Weak-lensing Peak Research Articles

Constraining modified gravity with weak lensing peaks

Abstract 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 log10(|fR0|) = −6 to 2% precision, and log10(H0rc) = 0.5 to 25% precision.

UNIONS: The impact of systematic errors on weak-lensing peak counts

Context. The Ultraviolet Near-Infrared Optical Northern Survey (UNIONS) is an ongoing deep photometric multiband survey of the northern sky. As part of UNIONS, the Canada-France Imaging Survey (CFIS) provides r-band data, which we use to study weak-lensing peak counts for cosmological inference. Aims. We assess systematic effects for weak-lensing peak counts and their impact on cosmological parameters for the UNIONS survey. In particular, we present results on local calibration, metacalibration shear bias, baryonic feedback, the source galaxy redshift estimate, intrinsic alignment, and cluster member dilution. Methods. For each uncertainty and systematic effect, we describe our mitigation scheme and the impact on cosmological parameter constraints. We obtain constraints on cosmological parameters from Monte Carlo Markov chains using CFIS data and MassiveNuS N-body simulations as a model for peak counts statistics. Results. Depending on the calibration (local versus global, and the inclusion or not of the residual multiplicative shear bias), the mean matter density parameter, Ωm, can shift by up to −0.024 (−0.5σ). We also see that including baryonic corrections can shift Ωm by +0.027 (+0.5σ) with respect to the dark-matter-only simulations. Reducing the impact of the intrinsic alignment and cluster member dilution through signal-to-noise cuts leads to larger constraints. Finally, with a mean redshift uncertainty of Δz̄ = 0.03, we see that the shift in Ωm (+0.001, which corresponds to +0.02σ) is not significant. Conclusions. This paper investigates, for the first time with UNIONS weak-lensing data and peak counts, the impact of systematic effects. The value of Ωm is the most impacted and can shift by up to ∼0.03, which corresponds to 0.5σ depending on the choices for each systematics. We expect constraints to become more reliable with future (larger) data catalogs, for which the current pipeline will provide a starting point. The code used to obtain the results is available on GitHub.

Weak-lensing peak statistics – steepness versus height

ABSTRACTIn weak-lensing cosmological studies, peak statistics is sensitive to non-linear structures and thus complementary to cosmic shear two-point correlations. In this paper, we explore a new approach, namely, the peak steepness statistics, with the overall goal to understand the cosmological information embedded there in comparison with the commonly used peak height statistics. We perform the analyses with ray-tracing simulations considering different sets of cosmological parameters Ωm and σ8. A theoretical model to calculate the abundance of high peaks based on steepness is also presented, which can well describe the main trend of the peak distribution from simulations. We employ Δχ2 and Fisher analyses to study the cosmological dependence of the two peak statistics using our limited sets of simulations as well as our theoretical model. Within our considerations without including potential systematic effects, the results show that the steepness statistics tends to have higher sensitivities to the cosmological parameters than the peak height statistics and this advantage is diluted with the increase of the shape noise. Using the theoretical model, we investigate the physical reasons accounting for the different cosmological information embedded in the two statistics. Our analyses indicate that the projection effect from large-scale structures plays an important role to enhance the gain from the steepness statistics. The redshift and cosmology dependence of dark matter halo density profiles also contributes to the differences between the two statistics.

Comparing weak lensing peak counts in baryonic correction models to hydrodynamical simulations

