Weak Lensing Mass Research Articles

Weak-lensing Mass Bias in Merging Galaxy Clusters

Although weak lensing (WL) is a powerful method to estimate a galaxy cluster mass without any dynamical assumptions, a model bias can arise when the cluster density profile departs from the assumed model profile. In a merging system, the bias is expected to become most severe because the constituent halos undergo significant structural changes. In this study, we investigate WL mass bias in binary cluster mergers using a suite of idealized hydrodynamical simulations. Realistic WL shear catalogs are generated by matching the source galaxy properties, such as intrinsic shape dispersion, measurement noise, source densities, etc., to those from Subaru and Hubble Space Telescope observations. We find that, with the typical mass–concentration (M–c) relation and the Navarro–Frenk–White profile, the halo mass bias depends on the time since the first pericenter passage and increases with the mass of the companion cluster. The time evolution of the mass bias is similar to that of the concentration, indicating that, to first order, the mass bias is modulated by the concentration change. For a collision between two ∼1015 M ⊙ clusters, the maximum bias amounts to ∼60%. This suggests that previous WL studies may have significantly overestimated the mass of the clusters in some of the most massive mergers. Finally, we apply our results to three merger cases: A2034, MACS J1752.0 + 4440, and ZwCl 1856.8 + 6616, and report their mass biases at the observed epoch, as well as their pre-merger masses, utilizing their merger shock locations as tracers of the merger phases.

Reconstruction of weak lensing mass maps for non-Gaussian studies in the celestial sphere

We present a novel method for reconstructing weak lensing mass or convergence maps as a probe to study non-Gaussianities in the cosmic density field. While previous surveys have relied on a flat-sky approximation, forthcoming Stage IV surveys will cover such large areas with a large field of view (FOV) to motivate mass reconstruction on the sphere. Here, we present an improved Kaiser-Squires (KS+) mass inversion method using a HEALPix pixelisation of the sphere while controlling systematic effects. As in the KS+ methodology, the convergence maps were reconstructed without noise regularisation to preserve the information content and allow for non-Gaussian studies. The results of this new method were compared with those of the Kaiser-Squires (KS) estimator implemented on the curved sky using high-resolution realistic N-body simulations. The quality of the method was evaluated by estimating the two-point correlation functions, third- and fourth-order moments, and peak counts of the reconstructed convergence maps. The effects of masking, sampling, and noise were tested. We also examined the systematic errors introduced by the flat-sky approximation. We show that the improved Kaiser-Squires on the sphere (SKS+) method systematically improves inferred correlation errors by ∼10 times and provides on average a 20–30 % better maximum signal-to-noise peak estimation compared to Kaiser-Squires on the sphere (SKS). We also show that the SKS+ method is nearly unbiased and reduces errors by a factor of about 2 and 4 in the third- and fourth-order moments, respectively. Finally, we show how the reconstruction of the convergence field directly on the celestial sphere eliminates the projection effects and allows the exclusion or consideration of a specific region of the sphere in the processing.

Combined strong and weak gravitational lensing mass measurements in clusters of galaxies

AbstractGravitational lensing in clusters of galaxies is one of the most powerful methods to probe the dark matter mass distribution inside such systems, after mapping the baryonic component, and test the currently accepted ɅCDM cosmological paradigm. With the advent of new high-resolution facilities such as the JWST, strong lensing (SL) is capable of providing extremely accurate mass measurements in the densest regions of such structures. Weak lensing (WL) provides complementary information by measuring the total mass distribution in the outskirts of galaxy clusters, where no multiple images of background sources are produced.In my talk, I will present updates on the WL mass reconstruction of the Frontier Fields galaxy cluster Abell 2744 (z = 0.308) based on Subaru, Magellan, and JWST data, and I will show how the results obtained, combined with accurate SL modeling of this lens, provide a consistent picture of the cluster total mass distribution. I will discuss the pipeline used for this work, the extensive checks performed on the different datasets and the scientific results obtained. Being composed of several substructures undergoing a merging process, the complex geometry of this cluster makes it an ideal laboratory to verify the consistency and reliability of the results obtained with the two methods. I will compare the predictions of the SL models extrapolated in the outer regions of the cluster with the non-parametric WL mass reconstruction to look for potential systematic effects affecting the SL analysis.

