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It is well established that maximizing the information extracted from upcoming and ongoing stage-IV weak-lensing surveys requires higher-order summary statistics that complement the standard two-point statistics. In this work, we focus on weak-lensing peak statistics to test two popular modified gravity models, $f(R)$ and nDGP, using the FORGE and BRIDGE weak-lensing simulations, respectively. From these simulations we measure the peak statistics as a function of both cosmological and modified gravity parameters simultaneously. Our findings indicate that the peak abundance is sensitive to the strength of modified gravity, while the peak two-point correlation function is sensitive to the nature of the screening mechanism in a modified gravity model. We combine these simulated statistics with a Gaussian Process Regression emulator and a Gaussian likelihood to generate stage-IV forecast posterior distributions for the modified gravity models. We demonstrate that, assuming small scales can be correctly modelled, peak statistics can be used to distinguish GR from $f(R)$ and nDGP models at the two-sigma level with a stage-IV survey area of $300 \, \rm{deg}^2$ and $1000 \, \rm{deg}^2$, respectively. Finally, we show that peak statistics can constrain $\log_{10}\left(|f_{R0}|\right) = -6$ to 2\% precision, and $\log_{10}(H_0 r_c) = 0.5$ to 25\% precision., Comment: 25 pages, 16 figures

We analyse the fourth data release of the Kilo Degree Survey (KiDS-1000) and extract cosmological parameter constraints based on the cosmic shear peak count statistics. Peaks are identified in aperture mass maps in which the filter is maximally sensitive to angular scales in the range 2-4arcmin, probing deep into the non-linear regime of structure formation. We interpret our results with a simulation-based inference pipeline, sampling over a broad $w$CDM prior volume and marginalising over uncertainties on shape calibration, photometric redshift distribution, intrinsic alignment and baryonic feedback. Our measurements constrain the structure growth parameter and the amplitude of the non-linear intrinsic alignment model to $\Sigma_8 \equiv \sigma_8\left[\Omega_{\rm m}/0.3\right]^{0.60}=0.765^{+0.030}_{-0.030}$ and $A_{\rm IA}= 0.71^{+0.42}_{-0.42}$, respectively, in agreement with previous KiDS-1000 results based on two-point shear statistics. These results are robust against modelling of the non-linear physics, different scale cuts and selections of tomographic bins. The posterior is also consistent with that from the Dark Energy Survey Year-1 peak count analysis presented in Harnois-D\'eraps et al (2021), and hence we jointly analyse both surveys. We obtain $\Sigma_8^{\rm joint} \equiv \sigma_8\left[\Omega_{\rm m}/0.3\right]^{0.57}=0.759^{+0.020}_{-0.017}$, in agreement with the Planck $w$CDM results. The shear-CMB tension on this parameter increases to $3.1\sigma$ when forcing $w=-1.0$, and to $4.1\sigma$ if comparing instead with $S_{8,\Lambda{\rm CDM}}^{\rm joint} = 0.736^{+0.016}_{-0.018}$, one of the tightest constraints to date on this quantity. (abridged), Comment: 25 pages, 20 figures. comments welcome

In this work, we demonstrate the constraining power of the tomographic weak lensing convergence PDF for StageIV-like source galaxy redshift bins and shape noise. We focus on scales of $10$ to $20$ arcmin in the mildly nonlinear regime, where the convergence PDF and its changes with cosmological parameters can be predicted theoretically. We model the impact of reconstructing the convergence from the shear field using the well-known Kaiser-Squires formalism. We cross-validate the predicted and the measured convergence PDF derived from convergence maps reconstructed using simulated shear catalogues. Employing a Fisher forecast, we determine the constraining power for $(\Omega_{m},S_{8},w_{0})$. We find that adding a 5-bin tomography improves the $\kappa-$PDF constraints by a factor of $\{3.8,1.3,1.6\}$ for $(\Omega_{m}, S_{8},w_{0})$ respectively. Additionally, we perform a joint analysis with the shear two-point correlation functions, finding an enhancement of around a factor of $1.5$ on all parameters with respect to the two-point statistics alone. These improved constraints come from disentangling $\Omega_{\rm m}$ from $w_0$ by extracting non-Gaussian information, in particular, including the PDF skewness at different redshift bins. We also study the effect of varying the number of parameters to forecast, in particular we add $h$, finding that the convergence PDF maintains its constraining power while the precision from two-point correlations degrades by a factor of $\{1.7,1.4,1.8\}$ for $\{\Omega_{\rm m},S_8,w_0\}$, respectively., Comment: 23 pages, 21 figures

In the context of cosmological weak lensing studies, intrinsic alignments (IAs) are one the most complicated astrophysical systematic to model, given the poor understanding of the physical processes that cause them. A number of modelling frameworks for IAs have been proposed in the literature, both purely phenomenological or grounded on a perturbative treatment of symmetry-based arguments. However, the accuracy with which any of these approaches is able to describe the impact of IAs on cosmic shear data, particularly on the comparatively small scales ($k\simeq 1\,{\rm Mpc}^{-1}$) to which this observable is sensitive, is not clear. Here we quantify the level of disagreement between the true underlying intrinsic alignments and the theoretical model used to describe them that can be allowed in the context of cosmic shear analyses with future Stage-IV surveys. We consider various models describing this "IA residual", covering both physics-based approaches, as well as completely agnostic prescriptions. The same qualitative results are recovered in all cases explored: for a Stage-IV cosmic shear survey, a mis-modelling of the IA contribution at the $\sim10\%$ level produces shifts of $\lesssim0.5\sigma$ on the final cosmological parameter constraints. Current and future IA models should therefore aim to achieve this level of accuracy, a prospect that is not unfeasible for models with sufficient flexibility.