ABSTRACT Next-generation weak lensing (WL) surveys, such as by the Vera Rubin Observatory, the Roman Space Telescope, and the Euclid space mission, will supply vast amounts of data probing small, highly non-linear scales. Extracting information from these scales requires higher-order statistics and the controlling of related systematics such as baryonic effects. To account for baryonic effects in cosmological analyses at reduced computational cost, semi-analytic baryonic correction models (BCMs) have been proposed. Here, we study the accuracy of a particular BCM (the A20-BCM) for WL peak counts, a well-studied, simple, and effective higher-order statistic. We compare WL peak counts generated from the full hydrodynamical simulation IllustrisTNG and a baryon-corrected version of the corresponding dark matter-only simulation IllustrisTNG-Dark. We apply galaxy shape noise matching depths reached by DES, KiDS, HSC, LSST, Roman, and Euclid. We find that peak counts from the A20-BCM are (i) accurate at per cent level for peaks with S/N < 4, (ii) statistically indistinguishable from IllustrisTNG in most current and ongoing surveys, but (iii) insufficient for deep future surveys covering the largest solid angles, such as LSST and Euclid. We find that the BCM matches individual peaks accurately, but underpredicts the amplitude of the highest peaks. We conclude that the A20-BCM is a viable substitute for full hydrodynamical simulations in cosmological parameter estimation from beyond-Gaussian statistics for ongoing and future surveys with modest solid angles. For the largest surveys, the A20-BCM must be refined to provide a more accurate match, especially to the highest peaks.

Effects of Galaxy Intrinsic Alignment on Weak Lensing Peak Statistics

The galaxy intrinsic alignment (IA) is a dominant source of systematics in weak lensing (WL) studies. In this paper, by employing large simulations with semianalytical galaxy formation, we investigate the IA effects on WL peak statistics. Different simulated source galaxy samples of different redshift distributions are constructed, where both WL shear and IA signals are included. Convergence reconstruction and peak statistics are then performed for these samples. Our results show that the IA effects on peak abundances mainly consist of two aspects. One is the additional contribution from IA to the shape noise. The other is from the satellite IA that can affect the peak signals from their host clusters significantly. The latter depends on the level of inclusion in a shear sample of the satellite galaxies of the clusters that contribute to WL peaks and thus is sensitive to the redshift distribution of source galaxies. We pay particular attention to satellite IA and adjust it artificially in the simulations to analyze the dependence of the satellite IA impacts on its strength. This information can potentially be incorporated into the modeling of WL peak abundances, especially for high peaks physically originated from massive clusters of galaxies, and thus mitigate the IA systematics on the cosmological constraints derived from WL peaks.

Cosmological studies from HSC-SSP tomographic weak-lensing peak abundances

ABSTRACT We perform weak-lensing tomographic peak studies using the first year of shear data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) survey. The effective area used in our analyses after field selection, masking, and boundary exclusions is $\sim 58 \deg ^2$. The source galaxies are divided into low- and high-redshift bins, with 0.2 ≤ zp ≤ 0.85 and 0.85 ≤ zp ≤ 1.5, respectively. We utilize our halo-based theoretical peak model, including the projection effect of large-scale structures, to derive cosmological constraints from the observed tomographic high-peak abundances with the signal-to-noise ratio in the range of νN = [3.5, 5.5]. These high peaks are closely associated with the lensing effects of massive clusters of galaxies. Thus, the inclusion of their member galaxies in the shear catalogue can lead to significant source clustering and dilute their lensing signals. We account for this systematic effect in our theoretical modelling. In addition, the impacts of baryonic effects, galaxy intrinsic alignments, as well as residual uncertainties in shear and photometric redshift calibrations are also analysed. Within the flat ΛCDM model, the derived constraint is $S_8=\sigma _8(\Omega _{\rm m}/0.3)^{0.5} =0.758_{-0.076}^{+0.033}$ and $0.768_{-0.057}^{+0.030}$ with the source clustering information measured from the two cluster catalogues CAMIRA and WZL, respectively. The asymmetric uncertainties are due to the different degeneracy direction of (Ωm, σ8) from high-peak abundances compared with that from the cosmic shear two-point correlations, which gives rise to the power index α ≈ 0.5. Fitting to our constraints, we obtain α ≈ 0.38 and $\Sigma _8=\sigma _8(\Omega _{\rm m}/0.3)^{\alpha }=0.772_{-0.032}^{+0.028}$ (CAMIRA) and $0.781_{-0.033}^{+0.028}$ (WZL). In comparison with the results from non-tomographic peak analyses, the 1σ uncertainties on Σ8 are reduced by a factor of ∼1.3.