Extending empirical constraints on the SZ–mass scaling relation to higher redshifts via HST weak lensing measurements of nine clusters from the SPT-SZ survey at z ≳ 1

We present a Hubble Space Telescope (HST) weak gravitational lensing study of nine distant and massive galaxy clusters with redshifts 1.0 ≲ z ≲ 1.7 (zmedian = 1.4) and Sunyaev Zel’dovich (SZ) detection significance ξ > 6.0 from the South Pole Telescope Sunyaev Zel’dovich (SPT-SZ) survey. We measured weak lensing galaxy shapes in HST/ACS F606W and F814W images and used additional observations from HST/WFC3 in F110W and VLT/FORS2 in UHIGH to preferentially select background galaxies at z ≳ 1.8, achieving a high purity. We combined recent redshift estimates from the CANDELS/3D-HST and HUDF fields to infer an improved estimate of the source redshift distribution. We measured weak lensing masses by fitting the tangential reduced shear profiles with spherical Navarro-Frenk-White (NFW) models. We obtained the largest lensing mass in our sample for the cluster SPT-CL J2040−4451, thereby confirming earlier results that suggest a high lensing mass of this cluster compared to X-ray and SZ mass measurements. Combining our weak lensing mass constraints with results obtained by previous studies for lower redshift clusters, we extended the calibration of the scaling relation between the unbiased SZ detection significance ζ and the cluster mass for the SPT-SZ survey out to higher redshifts. We found that the mass scale inferred from our highest redshift bin (1.2 < z < 1.7) is consistent with an extrapolation of constraints derived from lower redshifts, albeit with large statistical uncertainties. Thus, our results show a similar tendency as found in previous studies, where the cluster mass scale derived from the weak lensing data is lower than the mass scale expected in a PlanckνΛCDM (i.e. νΛ cold dark matter) cosmology given the SPT-SZ cluster number counts.

An empirical method for mitigating an excess up-scattering mass bias on the weak lensing mass estimates for shear-selected cluster samples

Abstract An excess up-scattering mass bias on a weak lensing cluster mass estimate is a statistical bias that an observed weak lensing mass (Mobs) of a cluster of galaxies is, in a statistical sense, larger than its true mass (Mtrue) because of a higher chance of up-scattering than that of down-scattering due to random noises in a weak lensing cluster shear profile. This non-symmetric scattering probability is caused by a monotonically decreasing cluster mass function with increasing mass. We examine this bias (defined by b = Mobs/Mtrue) in weak lensing shear-selected clusters, and present an empirical method for mitigating it. In so doing, we perform the standard weak lensing mass estimate of realistic mock clusters, and find that the weak lensing mass estimate based on the standard χ2 analysis gives a statistically correct confidence intervals, but resulting best-fitting masses are biased high on average. Our correction method uses the framework of the standard Bayesian statistics with the prior of the probability distribution of the cluster mass and concentration parameter from recent empirical models. We test our correction method using mock weak lensing clusters, and find that the method works well with resulting corrected Mobs-bin averaged mass biases being close to unity within ${\sim}10\%$. We applied the correction method to weak lensing shear-selected cluster sample of Hamana, Shirasaki, and Lin (2020, PASJ, 72, 78), and present bias-corrected weak lensing cluster masses.

Dark Energy Survey Year 3 results: Cosmology with moments of weak lensing mass maps

