES-Y1 data we calibrate the impact of photometric redshift and shear calibration uncertainty on the peak-count, marginalising over these uncertainties in our cosmological analysis. Using dedicated training samples we show that our measurements are unaffected by mass resolution limits in the simulation, and that our constraints are robust against uncertainty in the effect of baryon feedback. Accurate modelling for the impact of intrinsic alignments on the tomographic peak-count remains a challenge, currently limiting our exploitation of cross-correlated peak counts between high and low redshift bins. We demonstrate that once calibrated, a fully tomographic joint peak-count and correlation functions analysis has the potential to reach a 3% precision on $S_8$ for DES-Y1. Our methodology can be adopted to model any statistic that is sensitive to the non-Gaussian information encoded in the shear field. In order to accelerate the development of these beyond-two-point cosmic shear studies, our simulations are made available to the community upon request.

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arXiv2021

AMICO galaxy clusters in KiDS-DR3: cosmological constraints from large-scale stacked weak lensing profiles

Context. The large-scale mass distribution around dark matter haloes hosting galaxy clusters provides sensitive cosmological information. Aims. In this work, we make use of a large photometric galaxy cluster sample, constructed from the public Third Data Release of the Kilo-Degree Survey, and the corresponding shear signal, to assess cluster masses and test the concordance $Λ$-cold dark matter ($Λ$CDM) model. In particular, we study the weak gravitational lensing effects on scales beyond the cluster virial radius, where the signal is dominated by correlated and uncorrelated matter density distributions along the line-of-sight. The analysed catalogue consists of 6962 galaxy clusters, in the redshift range $0.1 \leq z \leq 0.6$ and with signal-to-noise ratio larger than 3.5. Methods. We perform a full Bayesian analysis to model the stacked shear profiles of these clusters. The adopted likelihood function considers both the small-scale 1-halo term, used primarily to constrain the cluster structural properties, and the 2-halo term, that can be used to constrain cosmological parameters. Results. We find that the adopted modelling is successful to assess both the cluster masses and the total matter density parameter, $Ω_M$, when fitting shear profiles up to the largest available scales of 35 Mpc/h. Moreover, our results provide a strong observational evidence of the 2-halo signal in the stacked gravitational lensing of galaxy clusters, further demonstrating the reliability of this probe for cosmological studies. The main result of this work is a robust constraint on $Ω_M$, assuming a flat $Λ$CDM cosmology. We get $Ω_M = 0.29 \pm 0.02$, estimated from the full posterior probability distribution, consistent with the estimates from cosmic microwave background experiments.

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arXiv2021

Impact of baryons in cosmic shear analyses with tomographic aperture mass statistics

NonGaussian cosmic shear statistics based on weak-lensing aperture mass ($M_{\rm ap}$) maps can outperform the classical shear two-point correlation function ($γ$-2PCF) in terms of cosmological constraining power. However, reaching the full potential of these new estimators requires accurate modeling of the physics of baryons as the extra nonGaussian information mostly resides at small scales. We present one such modeling based on the Magneticum hydrodynamical simulation for the KiDS-450 and DES-Y1 surveys and a Euclid-like survey. We compute the bias due to baryons on the lensing PDF and the distribution of peaks and voids in $M_{\rm ap}$ maps and propagate it to the cosmological forecasts on the structure growth parameter $S_8$, the matter density parameter $Ω_{\rm m}$, and the dark energy equation of state $w_0$ using the SLICS and cosmo-SLICS sets of dark-matter-only simulations. We report a negative bias of a few percent on $S_8$ and $Ω_{\rm m}$ and also measure a positive bias of the same level on $w_0$ when including a tomographic decomposition. These biases reach $\sim 5$% when combining $M_{\rm ap}$ statistics with the $γ$-2PCF as these estimators show similar dependency on the AGN feedback. We verify that these biases constitute a less than $1σ$ shift on the probed cosmological parameters for current cosmic shear surveys. However, baryons need to be accounted for at the percentage level for future Stage IV surveys and we propose to include the uncertainty on the AGN feedback amplitude by marginalizing over this parameter using multiple simulations such as those presented in this paper. Finally, we explore the possibility of mitigating the impact of baryons by filtering the $M_{\rm ap}$ map but find that this process would require to suppress the small-scale information to a point where the constraints would no longer be competitive.