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

We present cosmological constraints derived from peak counts, minimum counts, and the angular power spectrum of the Subaru Hyper Suprime-Cam first-year (HSC Y1) weak lensing shear catalog. Weak lensing peak and minimum counts contain non-Gaussian information and hence are complementary to the conventional two-point statistics in constraining cosmology. In this work, we forward-model the three summary statistics and their dependence on cosmology, using a suite of $N$-body simulations tailored to the HSC Y1 data. We investigate systematic and astrophysical effects including intrinsic alignments, baryon feedback, multiplicative bias, and photometric redshift uncertainties. We mitigate the impact of these systematics by applying cuts on angular scales, smoothing scales, statistic bins, and tomographic redshift bins. By combining peaks, minima, and the power spectrum, assuming a flat-$\Lambda$CDM model, we obtain $S_{8} \equiv \sigma_8\sqrt{\Omega_m/0.3}= 0.810^{+0.022}_{-0.026}$, a 35\% tighter constraint than that obtained from the angular power spectrum alone. Our results are in agreement with other studies using HSC weak lensing shear data, as well as with Planck 2018 cosmology and recent CMB lensing constraints from the Atacama Cosmology Telescope and the South Pole Telescope.

We present the Differentiable Lensing Lightcone (DLL), a fully differentiable physical model designed for being used as a forward model in Bayesian inference algorithms requiring access to derivatives of lensing observables with respect to cosmological parameters. We extend the public FlowPM N-body code, a particle-mesh N-body solver, simulating lensing lightcones and implementing the Born approximation in the Tensorflow framework. Furthermore, DLL is aimed at achieving high accuracy with low computational costs. As such, it integrates a novel Hybrid Physical-Neural parameterisation able to compensate for the small-scale approximations resulting from particle-mesh schemes for cosmological N-body simulations. We validate our simulations in an LSST setting against high-resolution $\kappa$TNG simulations by comparing both the lensing angular power spectrum and multiscale peak counts. We demonstrate an ability to recover lensing $C_\ell$ up to a 10% accuracy at $\ell=1000$ for sources at redshift 1, with as few as $\sim 0.6$ particles per Mpc/h. As a first use case, we use this tool to investigate the relative constraining power of the angular power spectrum and peak counts statistic in an LSST setting. Such comparisons are typically very costly as they require a large number of simulations, and do not scale well with the increasing number of cosmological parameters. As opposed to forecasts based on finite differences, these statistics can be analytically differentiated with respect to cosmology, or any systematics included in the simulations at the same computational cost of the forward simulation. We find that the peak counts outperform the power spectrum on the cold dark matter parameter $\Omega_c$, on the amplitude of density fluctuations $\sigma_8$, and on the amplitude of the intrinsic alignment signal $A_{IA}$., Comment: Submitted to A&A, 18 pages, 14 figures, comments are welcome

We present a first application to photometric galaxy clustering and weak lensing of wavelet based multi-scale higher order summary statistics: starlet peak counts and starlet $\ell_1$-norm. Peak counts are the local maxima in the map and the $\ell_1$-norm is computed via the sum of the absolute values of the starlet (wavelet) decomposition coefficients of a map, providing a fast multi-scale calculation of the pixel distribution, encoding the information of all pixels in the map. We employ the cosmo-SLICS simulations sources and lenses catalogues and we compute wavelet based higher order statistics in the context of combined probes and their potential when applied to the weak lensing convergence maps and galaxy maps. We get forecasts on the matter density parameter $\Omega_{\rm m}$, the reduced Hubble constant $h$, the matter fluctuation amplitude $\sigma_8$, and the dark energy equation of state parameter $w_0$. We find that, in our setting for this first application, considering the two probes as independent, starlet peaks and the $\ell_1$-norm represent interesting summary statistics that can improve the constraints with respect to the power spectrum also in the case of photometric galaxy clustering and when the two probes are combined., Comment: A&A Letters to the Editor, Forthcoming article, accepted