Cosmological forecasts with the clustering of weak lensing peaks

ABSTRACT Maximizing the information that can be extracted from weak lensing (WL) measurements is a key goal for upcoming stage IV surveys. 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 WL peak abundance. In this work, we study the clustering of WL peaks, and present parameter constraint forecasts for an lsst-like survey. We use the cosmo-SLICS wCDM 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 that 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 w0 than the peak abundance, and when the probes are combined, constraints on Ωm, S8, h, and w0 improve by at least a factor of 2, relative to the peak abundance alone. Finally, we compare the forecasts for WL peaks and voids, and show that the two are also complementary; both probes can offer better constraints on S8 and w0 than the shear correlation function by roughly a factor of 2.

Cosmological constraints from weak lensing peaks: Can halo models accurately predict peak counts?

In order to extract full cosmological information from next-generation large and high-precision weak lensing (WL) surveys (e.g. Euclid, Roman, LSST), higher-order statistics that probe the small-scale, non-linear regime of large scale structure (LSS) need to be utilized. WL peak counts, which trace overdensities in the cosmic web, are one promising and simple statistic for constraining cosmological parameters. The physical origin of WL peaks have previously been linked to dark matter halos along the line of sight and this peak-halo connection has been used to develop various semi-analytic halo-based models for predicting peak counts. Here, we study the origin of WL peaks and the effectiveness of halo-based models for WL peak counts using a suite of ray-tracing N-body simulations. We compare WL peaks in convergence maps from the full simulations to those in maps created from only particles associated with halos -- the latter playing the role of a "perfect" halo model. We find that while halo-only contributions are able to replicate peak counts qualitatively well, halos do not explain all WL peaks. Halos particularly underpredict negative peaks, which are associated with local overdensities in large-scale underdense regions along the line of sight. In addition, neglecting non-halo contributions to peaks counts leads to a significant bias on the parameters ($\Omega_{\rm m}$, $\sigma_{8}$) for surveys larger than $\geq$ 100 deg$^{2}$. We conclude that other elements of the cosmic web, outside and far away from dark matter halos, need to be incorporated into models of WL peaks in order to infer unbiased cosmological constraints.

Probing dark energy with tomographic weak-lensing aperture mass statistics

We forecast and optimize the cosmological power of various weak-lensing aperture mass (Map) map statistics for future cosmic shear surveys, including peaks, voids, and the full distribution of pixels (1DMap). 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-SLICSN-body simulations, we buildEuclid-like mocks to explore theS8 − Ωm − w0parameter space. We develop a new tomographic formalism that exploits the cross-information between redshift slices (cross-Map) in addition to the information from individual slices (auto-Map) probed in the standard approach. Our auto-Mapforecast precision is in good agreement with the recent literature on weak-lensing peak statistics and is improved by ∼50% when including cross-Map. It is further boosted by the use of 1DMapthat 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 parameterS8is enhanced by ∼45% (almost twice better) when combining 1DMapand theγ-2PCF compared to theγ-2PCF alone. We additionally measure the first combined forecasts on the dark energy equation of statew0, finding a factor of three reduction in the statistical error compared to theγ-2PCF alone. This demonstrates that the complementary cosmological information explored by non-GaussianMapmap statistics not only offers the potential to improve the constraints on the recentσ8–Ωmtension, but also constitutes an avenue to understanding the accelerated expansion of our Universe.