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arXiv2021

Probing dark energy with tomographic weak-lensing aperture mass statistics

We forecast and optimize the cosmological power of various weak-lensing aperture mass ($M_{\rm ap}$) map statistics for future cosmic shear surveys, including peaks, voids, and the full distribution of pixels (1D $M_{\rm ap}$). These alternative methods probe the non-Gaussian regime of the matter distribution, adding complementary cosmological information to the classical two-point estimators. Based on the SLICS and cosmo-SLICS $N$-body simulations, we build Euclid-like mocks to explore the $S_8 - Ω_{\rm m} - w_0$ parameter space. We develop a new tomographic formalism which exploits the cross-information between redshift slices (cross-$M_{\rm ap}$) in addition to the information from individual slices (auto-$M_{\rm ap}$) probed in the standard approach. Our auto-$M_{\rm ap}$ forecast precision is in good agreement with the recent literature on weak-lensing peak statistics, and is improved by $\sim 50$% when including cross-$M_{\rm ap}$. It is further boosted by the use of 1D $M_{\rm ap}$ that outperforms all other estimators, including the shear two-point correlation function ($γ$-2PCF). When considering all tomographic terms, our uncertainty range on the structure growth parameter $S_8$ is enhanced by $\sim 45$% (almost twice better) when combining 1D $M_{\rm ap}$ and the $γ$-2PCF compared to the $γ$-2PCF alone. We additionally measure the first combined forecasts on the dark energy equation of state $w_0$, finding a factor of three reduction of the statistical error compared to the $γ$-2PCF alone. This demonstrates that the complementary cosmological information explored by non-Gaussian $M_{\rm ap}$ map statistics not only offers the potential to improve the constraints on the recent $σ_8$ - $Ω_{\rm m}$ tension, but also constitutes an avenue to understand the accelerated expansion of our Universe.

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arXiv2020

Strong detection of the CMB lensingxgalaxy weak lensingcross-correlation from ACT-DR4,PlanckLegacy and KiDS-1000

We measure the cross-correlation between galaxy weak lensing data from the Kilo Degree Survey (KiDS-1000, DR4) and cosmic microwave background (CMB) lensing data from the Atacama Cosmology Telescope (ACT, DR4) and the Planck Legacy survey. We use two samples of source galaxies, selected with photometric redshifts, $(0.1<z_{\rm B}<1.2)$ and $(1.2<z_{\rm B}<2)$, which produce a combined detection significance of the CMB lensing/weak galaxy lensing cross-spectrum of $7.7σ$. With the lower redshift galaxy sample, for which the cross-correlation is detected at a significance of $5.3σ$, we present joint cosmological constraints on the matter density parameter, $Ω_{\rm m}$, and the matter fluctuation amplitude parameter, $σ_8$, marginalising over three nuisance parameters that model our uncertainty in the redshift and shear calibration, and the intrinsic alignment of galaxies. We find our measurement to be consistent with the best-fitting flat $Λ$CDM cosmological models from both Planck and KiDS-1000. We demonstrate the capacity of CMB-weak lensing cross-correlations to set constraints on either the redshift or shear calibration, by analysing a previously unused high-redshift KiDS galaxy sample $(1.2<z_{\rm B}<2)$, with the cross-correlation detected at a significance of $7σ$. This analysis provides an independent assessment for the accuracy of redshift measurements in a regime that is challenging to calibrate directly owing to known incompleteness in spectroscopic surveys.

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arXiv2020

Non-Gaussianity in the Weak Lensing Correlation Function Likelihood -- Implications for Cosmological Parameter Biases