We present MGLenS, a large series of modified gravity lensing simulations tailored for cosmic shear data analyses and forecasts in which cosmological and modified gravity parameters are varied simultaneously. Based on the FORGE and BRIDGE $N$-body simulation suites presented in companion papers, we construct 500,000 deg$^2$ of mock Stage-IV lensing data, sampling a pair of 4-dimensional volumes designed for the training of emulators. We validate the accuracy of MGLenS with inference analyses based on the lensing power spectrum exploiting our implementation of $f(R)$ and nDGP theoretical predictions within the cosmoSIS cosmological inference package. A Fisher analysis reveals that the vast majority of the constraining power from such a survey comes from the highest redshift galaxies alone. We further find from a full likelihood sampling that cosmic shear can achieve 95% CL constraints on the modified gravity parameters of log$_{10}\left[ f_{R_0}\right] < -5.24$ and log$_{10}\left[ H_0 r_c\right] > -0.05$, after marginalising over intrinsic alignments of galaxies and including scales up to $\ell=5000$. Such a survey setup could in fact detect with more than $3\sigma$ confidence $f(R)$ values larger than $3 \times 10^{-6}$ and $H_0 r_c$ smaller than 1.0. Scale cuts at $\ell=3000$ reduce the degeneracy breaking between $S_8$ and the modified gravity parameters, while photometric redshift uncertainty seem to play a subdominant role in our error budget. We finally explore the consequences of analysing data with the wrong gravity model, and report the catastrophic biases for a number of possible scenarios. The Stage-IV MGLenS simulations, the FORGE and BRIDGE emulators and the cosmoSIS interface modules will be made publicly available upon journal acceptance., Comment: 22 pages, 15 figures, comments welcome, simulations available upon request

We quantify the cosmological constraining power of the `lensing PDF' - the one-point probability density of weak lensing convergence maps - by modelling this statistic numerically with an emulator trained on $w$CDM cosmic shear simulations. After validating our methods on Gaussian and lognormal fields, we show that `multi-scale' PDFs - measured from maps with multiple levels of smoothing - offer considerable gains over two-point statistics, owing to their ability to extract non-Gaussian information: for a mock Stage-III survey, lensing PDFs yield 33\% tighter constraints on the clustering parameter $S_8=\sigma_8\sqrt{\Omega_{\rm m}/0.3}$ than the two-point shear correlation functions. For Stage-IV surveys, we achieve $>$90\% tighter constraints on $S_8$, but also on the Hubble and dark energy equation of state parameters. Interestingly, we find improvements when combining these two probes only in our Stage-III setup; in the Stage-IV scenario the lensing PDFs contain all information from the standard two-point statistics and more. This suggests that while these two probes are currently complementary, the lower noise levels of upcoming surveys will unleash the constraining power of the PDF., Comment: 18 pages, 9 figures, accepted for publication in MNRAS

Context. Weak lensing and clustering statistics beyond two-point functions can capture non-Gaussian information about the matter density field, thereby improving the constraints on cosmological parameters relative to the mainstream methods based on correlation functions and power spectra. Aims. This paper presents a cosmological analysis of the fourth data release of the Kilo Degree Survey based on the density split statistics, which measures the mean shear profiles around regions classified according to foreground densities. The latter is constructed from a bright galaxy sample, which we further split into red and blue samples, allowing us to probe their respective connection to the underlying dark matter density. Methods. We use the state-of-the-art model of the density splitting statistics and validate its robustness against mock data infused with known systematic effects such as intrinsic galaxy alignment and baryonic feedback. Results. After marginalising over the photometric redshift uncertainty and the residual shear calibration bias, we measure for the full KiDS-bright sample a structure growth parameter of $S_8 = \sigma_8 \sqrt{\Omega_\mathrm{m}/0.3} = 0.74^{+0.03}_{-0.02}$ that is competitive to and consistent with two-point cosmic shear results, a matter density of $\Omega_\mathrm{m} = 0.28 \pm 0.02$, and a constant galaxy bias of $b = 1.32^{+0.12}_{-0.10}$., Comment: 18 pages, 23 Figures

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 $3\sigma$-level.

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 $>1\sigma$ biases in the $w_0-\sigma_8$ 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., Comment: 17 pages, 7 figures, 3 tables. Submitted to MNRAS. Comments welcome

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 $\Omega_{\rm m}$, $S_8$, $h$ 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., Comment: 13 pages, 8 figures, comments welcome. arXiv admin note: text overlap with arXiv:2010.11954

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 $\bar{f}_{R0}$, $\Omega_m$, $\sigma_8$ 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., Comment: 15 pages, FORGE emulator code publicly available from https://bitbucket.org/arnoldcn/forge_emulator/

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 ($\gamma$-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 $\gamma$-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$\sigma_{\rm stat}$), $\Omega_{\rm m}$ (4-6$\sigma_{\rm stat}$), and $S_8 \equiv \sigma_8\sqrt{\Omega_{\rm m}/0.3}$ ($\sim$3$\sigma_{\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 $\gamma$-2PCFs IA analytical models., Comment: 21 pages, 12 figures, accepted version

Studying the statistical properties of the large-scale structure in the Universe with weak gravitational lensing is a prime goal of several current and forthcoming galaxy surveys. The power that weak lensing has to constrain cosmological parameters can be enhanced by considering statistics beyond second-order shear correlation functions or power spectra. One such higher-order probe that has proven successful in observational data is the density split statistics (DSS), in which one analyses the mean shear profiles around points that are classified according to their foreground galaxy density. In this paper, we generalise the most accurate DSS model to allow for a broad class of angular filter functions used for the classification of the different local density regions. This approach is motivated by earlier findings showing that an optimised filter can provide tighter constraints on model parameters compared to the standard top-hat case. We build on large deviation theory approaches and approximations thereof to model the matter density PDF, and on perturbative calculations of higher-order moments of the density field. The novel addition relies on the generalisation of these previously employed calculations to allow for general filter functions and is validated on several sets of numerical simulations. The revised model fits well the simulation measurements, with a residual systematic offset that is small compared to the statistical accuracy of current weak lensing surveys. The accuracy of the model is slightly lower for a compensated filter than for a non-negative filter function, and that it increases with the filter size. Using a Fisher matrix approach, we find constraints comparable to the commonly used two-point cosmic shear measures. Hence, our DSS model can be used in competitive analyses of current cosmic shear data, while it may need refinements for forthcoming lensing surveys., Comment: 21 pages, 13 figures