We present a cosmological analysis using the second and third moments of the weak lensing mass (convergence) maps from the first three years of data (Y3) data of the Dark Energy Survey. The survey spans an effective area of 4139 square degrees and uses the images of over 100 million galaxies to reconstruct the convergence field. The second moment of the convergence as a function of smoothing scale contains information similar to standard shear 2-point statistics. The third moment, or the skewness, contains additional non-Gaussian information. The data is analyzed in the context of the ΛCDM model, varying five cosmological parameters and 19 nuisance parameters modeling astrophysical and measurement systematics. Our modeling of the observables is completely analytical, and has been tested with simulations in our previous methodology study. We obtain a 1.7% measurement of the amplitude of fluctuations parameter S8≡σ8(Ωm/0.3)0.5=0.784±0.013. The measurements are shown to be internally consistent across redshift bins, angular scales, and between second and third moments. In particular, the measured third moment is consistent with the expectation of gravitational clustering under the ΛCDM model. The addition of the third moment improves the constraints on S8 and Ωm by ∼15% and ∼25% compared to an analysis that only uses second moments. We compare our results with Planck constraints from the cosmic microwave background, finding a 2.2–2.8σ tension in the full parameter space, depending on the combination of moments considered. The third moment, independently, is in 2.8σ tension with Planck, and thus provides a cross-check on the analyses of 2-point correlations.13 MoreReceived 13 November 2021Accepted 30 August 2022DOI:https://doi.org/10.1103/PhysRevD.106.083509© 2022 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasCosmological parametersCosmologyGravitation, Cosmology & Astrophysics

Towards 1% accurate galaxy cluster masses: including baryons in weak-lensing mass inference

Galaxy clusters are a promising probe of late-time structure growth, but constraints on cosmology from cluster abundances are currently limited by systematics in their inferred masses. One unmitigated systematic effect in weak-lensing mass inference is ignoring the presence of baryons and treating the entire cluster as a dark matter halo. In this work we present a new flexible model for cluster densities that captures both the baryonic and dark matter profiles, a new general technique for calculating the lensing signal of an arbitrary density profile, and a methodology for stacking those lensing signal to appropriately model stacked weak-lensing measurements of galaxy cluster catalogues. We test this model on 1400 simulated clusters. Similarly to previous studies, we find that a dark matter-only model overestimates the average mass by 7.5%, but including our baryonic term reduces that to 0.7%. Since two more variables are marginalized over when we include our baryonic term the posteriors on the cluster mass calibration are larger than the dark matter-only model. Additionally, to mitigate the computational complexity of our model, we construct an emulator (surrogate model) which accurately interpolates our model for parameter inference, while being much faster to use than the raw model. We also provide an open-source software framework for our model and emulator, called maszcal, which will serve as a platform for continued efforts to improve these mass-calibration techniques. In this work, we detail our model, the construction of the emulator, and the tests which we used to validate that our model does mitigate bias. Lastly, we describe tests of the emulator's accuracy.

A major galaxy cluster merger caught by eROSITA: weak lensing mass distribution and kinematic description

ABSTRACT We present the weak lensing mass distribution of a triple merging cluster candidate at zphoto ∼ 0.36 belonging to a supercluster recently discovered during the eROSITA Performance Verification phase. Our analysis solved a previous tension in the merger classification by confirming that the cluster pair eFEDS J093513.3+004746 and eFEDS J093510.7+004910 is undergoing a major merger with a mass ratio $1.7_{-0.7}^{+0.5}$. According to our two-body kinematic description, the encounter happened $0.58_{-0.20}^{+0.15}$ Gyr ago, in a scenario that supports the observed radio relic position at the cluster outskirts. However, the same analysis showed that the companion cluster, eFEDS J093501.1+005418, is not gravitationally bound to the interacting system and therefore it is not part of the supercluster. We also checked the impact of adopting a scaling relation to determine the halo concentration c200. At the observed merger stage, where the clusters have travelled ∼55 per cent of the path to reach the apoapsis, the choice of c200 (whether from a scaling relation or a free parameter in the mass model) does not change significantly either the cluster masses or the kinematic description.