Optimal void finders in weak lensing maps

ABSTRACT Cosmic voids are a key component of the large-scale structure that contain a plethora of cosmological information. Typically, voids are identified from the underlying galaxy distribution, which is a biased tracer of the total matter field. Previous works have shown that 2D voids identified in weak lensing (WL) maps – WL voids – correspond better to true underdense regions along the line of sight. In this work, we study how the properties of WL voids depend on the choice of void finder, by adapting several popular void finders. We present and discuss the differences between identifying voids directly in the convergence maps, and in the distribution of WL peaks. Particular effort has been made to test how these results are affected by galaxy shape noise (GSN), which is a dominant source of noise in WL observations. By studying the signal-to-noise ratios (S/N) for the tangential shear profile of each void finder, we find that voids identified directly in the convergence maps have the highest S/N but are also the ones most affected by GSN. Troughs are least affected by noise, but also have the lowest S/N. The tunnel algorithm, which identifies voids in the distribution of WL peaks, represents a good compromise between finding a large tangential shear S/N and mitigating the effect of GSN.

Weak-lensing Peak Statistics in Mocks by the Inverse-Gaussianization Method

Abstract Recent studies have shown the great power of peak counts in weak-lensing maps. In this work, we apply the inverse-Gaussianization method proposed in Yu et al. to produce weak-lensing convergence maps quickly and investigate the peak statistics, including the peak height counts and peak steepness counts in these mocks. The distributions of peak height and steepness are in good agreement with the simulation results. The difference is ≲20% for these peak statistics in the maps at source redshift z s = 1. Also, the loss of off-diagonal elements in the peak covariance motivates us to consider the super-sample variance in weak-lensing peak statistics. We propose four correction methods to effectively recover the (anti)correlation among different bins by adding different scatters in the mean value of these mocks. Finally, as an example of the application, we adopt the improved inverse-Gaussianization method to quickly generate 40,000 mocks to calculate precision matrices for the power spectrum and peak-statistics joint analysis.

Cosmological Studies from Tomographic Weak Lensing Peak Abundances and Impacts of Photo-z Errors

Abstract Weak lensing peak abundance analyses have been applied in different surveys and demonstrated to be a powerful statistic in extracting cosmological information complementary to cosmic shear two-point correlation studies. Future large surveys with high number densities of galaxies will enable tomographic peak analyses. Focusing on high peaks, we investigate quantitatively how the tomographic redshift binning can enhance the cosmological gains. We also perform detailed studies about the degradation of cosmological information due to photometric redshift (photo-z) errors. We show that for surveys with a number density of galaxies of ∼40 arcmin−2, a median redshift of ∼1, and a survey area of ∼15,000 deg2, the four-bin tomographic peak analyses can reduce the error contours of (Ωm, σ 8) by a factor of 5 compared to 2D peak analyses in the ideal case of the photo-z error being absent. More redshift bins can hardly lead to significantly better constraints. The photo-z error model here is parameterized by z bias and σ ph and the fiducial values of z bias = 0.003 and σ ph = 0.02 are taken. We find that using tomographic peak analyses can constrain the photo-z errors simultaneously with cosmological parameters. For four-bin analyses, we can obtain σ(z bias)/z bias ∼ 10% and σ(σ ph)/σ ph ∼ 5% without assuming priors on them. Accordingly, the cosmological constraints on Ωm and σ 8 degrade by factors of ∼2.2 and ∼1.8, respectively, with respect to zero uncertainties on photo-z parameters. We find that the uncertainty of z bias plays a more significant role in degrading the cosmological constraints than that of σ ph.

Cosmological test of gravity using weak lensing voids

ABSTRACT Modifications to general relativity often incorporate screening mechanisms in order to remain compatible with existing tests of gravity. The screening is less efficient in underdense regions, which suggests that cosmic voids can be a useful cosmological probe for constraining modified gravity models. In particular, weak lensing by voids has been proposed as a promising test of such theories. Usually, voids are identified from galaxy distributions, making them biased tracers of the underlying matter field. An alternative approach is to study voids identified in weak lensing maps – weak lensing voids – which have been shown to better correspond to true underdense regions. In this paper, we study the ability of weak lensing voids to detect the signatures of modified gravity. Focusing on the void abundance and weak lensing profiles, we find that both statistics are sensitive probes of gravity. These are quantified in terms of the signal-to-noise ratios (SNR) with which an LSST-like survey will be able to distinguish between different gravity models. We find that the tangential shear profiles of weak lensing voids are considerably better than galaxy voids at this, though voids have somewhat lower SNR than weak lensing peaks. The abundances of voids and peaks have, respectively, $\rm {SNR} = 50$ and 70 for a popular class of modified gravity in an LSST-like survey.