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 ${\Lambda}$-cold dark matter (${\Lambda}$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, ${\Omega}_M$, 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 ${\Omega}_M$, assuming a flat ${\Lambda}$CDM cosmology. We get ${\Omega}_M = 0.29 \pm 0.02$, estimated from the full posterior probability distribution, consistent with the estimates from cosmic microwave background experiments., Comment: Accepted for publication on A&A, replaced to match the final version: minor comments

NonGaussian cosmic shear statistics based on weak-lensing aperture mass ($M_{\rm ap}$) maps can outperform the classical shear two-point correlation function ($\gamma$-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 $\Omega_{\rm m}$, 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 $\Omega_{\rm m}$ 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 $\gamma$-2PCF as these estimators show similar dependency on the AGN feedback. We verify that these biases constitute a less than $1\sigma$ 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., Comment: 12 pages, 9 figures, matching the version accepted in A&A

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 $S_8\equiv \sigma_8\sqrt{\Omega_{\rm m}/0.3} = 0.766^{+0.033}_{-0.038}$, 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 ($\Omega_{\rm m}$, $\sigma_8$, $h$, $w_0$). 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., Comment: 27 pages, 23 figures, updated to MNRAS accepted version

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

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, $\Omega_{\rm m}$, 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 $\Omega_m$, $S_8$ 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., Comment: 12 pages, 8 figures, accepted by MNRAS

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 $S_8 - \Omega_{\rm m} - w_0$ 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 ($\gamma$-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 $\gamma$-2PCF compared to the $\gamma$-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 $\gamma$-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 $\sigma_8$ - $\Omega_{\rm m}$ tension, but also constitutes an avenue to understand the accelerated expansion of our Universe., Comment: Matching version accepted by A&A, 18 pages, 12 figures

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 $S_8 \equiv \sigma_8\sqrt{\Omega_\mathrm{m}/0.3}$ 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 $\Omega_\mathrm{m}$ 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.

Context. The density split statistics in weak gravitational lensing analyses probes the correlation between regions of different (foreground) galaxy number densities and their weak lensing signal, measured by the shape distortion of background galaxies. Aims. In this paper, we reconsider density split statistics, by constructing a new angular filter function that is adapted to the expected relation between galaxy number density and shear pattern, in a way that the filter weighting the galaxy number density is matched to the filter that is used to quantify the shear signal. Methods. We use the results of numerical ray-tracing simulations, specifically through Millennium Simulation supplemented by a galaxy distribution based on a semi-analytic model, to construct a matched pair of adapted filter functions for the galaxy density and the tangential shear signal. We compare the performance of our new filter to the previously used top-hat filter, applying both to a different and independent set of numerical simulations (SLICS, cosmo-SLICS). Results. We show that the adapted filter yields a better correlation between the total matter and the galaxy distribution. Furthermore, the adapted filter provides a larger signal-to-noise ratio to constrain the bias between the total matter and the galaxy distribution, and we show that it is, in general, a more sensitive discriminator between different cosmologies, with the exception of cosmologies with very large $\sigma_8$ values. All analyses lead to the conclusion that our adapted filter should be favored in future density split statistic works., Comment: 13 pages, 15 figures, accepted for publication by A&A

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 $3.4\,\sigma$ 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., Comment: 13 pages, 8 figures, accepted for publication in A&A

We analytically model the non-linear effects induced by massive neutrinos on the total matter power spectrum using the halo model reaction framework of Cataneo et al. 2019. In this approach the halo model is used to determine the relative change to the matter power spectrum caused by new physics beyond the concordance cosmology. Using standard fitting functions for the halo abundance and the halo mass-concentration relation, the total matter power spectrum in the presence of massive neutrinos is predicted to percent-level accuracy, out to $k=10 \, h \, {\rm Mpc}^{-1}$. We find that refining the prescriptions for the halo properties using $N$-body simulations improves the recovered accuracy to better than 1%. This paper serves as another demonstration for how the halo model reaction framework, in combination with a single suite of standard $\Lambda$CDM simulations, can recover percent-level accurate predictions for beyond-$\Lambda$CDM matter power spectra, well into the non-linear regime., Comment: 7 pages, 3 figures; matches MNRAS accepted version