Optical selection bias and projection effects in stacked galaxy cluster weak lensing

ABSTRACT Cosmological constraints from current and upcoming galaxy cluster surveys are limited by the accuracy of cluster mass calibration. In particular, optically identified galaxy clusters are prone to selection effects that can bias the weak lensing mass calibration. We investigate the selection bias of the stacked cluster lensing signal associated with optically selected clusters, using clusters identified by the redMaPPer algorithm in the Buzzard simulations as a case study. We find that at a given cluster halo mass, the residuals of redMaPPer richness and weak lensing signal are positively correlated. As a result, for a given richness selection, the stacked lensing signal is biased high compared with what we would expect from the underlying halo mass probability distribution. The cluster lensing selection bias can thus lead to overestimated mean cluster mass and biased cosmology results. We show that the lensing selection bias exhibits a strong scale dependence and is approximately 20–60 per cent for ΔΣ at large scales. This selection bias largely originates from spurious member galaxies within ±20–60 $h^{-1}\, \rm Mpc$ along the line of sight, highlighting the importance of quantifying projection effects associated with the broad redshift distribution of member galaxies in photometric cluster surveys. While our results qualitatively agree with those in the literature, accurate quantitative modelling of the selection bias is needed to achieve the goals of cluster lensing cosmology and will require synthetic catalogues covering a wide range of galaxy–halo connection models.

The eROSITA Final Equatorial-Depth Survey (eFEDS)

Context.The eFEDS survey is a proof-of-concept mini-survey designed to demonstrate the survey science capabilities of SRG/eROSITA. It covers an area of 140 deg2where ~540 galaxy clusters have been detected out to a redshift of 1.3. The eFEDS field is partly embedded in the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) S19A data release, which covers ~510 deg2, containing approximately 36 million galaxies. This galaxy catalogue has been used to construct a sample of ~180 shear-selected galaxy clusters. The common area to both surveys covers about 90 deg2, making it an ideal region to study galaxy clusters selected in different ways.Aims.The aim of this work is to investigate the effects of selection methods in the galaxy cluster detection by comparing the X-ray selected, eFEDS, and the shear-selected, HSC-SSP S19A, galaxy cluster samples. There are 25 shear-selected clusters in the eFEDS fooprint.Methods.The relation between X-ray bolometric luminosity and weak-lensing mass is investigated (Lbol-Mrelation), comparing this relation derived from a shear-selected cluster sample to the relation obtained from an X-ray selected sample. Moreover, the dynamical state of the shear-selected clusters is investigated and compared to the X-ray selected sample using X-ray morphological parameters and galaxy distribution.Results.The normalisation of theLbol– M relation of the X-ray selected and shear-selected samples is consistent within 1σ-. Moreover, the dynamical state and merger fraction of the shear-selected clusters is not different from the X-ray selected ones. Four shear-selected clusters are undetected in X-rays. A close inspection reveals that one is the result of projection effects, while the other three have an X-ray flux below the ultimate eROSITA detection limit. Finally, 43% of the shear-selected clusters lie in superclusters.Conclusions.Our results indicate that the scaling relation between X-ray bolometric luminosity and true cluster mass of the shear-selected cluster sample is consistent with the eFEDS sample. There is no significant population of X-ray underluminous clusters, indicating that X-ray selected cluster samples are complete and can be used as an accurate cosmological probe.

The eROSITA Final Equatorial-Depth Survey (eFEDS)

We present the first weak-lensing mass calibration and X-ray scaling relations of galaxy clusters and groups selected in the eROSITA Final Equatorial Depth Survey (eFEDS) observed by Spectrum Roentgen Gamma/eROSITA over a contiguous footprint with an area of ≈140 deg2, using the three-year (S19A) weak-lensing data from the Hyper Suprime-Cam (HSC) Subaru Strategic Program survey. In this work, we study a sample of 434 optically confirmed galaxy clusters (and groups) at redshift 0.01 ≲z ≲1.3 with a median of 0.35, of which 313 systems are uniformly covered by the HSC survey to enable the extraction of the weak-lensing shear observable. In a Bayesian population modeling, we perform a blind analysis for the weak-lensing mass calibration by simultaneously modeling the observed count rateηand the shear profileg+of individual clusters through the count-rate-to-mass-and-redshift (η-M500-z) relation and the weak-lensing-mass-to-mass-and-redshift (MWL-M500-z) relation, respectively, while accounting for the bias in these observables using simulation-based calibrations. As a result, the count-rate-inferred and lensing-calibrated cluster mass is obtained from the joint modeling of the scaling relations, as the ensemble mass spanning a range of 1013h-1M⊙≲M500≲ 1015h-1M⊙with a median of ≈1014h-1M⊙for the eFEDS sample. With the mass calibration, we further model the X-ray observable-to-mass-and-redshift relations, including the rest-frame soft-band and bolometric luminosity (LXandLb), the emission-weighted temperatureTX, the mass of intra-cluster mediumMg, and the mass proxyYX, which is the product ofTXandMg. Except forLXwith a steeper dependence on the cluster mass at a statistically significant level, we find that the other X-ray scaling relations all show a mass trend that is statistically consistent with the self-similar prediction at a level of ≲1.7σ. Meanwhile, all these scaling relations show no significant deviation from the self-similarity in their redshift scaling. Moreover, no significant redshift-dependent mass trend is present. This work demonstrates the synergy between the eROSITA and HSC surveys in preparation for the forthcoming first-year eROSITA cluster cosmology.