We study the significance of non-Gaussianity in the likelihood of weak lensing shear two-point correlation functions, detecting significantly non-zero skewness and kurtosis in one-dimensional marginal distributions of shear two-point correlation functions in simulated weak lensing data. We examine the implications in the context of future surveys, in particular LSST, with derivations of how the non-Gaussianity scales with survey area. We show that there is no significant bias in one-dimensional posteriors of $Ω_{\rm m}$ and $σ_{\rm 8}$ due to the non-Gaussian likelihood distributions of shear correlations functions using the mock data ($100$ deg$^{2}$). We also present a systematic approach to constructing approximate multivariate likelihoods with one-dimensional parametric functions by assuming independence or more flexible non-parametric multivariate methods after decorrelating the data points using principal component analysis (PCA). While the use of PCA does not modify the non-Gaussianity of the multivariate likelihood, we find empirically that the one-dimensional marginal sampling distributions of the PCA components exhibit less skewness and kurtosis than the original shear correlation functions.Modeling the likelihood with marginal parametric functions based on the assumption of independence between PCA components thus gives a lower limit for the biases. We further demonstrate that the difference in cosmological parameter constraints between the multivariate Gaussian likelihood model and more complex non-Gaussian likelihood models would be even smaller for an LSST-like survey. In addition, the PCA approach automatically serves as a data compression method, enabling the retention of the majority of the cosmological information while reducing the dimensionality of the data vector by a factor of $\sim$5.

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arXiv2020

Persistent homology in cosmic shear: constraining parameters with topological data analysis

In recent years, cosmic shear has emerged as a powerful tool to study the statistical distribution of matter in our Universe. Apart from the standard two-point correlation functions, several alternative methods like peak count statistics offer competitive results. Here we show that persistent homology, a tool from topological data analysis, can extract more cosmological information than previous methods from the same dataset. For this, we use persistent Betti numbers to efficiently summarise the full topological structure of weak lensing aperture mass maps. This method can be seen as an extension of the peak count statistics, in which we additionally capture information about the environment surrounding the maxima. We first demonstrate the performance in a mock analysis of the KiDS+VIKING-450 data: we extract the Betti functions from a suite of $w$CDM $N$-body simulations and use these to train a Gaussian process emulator that provides rapid model predictions; we next run a Markov-Chain Monte Carlo analysis on independent mock data to infer the cosmological parameters and their uncertainty. When comparing our results, we recover the input cosmology and achieve a constraining power on $S_8 \equiv σ_8\sqrt{Ω_\mathrm{m}/0.3}$ that is 5% tighter than that of peak count statistics. Performing the same analysis on 100 deg$^2$ of Euclid-like simulations, we are able to improve the constraints on $S_8$ and $Ω_\mathrm{m}$ by 18% and 10%, respectively, while breaking some of the degeneracy between $S_8$ and the dark energy equation of state. To our knowledge, the methods presented here are the most powerful topological tools to constrain cosmological parameters with lensing data.

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arXiv2019

Painting with baryons: augmenting N-body simulations with gas using deep generative models

Running hydrodynamical simulations to produce mock data of large-scale structure and baryonic probes, such as the thermal Sunyaev-Zeldovich (tSZ) effect, at cosmological scales is computationally challenging. We propose to leverage the expressive power of deep generative models to find an effective description of the large-scale gas distribution and temperature. We train two deep generative models, a variational auto-encoder and a generative adversarial network, on pairs of matter density and pressure slices from the BAHAMAS hydrodynamical simulation. The trained models are able to successfully map matter density to the corresponding gas pressure. We then apply the trained models on 100 lines-of-sight from SLICS, a suite of N-body simulations optimised for weak lensing covariance estimation, to generate maps of the tSZ effect. The generated tSZ maps are found to be statistically consistent with those from BAHAMAS. We conclude by considering a specific observable, the angular cross-power spectrum between the weak lensing convergence and the tSZ effect and its variance, where we find excellent agreement between the predictions from BAHAMAS and SLICS, thus enabling the use of SLICS for tSZ covariance estimation.

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arXiv2019

A gravitational lensing detection of filamentary structures connecting luminous red galaxies

We present a weak lensing detection of filamentary structures in the cosmic web, combining data from the Kilo-Degree Survey, the Red Cluster Sequence Lensing Survey and the Canada-France-Hawaii Telescope Lensing Survey. The line connecting luminous red galaxies with a separation of $3 - 5\, h^{-1}\text{Mpc}$ is chosen as a proxy for the location of filaments. We measure the average weak lensing shear around $\sim$11,000 candidate filaments selected in this way from the Sloan Digital Sky Survey. After nulling the shear induced by the dark matter haloes around each galaxy, we report a $3.4\,σ$ detection of an anisotropic shear signal from the matter that connects them. Adopting a filament density profile, motivated from $N$-body simulations, the average density at the centre of these filamentary structures is found to be $15 \pm 4$ times the critical density.