We present here the cosmo-SLICS, a new suite of simulations specially designed for the analysis of current and upcoming weak lensing data beyond the standard two-point cosmic shear. We sample the $[\Omega_{\rm m}, \sigma_8, h, w_0]$ parameter space at 25 points organised in a Latin hyper-cube, spanning a range that contains most of the $2\sigma$ posterior distribution from ongoing lensing surveys. At each of these nodes we evolve a pair of $N$-body simulations in which the sampling variance is highly suppressed, and ray-trace the volumes 800 times to further increase the effective sky coverage. We extract a lensing covariance matrix from these pseudo-independent light-cones and show that it closely matches a brute-force construction based on an ensemble of 800 truly independent $N$-body runs. More precisely, a Fisher analysis reveals that both methods yield marginalized two-dimensional constraints that vary by less than 6% in area, a result that holds under different survey specifications and that matches to within 15% the area obtained from an analytical covariance calculation. Extending this comparison with our 25 $w$CDM models, we probe the cosmology dependence of the lensing covariance directly from numerical simulations, reproducing remarkably well the Fisher results from the analytical models at most cosmologies. We demonstrate that varying the cosmology at which the covariance matrix is evaluated in the first place might have an order of magnitude greater impact on the parameter constraints than varying the choice of covariance estimation technique. We present a test case in which we generate fast predictions for both the lensing signal and its associated variance with a flexible Gaussian process regression emulator, achieving an accuracy of a few percent on the former and 10% on the latter., Comment: 27 pages, 23 figures, A&A accepted, updated to the journal version; simulations available upon request

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 $\Omega_{\rm m}$ and $\sigma_{\rm 8}$ 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., Comment: 16 pages, 10 figures, published MNRAS

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., Comment: Comments welcome. Code and trained models can be found at https://www.github.com/tilmantroester/baryon_painter. Accepted in MNRAS Letters

We analyse three public cosmic shear surveys; the Kilo-Degree Survey (KiDS-450), the Dark Energy Survey (DES-SV) and the Canada France Hawaii Telescope Lensing Survey (CFHTLenS). Adopting the COSEBIs statistic to cleanly and completely separate the lensing E-modes from the non-lensing B-modes, we detect B-modes in KiDS-450 and CFHTLenS at the level of about 2.7 $\sigma$. For DES- SV we detect B-modes at the level of 2.8 $\sigma$ in a non-tomographic analysis, increasing to a 5.5 $\sigma$ B-mode detection in a tomographic analysis. In order to understand the origin of these detected B-modes we measure the B-mode signature of a range of different simulated systematics including PSF leakage, random but correlated PSF modelling errors, camera-based additive shear bias and photometric redshift selection bias. We show that any correlation between photometric-noise and the relative orientation of the galaxy to the point-spread-function leads to an ellipticity selection bias in tomographic analyses. This work therefore introduces a new systematic for future lensing surveys to consider. We find that the B-modes in DES-SV appear similar to a superposition of the B-mode signatures from all of the systematics simulated. The KiDS-450 and CFHTLenS B-mode measurements show features that are consistent with a repeating additive shear bias., Comment: 32 pages, 26 figures

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 $S_8=\sigma_8(\Omega_{\rm{m}}/0.3)^{0.5}$ 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., Comment: 22 pages, 17 figures. Accepted by MNRAS

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 $\delta$, 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 Ci\`encies 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 $\theta_A$ = {5,10,15,20} arcmin, resulting in {16.8,14.9,10.13,7.55} $\sigma$ 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 $\delta$ 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., Comment: 23 pages, 15 figures, 2 tables; published in MNRAS

We study the distribution of dark matter in the nonlinear regime in a model in which the primordial fluctuations include, in addition to the dominant primordial Gaussian fluctuations generated by the standard $\Lambda CDM$ cosmological model, the effects of a cosmic string wake set up at the time of equal matter and radiation, making use of cosmological $N$-body simulations. At early times the string wake leads to a planar overdensity of dark matter. We study how this non-Gaussian pattern of a cosmic string wake evolves in the presence of the Gaussian perturbations, making use of wavelet and ridgelet-like statistics specifically designed to extract string wake signals. At late times the Gaussian fluctuations disrupt the string wake. We find that for a string tension of $G \mu = 10^{-7}$, a value just below the current observational limit, the effects of a string wake can be identified in the dark matter distribution, using the current level of the statistical analysis, down to a redshift of $z = 10$., Comment: 18 pages, 15 figures

We derive the essentials of the skewed weak lensing likelihood via a simple Hierarchical Model. Our likelihood passes four objective and cosmology-independent tests which a standard Gaussian likelihood fails. We demonstrate that sound weak lensing analyses are naturally biased low, and this does not indicate any new physics such as deviations from $\Lambda$CDM. Mathematically, the biases arise because noisy two-point functions follow skewed distributions. This form of bias is already known from CMB analyses, where the low multipoles have asymmetric error bars. Weak lensing is more strongly affected by this asymmetry as galaxies form a discrete set of shear tracer particles, in contrast to a smooth shear field. We demonstrate that the biases can be up to 30 percent of the standard deviation per data point, dependent on the properties of the weak lensing survey. Our likelihood provides a versatile framework with which to address this bias in future weak lensing analyses., Comment: Submitted to MNRAS