Brightest cluster galaxies trace weak lensing mass bias and halo triaxiality in the three hundred project

ABSTRACT Galaxy clusters have a triaxial matter distribution. The weak-lensing signal, an important part in cosmological studies, measures the projected mass of all matter along the line of sight, and therefore changes with the orientation of the cluster. Studies suggest that the shape of the brightest cluster galaxy (BCG) in the centre of the cluster traces the underlying halo shape, enabling a method to account for projection effects. We use 324 simulated clusters at four redshifts between 0.1 and 0.6 from ‘The Three Hundred Project’ to quantify correlations between the orientation and shape of the BCG and the halo. We find that haloes and their embedded BCGs are aligned, with an average ∼20 degree angle between their major axes. The bias in weak lensing cluster mass estimates correlates with the orientation of both the halo and the BCG. Mimicking observations, we compute the projected shape of the BCG, as a measure of the BCG orientation, and find that it is most strongly correlated to the weak-lensing mass for relaxed clusters. We also test a 2D cluster relaxation proxy measured from BCG mass isocontours. The concentration of stellar mass in the projected BCG core compared to the total stellar mass provides an alternative proxy for the BCG orientation. We find that the concentration does not correlate to the weak-lensing mass bias, but does correlate with the true halo mass. These results indicate that the BCG shape and orientation for large samples of relaxed clusters can provide information to improve weak-lensing mass estimates.

Measuring weak lensing masses on individual clusters

ABSTRACT We present weak lensing mass estimates for a sample of 458 galaxy clusters from the redMaPPer Sloan Digital Sky Survey DR8 catalogue using Hyper Suprime-Cam weak lensing data. We develop a method to quickly estimate cluster masses from weak lensing shear and use this method to estimate weak lensing masses for each of the galaxy clusters in our sample. Subsequently, we constrain the mass–richness relation as well as the intrinsic scatter between the cluster richness and the measured weak lensing masses. When calculating the mass–richness relation for all clusters with a richness λ > 20, we find a tension in the slope of the mass–richness relation with the Dark Energy Survey Year 1 stacked weak lensing analysis. For a reduced sample of clusters with a richness λ > 40, our results are consistent with the Dark Energy Survey Year 1 analysis.

Likelihood-free Forward Modeling for Cluster Weak Lensing and Cosmology

Abstract Likelihood-free inference provides a rigorous approach to performing Bayesian analysis using forward simulations only. The main advantage of likelihood-free methods is their ability to account for complex physical processes and observational effects in forward simulations. Here we explore the potential of likelihood-free forward modeling for Bayesian cosmological inference using the redshift evolution of the cluster abundance combined with weak-lensing mass calibration. We use two complementary likelihood-free methods, namely Approximate Bayesian Computation (ABC) and Density-Estimation Likelihood-Free Inference (DELFI), to develop an analysis procedure for the inference of the cosmological parameters (Ωm, σ 8) and the mass scale of the survey sample. Adopting an eROSITA-like selection function and a 10% scatter in the observable–mass relation in a flat ΛCDM cosmology with Ωm = 0.286 and σ 8 = 0.82, we create a synthetic catalog of observable-selected Navarro–Frenk–White clusters in a survey area of 50 deg2. The stacked tangential shear profile and the number counts in redshift bins are used as summary statistics for both methods. By performing a series of forward simulations, we obtain convergent solutions for the posterior distribution from both methods. We find that ABC recovers broader posteriors than DELFI, especially for the Ωm parameter. For a weak-lensing survey with a source density of n g = 20 arcmin−2, we obtain posterior constraints on S 8 = σ 8 Ω m / 0.3 0.3 of 0.836 ± 0.032 and 0.810 ± 0.019 from ABC and DELFI, respectively. The analysis framework developed in this study will be particularly powerful for cosmological inference with ongoing cluster cosmology programs, such as the XMM–XXL survey and the eROSITA all-sky survey, in combination with wide-field weak-lensing surveys.