Effects of baryons on weak lensing peak statistics

Upcoming weak-lensing surveys have the potential to become leading cosmological probes provided all systematic effects are under control. Recently, the ejection of gas due to feedback energy from active galactic nuclei (AGN) has been identified as major source of uncertainty, challenging the success of future weak-lensing probes in terms of cosmology. In this paper we investigate the effects of baryons on the number of weak-lensing peaks in the convergence field. Our analysis is based on full-sky convergence maps constructed via light-cones from N-body simulations, and we rely on the baryonic correction model of [1] to model the baryonic effects on the density field. As a result we find that the baryonic effects strongly depend on the Gaussian smoothing applied to the convergence map. For a DES-like survey setup, a smoothing of θk≳8 arcmin is sufficient to keep the baryon signal below the expected statistical error. Smaller smoothing scales lead to a significant suppression of high peaks with \U0001d4ae/\U0001d4a9> 2, while lower peaks are not affected. The situation is more severe for a Euclid-like setup, where a smoothing of θk≳16 arcmin is required to keep the baryonic suppression signal below the statistical error. Smaller smoothing scales require a full modelling of baryonic effects since both low and high peaks are strongly affected by baryonic feedback.

Halo collapse: virialization by shear and rotation in dynamical dark-energy models. Effects on weak-lensing peaks

The evolution of the virial overdensity Δvir for ΛCDM and seven dynamical dark-energy models is investigated in the extended spherical collapse model (SCM). Here the virialization process is naturally achieved by introducing shear and rotation instead of using the virial theorem. We generalise two approaches proposed in the literature and show that, regardless of the dark-energy model, the new virialization term can be calibrated on the peculiar velocity of the shell as measured from Einstein-de Sitter simulations. The two virialization recipes qualitatively reproduce the features of the ordinary SCM, i.e., a constant Δvir for the EdS model and time-variation for dark-energy models, but without any mass dependence. Depending on the actual description of virialization and on the dark-energy model, the value of Δvir varies between 10 and 40 percent. We use the new recipes to predict the surface-mass-density profile of dark matter haloes and the number of convergence density peaks for LSST- and Euclid-like weak lensing surveys.

The self-similarity of weak lensing peaks

ABSTRACT We study the statistics of weak lensing convergence peaks, such as their abundance and two-point correlation function (2PCF), for a wide range of cosmological parameters Ωm and σ8 within the standard ΛCDM paradigm, focusing on intermediate-height peaks with signal-to-noise ratio (SNR) of 1.5–3.5. We find that the cosmology dependence of the peak abundance can be described by a one-parameter fitting formula that is accurate to within $\sim 3{{\ \rm per\ cent}}$. The peak 2PCFs are shown to feature a self-similar behaviour: if the peak separation is rescaled by the mean interpeak distance, catalogues with different minimum peak SNR values have identical clustering, which suggests that the peak abundance and clustering are closely interconnected. A simple fitting model for the rescaled 2PCF is given, which together with the peak abundance model above can predict peak 2PCFs with an accuracy better than $\sim 5{{\ \rm per\ cent}}$. The abundance and 2PCFs for intermediate peaks have very different dependencies on Ωm and σ8, implying that their combination can be used to break the degeneracy between these two parameters.