Recent studies have presented evidence for tension between the constraints on Omega_m and sigma_8 from the cosmic microwave background (CMB) and measurements of large-scale structure (LSS). This tension can potentially be resolved by appealing to extensions of the standard model of cosmology and/or untreated systematic errors in the modelling of LSS, of which baryonic physics has been frequently suggested. We revisit this tension using, for the first time, carefully-calibrated cosmological hydrodynamical simulations, which thus capture the back reaction of the baryons on the total matter distribution. We have extended the BAHAMAS simulations to include a treatment of massive neutrinos, which currently represents the best motivated extension to the standard model. We make synthetic thermal Sunyaev-Zel'dovich effect, weak galaxy lensing, and CMB lensing maps and compare to observed auto- and cross-power spectra from a wide range of recent observational surveys. We conclude that: i) in general there is tension between the primary CMB and LSS when adopting the standard model with minimal neutrino mass; ii) after calibrating feedback processes to match the gas fractions of clusters, the remaining uncertainties in the baryonic physics modelling are insufficient to reconcile this tension; and iii) if one accounts for internal tensions in the Planck CMB dataset (by allowing the lensing amplitude, A_Lens, to vary), invoking a non-minimal neutrino mass, typically of 0.2-0.4 eV, can resolve the tension. This solution is fully consistent with separate constraints from the primary CMB and baryon acoustic oscillations., Comment: To match the accepted MNRAS version. BAHAMAS maps available at http://www.astro.ljmu.ac.uk/~igm/BAHAMAS/

We study the statistics of peaks in a weak lensing reconstructed mass map of the first 450 square degrees of the Kilo Degree Survey. The map is computed with aperture masses directly applied to the shear field with an NFW-like compensated filter. We compare the peak statistics in the observations with that of simulations for various cosmologies to constrain the cosmological parameter $S_8 = \sigma_8 \sqrt{\Omega_{\rm m}/0.3}$, which probes the ($\Omega_{\rm m}, \sigma_8$) plane perpendicularly to its main degeneracy. We estimate $S_8=0.750\pm0.059$, using peaks in the signal-to-noise range $0 \leq {\rm S/N} \leq 4$, and accounting for various systematics, such as multiplicative shear bias, mean redshift bias, baryon feedback, intrinsic alignment, and shear-position coupling. These constraints are $\sim25\%$ tighter than the constraints from the high significance peaks alone ($3 \leq {\rm S/N} \leq 4$) which typically trace single-massive halos. This demonstrates the gain of information from low-S/N peaks. However we find that including ${\rm S/N} < 0$ peaks does not add further information. Our results are in good agreement with the tomographic shear two-point correlation function measurement in KiDS-450. Combining shear peaks with non-tomographic measurements of the shear two-point correlation functions yields a $\sim20\%$ improvement in the uncertainty on $S_8$ compared to the shear two-point correlation functions alone, highlighting the great potential of peaks as a cosmological probe., Comment: 20 pages, 17 figures, accepted for publication in MNRAS

This paper is the first of a series of papers constraining cosmological parameters with weak lensing peak statistics using $\sim 450~\rm deg^2$ of imaging data from the Kilo Degree Survey (KiDS-450). We measure high signal-to-noise ratio (SNR: $\nu$) weak lensing convergence peaks in the range of $3<\nu<5$, and employ theoretical models to derive expected values. These models are validated using a suite of simulations. We take into account two major systematic effects, the boost factor and the effect of baryons on the mass-concentration relation of dark matter haloes. In addition, we investigate the impacts of other potential astrophysical systematics including the projection effects of large scale structures, intrinsic galaxy alignments, as well as residual measurement uncertainties in the shear and redshift calibration. Assuming a flat $\Lambda$CDM model, we find constraints for $S_{\rm 8}=\sigma_{\rm 8}(\Omega_{\rm m}/0.3)^{0.5}=0.746^{+0.046}_{-0.107}$ according to the degeneracy direction of the cosmic shear analysis and $\Sigma_{\rm 8}=\sigma_{\rm 8}(\Omega_{\rm m}/0.3)^{0.38}=0.696^{+0.048}_{-0.050}$ based on the derived degeneracy direction of our high-SNR peak statistics. The difference between the power index of $S_{\rm 8}$ and in $\Sigma_{\rm 8}$ indicates that combining the two probes has the potential to break the degeneracy in $\sigma_{\rm 8}$ and $\Omega_{\rm m}$. Our results are consistent with the cosmic shear tomographic correlation analysis of the same dataset and $\sim 2\sigma$ lower than the Planck 2016 results., Comment: 20 pages, 12 figures, accepted for publication in MNRAS

We perform a combined analysis of cosmic shear tomography, galaxy-galaxy lensing tomography, and redshift-space multipole power spectra (monopole and quadrupole) using 450 deg$^2$ of imaging data by the Kilo Degree Survey (KiDS) overlapping with two spectroscopic surveys: the 2-degree Field Lensing Survey (2dFLenS) and the Baryon Oscillation Spectroscopic Survey (BOSS). We restrict the galaxy-galaxy lensing and multipole power spectrum measurements to the overlapping regions with KiDS, and self-consistently compute the full covariance between the different observables using a large suite of $N$-body simulations. We methodically analyze different combinations of the observables, finding that galaxy-galaxy lensing measurements are particularly useful in improving the constraint on the intrinsic alignment amplitude (by 30%, positive at $3.5\sigma$ in the fiducial data analysis), while the multipole power spectra are useful in tightening the constraints along the lensing degeneracy direction (e.g. factor of two stronger matter density constraint in the fiducial analysis). The fully combined constraint on $S_8 \equiv \sigma_8 \sqrt{\Omega_{\rm m}/0.3} = 0.742 \pm 0.035$, which is an improvement by 20% compared to KiDS alone, corresponds to a $2.6\sigma$ discordance with Planck, and is not significantly affected by fitting to a more conservative set of scales. Given the tightening of the parameter space, we are unable to resolve the discordance with an extended cosmology that is simultaneously favored in a model selection sense, including the sum of neutrino masses, curvature, evolving dark energy, and modified gravity. The complementarity of our observables allows for constraints on modified gravity degrees of freedom that are not simultaneously bounded with either probe alone, and up to a factor of three improvement in the $S_8$ constraint in the extended cosmology compared to KiDS alone., Comment: 31 pages, 20 figures, results unchanged, version accepted for publication by MNRAS. Abstract abridged. Our measurements and fitting pipeline are public at https://github.com/sjoudaki/CosmoLSS