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arXiv2019

Studying galaxy troughs and ridges using Weak Gravitational Lensing with the Kilo-Degree Survey

We study projected underdensities in the cosmic galaxy density field known as 'troughs', and their overdense counterparts, which we call 'ridges'. We identify these regions using a bright sample of foreground galaxies from the photometric Kilo-Degree Survey (KiDS), specifically selected to mimic the spectroscopic Galaxy And Mass Assembly survey (GAMA). Using background galaxies from KiDS, we measure the weak gravitational lensing profiles of the troughs/ridges. We quantify the amplitude of their lensing strength $A$ as a function of galaxy density percentile rank $P$ and galaxy overdensity $δ$, and find that the skewness in the galaxy density distribution is reflected in the total mass distribution measured by weak lensing. We interpret our results using the mock galaxy catalogue from the Marenostrum Institut de Ciències de l'Espai (MICE) simulation, and find a good agreement with our observations. Using signal-to-noise weights derived from the Scinet LIghtCone Simulations (SLICS) mock catalogue we optimally stack the lensing signal of KiDS troughs with an angular radius $θ_A$ = {5,10,15,20} arcmin, resulting in {16.8,14.9,10.13,7.55} $σ$ detections. Finally, we select troughs using a volume-limited sample of galaxies, split into two redshift bins between 0.1 < z < 0.3. For troughs/ridges with transverse comoving radius $R_A$ = 1.9 Mpc/h, we find no significant difference in the comoving Excess Surface Density as a function of $P$ and $δ$ between the low- and high-redshift sample. Using the MICE and SLICS mocks we predict that trough and ridge evolution could be detected with gravitational lensing using deeper and wider lensing surveys, such as those from the Large Synoptic Survey Telescope and Euclid.

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arXiv2018

KiDS-450: Enhancing cosmic shear with clipping transformations

We present the first "clipped" cosmic shear measurement using data from the Kilo-Degree Survey (KiDS-450). "Clipping" transformations suppress the signal from the highest density, non-linear regions of cosmological fields. We demonstrate that these transformations improve constraints on $S_8=σ_8(Ω_{\rm{m}}/0.3)^{0.5}$ when used in combination with conventional two-point statistics. For the KiDS-450 data, we find that the combined measurements improve the constraints on $S_8$ by 17%, compared to shear correlation functions alone. We determine the expectation value of the clipped shear correlation function using a suite of numerical simulations, and develop methodology to mitigate the impact of masking and shot noise. Future improvements in numerical simulations and mass reconstruction methodology will permit the precise calibration of clipped cosmic shear statistics such that clipping can become a standard tool in weak lensing analyses.

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arXiv2018

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

We present cosmological parameter constraints from a joint analysis of three cosmological probes: the tomographic cosmic shear signal in $\sim$450 deg$^2$ of data from the Kilo Degree Survey (KiDS), the galaxy-matter cross-correlation signal of galaxies from the Galaxies And Mass Assembly (GAMA) survey determined with KiDS weak lensing, and the angular correlation function of the same GAMA galaxies. We use fast power spectrum estimators that are based on simple integrals over the real-space correlation functions, and show that they are practically unbiased over relevant angular frequency ranges. We test our full pipeline on numerical simulations that are tailored to KiDS and retrieve the input cosmology. By fitting different combinations of power spectra, we demonstrate that the three probes are internally consistent. For all probes combined, we obtain $S_8\equiv σ_8 \sqrt{Ω_{\rm m}/0.3}=0.800_{-0.027}^{+0.029}$, consistent with Planck and the fiducial KiDS-450 cosmic shear correlation function results. Marginalising over wide priors on the mean of the tomographic redshift distributions yields consistent results for $S_8$ with an increase of $28\%$ in the error. The combination of probes results in a $26\%$ reduction in uncertainties of $S_8$ over using the cosmic shear power spectra alone. The main gain from these additional probes comes through their constraining power on nuisance parameters, such as the galaxy intrinsic alignment amplitude or potential shifts in the redshift distributions, which are up to a factor of two better constrained compared to using cosmic shear alone, demonstrating the value of large-scale structure probe combination.

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