Weak lensing peak statistics in the era of large scale cosmological surveys

Weak lensing peak counts are a powerful statistical tool for constraining cosmological parameters. So far, this method has been applied only to surveys with relatively small areas, up to several hundred square degrees. As future surveys will provide weak lensing datasets with size of thousands of square degrees, the demand on the theoretical prediction of the peak statistics will become heightened. In particular, large simulations of increased cosmological volume are required. In this work, we investigate the possibility of using simulations generated with the fast Comoving-Lagrangian acceleration (COLA) method, coupled to the convergence map generator Ufalcon, for predicting the peak counts. We examine the systematics introduced by the COLA method by comparing it with a full TreePM code. We find that for a 2000 deg2 survey, the systematic error is much smaller than the statistical error. This suggests that the COLA method is able to generate promising theoretical predictions for weak lensing peaks. We also examine the constraining power of various configurations of data vectors, exploring the influence of splitting the sample into tomographic bins and combining different smoothing scales. We find the combination of smoothing scales to have the most constraining power, improving the constraints on the S8 amplitude parameter by at least 40% compared to a single smoothing scale, with tomography brining only limited increase in measurement precision.

Quantifying systematics from the shear inversion on weak-lensing peak counts

Weak-lensing peak counts provide a straightforward way to constrain cosmology by linking local maxima of the lensing signal to the mass function. Recent applications to data have already been numerous and fruitful. However, the importance of understanding and dealing with systematics increases as data quality reaches an unprecedented level. One of the sources of systematics is the convergence-shear inversion. This effect, inevitable when carrying out a convergence field from observations, is usually neglected by theoretical peak models. Thus, it could have an impact on cosmological results. In this paper, we study the bias from neglecting (mis-modeling) the inversion. Our tests show a small but non-negligible bias. The cosmological dependence of this bias seems to be related to the parameter Σ8 ≡ (Ωm∕(1 − α))1 − α(σ8∕α)α, where α = 2∕3. When this bias propagates to the parameter estimation, we discovered that constraint contours involving the dark energy equation of state can differ by 2σ. Such an effect can be even larger for future high-precision surveys and we argue that the inversion should be properly modeled for theoretical peak models.

Weak-lensing peaks in simulated light cones: investigating the coupling between dark matter and dark energy

In this paper, we study the statistical properties of weak lensing peaks in light-cones generated from cosmological simulations. In order to assess the prospects of such observable as a cosmological probe, we consider simulations that include interacting Dark Energy (hereafter DE) models with coupling term between DE and Dark Matter. Cosmological models that produce a larger population of massive clusters have more numerous high signal-to-noise peaks; among models with comparable numbers of clusters those with more concentrated haloes produce more peaks. The most extreme model under investigation shows a difference in peak counts of about $20\%$ with respect to the reference $\mathrm{\Lambda}$CDM model. We find that peak statistics can be used to distinguish a coupling DE model from a reference one with the same power spectrum normalisation. The differences in the expansion history and the growth rate of structure formation are reflected in their halo counts, non-linear scale features and, through them, in the properties of the lensing peaks. For a source redshift distribution consistent with the expectations of future space-based wide field surveys, we find that typically seventy percent of the cluster population contributes to weak-lensing peaks with signal-to-noise ratios larger than two, and that the fraction of clusters in peaks approaches one-hundred percent for haloes with redshift z$\leq$0.5. Our analysis demonstrates that peak statistics are an important tool for disentangling DE models by accurately tracing the structure formation processes as a function of the cosmic time.

Projection Effects of Large-scale Structures on Weak-lensing Peak Abundances

Abstract High peaks in weak lensing (WL) maps originate dominantly from the lensing effects of single massive halos. Their abundance is therefore closely related to the halo mass function and thus a powerful cosmological probe. However, besides individual massive halos, large-scale structures (LSS) along lines of sight also contribute to the peak signals. In this paper, with ray-tracing simulations, we investigate the LSS projection effects. We show that for current surveys with a large shape noise, the stochastic LSS effects are subdominant. For future WL surveys with source galaxies having a median redshift z med ∼ 1 or higher, however, they are significant. For the cosmological constraints derived from observed WL high-peak counts, severe biases can occur if the LSS effects are not taken into account properly. We extend the model of Fan et al. by incorporating the LSS projection effects into the theoretical considerations. By comparing with simulation results, we demonstrate the good performance of the improved model and its applicability in cosmological studies.