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 $S_8\equiv \sigma_8 \sqrt{\Omega_{\rm m}/0.3}=0.800_{-0.027}^{+0.029}$, 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., Comment: 32 pages, 22 figures. Minor changes to match version accepted by MNRAS. Data publicly available at http://kids.strw.leidenuniv.nl/sciencedata.php

We present the tomographic cross-correlation between galaxy lensing measured in the Kilo Degree Survey (KiDS-450) with overlapping lensing measurements of the cosmic microwave background (CMB), as detected by Planck 2015. We compare our joint probe measurement to the theoretical expectation for a flat $\Lambda$CDM cosmology, assuming the best-fitting cosmological parameters from the KiDS-450 cosmic shear and Planck CMB analyses. We find that our results are consistent within $1\sigma$ with the KiDS-450 cosmology, with an amplitude re-scaling parameter $A_{\rm KiDS} = 0.86 \pm 0.19$. Adopting a Planck cosmology, we find our results are consistent within $2\sigma$, with $A_{\it Planck} = 0.68 \pm 0.15$. We show that the agreement is improved in both cases when the contamination to the signal by intrinsic galaxy alignments is accounted for, increasing $A$ by $\sim 0.1$. This is the first tomographic analysis of the galaxy lensing -- CMB lensing cross-correlation signal, and is based on five photometric redshift bins. We use this measurement as an independent validation of the multiplicative shear calibration and of the calibrated source redshift distribution at high redshifts. We find that constraints on these two quantities are strongly correlated when obtained from this technique, which should therefore not be considered as a stand-alone competitive calibration tool., Comment: 14 pages, 11 figures

We compute the spherical-sky weak-lensing power spectrum of the shear and convergence. We discuss various approximations, such as flat-sky, and first- and second- order Limber equations for the projection. We find that the impact of adopting these approximations is negligible when constraining cosmological parameters from current weak lensing surveys. This is demonstrated using data from the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). We find that the reported tension with Planck Cosmic Microwave Background (CMB) temperature anisotropy results cannot be alleviated. For future large-scale surveys with unprecedented precision, we show that the spherical second-order Limber approximation will provide sufficient accuracy. In this case, the cosmic-shear power spectrum is shown to be in agreement with the full projection at the sub-percent level for l > 3, with the corresponding errors an order of magnitude below cosmic variance for all l. When computing the two-point shear correlation function, we show that the flat-sky fast Hankel transformation results in errors below two percent compared to the full spherical transformation. In the spirit of reproducible research, our numerical implementation of all approximations and the full projection are publicly available within the package nicaea at http://www.cosmostat.org/software/nicaea., Comment: 17 pages, 5 figures, 2 tables. Matches published version (MNRAS, 2017, 472, 2126)

We develop a statistical estimator to infer the redshift probability distribution of a photometric sample of galaxies from its angular cross-correlation in redshift bins with an overlapping spectroscopic sample. This estimator is a minimum variance weighted quadratic function of the data: a quadratic estimator. This extends and modifies the methodology presented by McQuinn & White (2013). The derived source redshift distribution is degenerate with the source galaxy bias, which must be constrained via additional assumptions. We apply this estimator to constrain source galaxy redshift distributions in the Kilo-Degree imaging survey through cross-correlation with the spectroscopic 2-degree Field Lensing Survey, presenting results first as a binned step-wise distribution in the range z < 0.8, and then building a continuous distribution using a Gaussian process model. We demonstrate the robustness of our methodology using mock catalogues constructed from N-body simulations, and comparisons with other techniques for inferring the redshift distribution., Comment: 17 pages, 10 figures, accepted for publication by MNRAS

We measure the cross-correlation between Fermi-LAT gamma-ray photons and over 1000 deg$^2$ of weak lensing data from the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS), the Red Cluster Sequence Lensing Survey (RCSLenS), and the Kilo Degree Survey (KiDS). We present the first measurement of tomographic weak lensing cross-correlations and the first application of spectral binning to cross-correlations between gamma rays and weak lensing. The measurements are performed using an angular power spectrum estimator while the covariance is estimated using an analytical prescription. We verify the accuracy of our covariance estimate by comparing it to two internal covariance estimators. Based on the non-detection of a cross-correlation signal, we derive constraints on weakly interacting massive particle (WIMP) dark matter. We compute exclusion limits on the dark matter annihilation cross-section $\langle\sigma_\rm{ann} v \rangle$, decay rate $\Gamma_\rm{dec}$, and particle mass $m_\rm{DM}$. We find that in the absence of a cross-correlation signal, tomography does not significantly improve the constraining power of the analysis. Assuming a strong contribution to the gamma-ray flux due to small-scale clustering of dark matter and accounting for known astrophysical sources of gamma rays, we exclude the thermal relic cross-section for particle masses of $m_\rm{DM}\lesssim 20$ GeV., Comment: 19 pages, 17 figures, accepted in MNRAS

Constraining neutrino mass remains an elusive challenge in modern physics. Precision measurements are expected from several upcoming cosmological probes of large-scale structure. Achieving this goal relies on an equal level of precision from theoretical predictions of neutrino clustering. Numerical simulations of the non-linear evolution of cold dark matter and neutrinos play a pivotal role in this process. We incorporate neutrinos into the cosmological N-body code CUBEP3M and discuss the challenges associated with pushing to the extreme scales demanded by the neutrino problem. We highlight code optimizations made to exploit modern high performance computing architectures and present a novel method of data compression that reduces the phase-space particle footprint from 24 bytes in single precision to roughly 9 bytes. We scale the neutrino problem to the Tianhe-2 supercomputer and provide details of our production run, named TianNu, which uses 86% of the machine (13,824 compute nodes). With a total of 2.97 trillion particles, TianNu is currently the world's largest cosmological N-body simulation and improves upon previous neutrino simulations by two orders of magnitude in scale. We finish with a discussion of the unanticipated computational challenges that were encountered during the TianNu runtime., Comment: Accepted for publication in Research in Astronomy and Astrophysics

Astrophysical techniques have pioneered the discovery of neutrino mass properties. Current cosmological observations give an upper bound on neutrino masses by attempting to disentangle the small neutrino contribution from the sum of all matter using precise theoretical models. We discover the differential neutrino condensation effect in our TianNu N-body simulation. Neutrino masses can be inferred using this effect by comparing galaxy properties in regions of the universe with different neutrino relative abundance (i.e. the local neutrino to cold dark matter density ratio). In "neutrino-rich"' regions, more neutrinos can be captured by massive halos compared to "neutrino-poor" regions. This effect differentially skews the halo mass function and opens up the path to independent neutrino mass measurements in current or future galaxy surveys., Comment: 15 pages, 6 figures

We present measurements of the spatial mapping between (hot) baryons and the total matter in the Universe, via the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) map from Planck and the weak gravitational lensing maps from the Red Sequence Cluster Survey (RCSLenS). The cross-correlations are performed on the map level where all the sources (including diffuse intergalactic gas) contribute to the signal. We consider two configuration-space correlation function estimators, $\xi^{ y-\kappa}$ and $\xi^ {y-\gamma_{t}}$, and a Fourier space estimator, $C_{\ell}^{y-\kappa}$, in our analysis. We detect a significant correlation out to three degrees of angular separation on the sky. Based on statistical noise only, we can report 13$\sigma$ and 17$\sigma$ detections of the cross-correlation using the configuration-space $y-\kappa$ and $y-\gamma_{t}$ estimators, respectively. Including a heuristic estimate of the sampling variance yields a detection significance of 6$\sigma$ and 8$\sigma$, respectively. A similar level of detection is obtained from the Fourier-space estimator, $C_{\ell}^{y-\kappa}$. As each estimator probes different dynamical ranges, their combination improves the significance of the detection. We compare our measurements with predictions from the cosmo-OWLS suite of cosmological hydrodynamical simulations, where different galactic feedback models are implemented. We find that a model with considerable AGN feedback that removes large quantities of hot gas from galaxy groups and WMAP-7yr best-fit cosmological parameters provides the best match to the measurements. All baryonic models in the context of a Planck cosmology over-predict the observed signal. Similar cosmological conclusions are drawn when we employ a halo model with the observed `universal' pressure profile., Comment: 16 pages, 13 figures

We present the 2-degree Field Lensing Survey (2dFLenS), a new galaxy redshift survey performed at the Anglo-Australian Telescope. 2dFLenS is the first wide-area spectroscopic survey specifically targeting the area mapped by deep-imaging gravitational lensing fields, in this case the Kilo-Degree Survey. 2dFLenS obtained 70,079 redshifts in the range z < 0.9 over an area of 731 sq deg, and is designed to extend the datasets available for testing gravitational physics and promote the development of relevant algorithms for joint imaging and spectroscopic analysis. The redshift sample consists first of 40,531 Luminous Red Galaxies (LRGs), which enable analyses of galaxy-galaxy lensing, redshift-space distortion, and the overlapping source redshift distribution by cross-correlation. An additional 28,269 redshifts form a magnitude-limited (r < 19.5) nearly-complete sub-sample, allowing direct source classification and photometric-redshift calibration. In this paper, we describe the motivation, target selection, spectroscopic observations, and clustering analysis of 2dFLenS. We use power spectrum multipole measurements to fit the redshift-space distortion parameter of the LRG sample in two redshift ranges 0.15 < z < 0.43 and 0.43 < z < 0.7 as beta = 0.49 +/- 0.15 and beta = 0.26 +/- 0.09, respectively. These values are consistent with those obtained from LRGs in the Baryon Oscillation Spectroscopic Survey. 2dFLenS data products will be released via our website http://2dflens.swin.edu.au., Comment: 28 pages, 21 figures, accepted for publication by MNRAS