The effect of selection – a tale of cluster mass measurement bias induced by correlation and projection

ABSTRACT Cosmology analyses using galaxy clusters by the Dark Energy Survey have recently uncovered an issue of a previously unknown selection effect affecting weak-lensing mass estimates. In this letter, we use the Illustris-TNG simulation to demonstrate that selecting on galaxy counts induces a selection effect because of projection and correlation between different observables. We compute the weak-lensing-like projected mass estimations of dark matter haloes and examine their projected subhalo counts. In the two-dimensional (2D) projected space, haloes that are measured as more massive than truth have higher subhalo counts. Thus, projection along the line of sight creates cluster observables that are correlated with cluster mass measurement deviations, which in turn creates a mass measurement bias when the clusters are selected by this correlated observable. We demonstrate that the bias is predicted in a forward model using the observable-mass measurement correlation.

HSC-XXL: Baryon budget of the 136 XXL groups and clusters

Abstract We present our determination of the baryon budget for an X-ray-selected XXL sample of 136 galaxy groups and clusters spanning nearly two orders of magnitude in mass (M500 ∼ 1013–1015 M⊙) and the redshift range 0 ≲ z ≲ 1. Our joint analysis is based on the combination of Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) weak-lensing mass measurements, XXL X-ray gas mass measurements, and HSC and Sloan Digital Sky Survey multiband photometry. We carry out a Bayesian analysis of multivariate mass-scaling relations of gas mass, galaxy stellar mass, stellar mass of brightest cluster galaxies (BCGs), and soft-band X-ray luminosity, by taking into account the intrinsic covariance between cluster properties, selection effect, weak-lensing mass calibration, and observational error covariance matrix. The mass-dependent slope of the gas mass–total mass (M500) relation is found to be $1.29_{-0.10}^{+0.16}$, which is steeper than the self-similar prediction of unity, whereas the slope of the stellar mass–total mass relation is shallower than unity; $0.85_{-0.09}^{+0.12}$. The BCG stellar mass weakly depends on cluster mass with a slope of $0.49_{-0.10}^{+0.11}$. The baryon, gas mass, and stellar mass fractions as a function of M500 agree with the results from numerical simulations and previous observations. We successfully constrain the full intrinsic covariance of the baryonic contents. The BCG stellar mass shows the larger intrinsic scatter at a given halo total mass, followed in order by stellar mass and gas mass. We find a significant positive intrinsic correlation coefficient between total (and satellite) stellar mass and BCG stellar mass and no evidence for intrinsic correlation between gas mass and stellar mass. All the baryonic components show no redshift evolution.

Galaxy cluster number counts with individual lensing mass estimates: Forecasts for Euclid

The ΛCDM model is gradually becoming challenged by observational data. Upcoming cosmological surveys will increase the number of detected galaxy clusters by several orders of magnitude. Therefore, clusters will shortly provide precise cosmological constraints and improve our understanding of structure formation in the Universe. In the following, we present a cluster likelihood based on individual weak lensing mass estimates and forecast Euclid’s performances within this framework. We use a matched filter for weak lensing mass estimation and model its characteristics with a set of simulations. We use the Flagship N-body simulation to emulate the expected cluster mass distribution of a Euclid-like sample and test our statistical framework against it. Finally, we simultaneously constrain the observable-mass relation and the cosmological parameters.

Galaxy velocity bias in cosmological simulations: towards per cent-level calibration

ABSTRACT Galaxy cluster masses, rich with cosmological information, can be estimated from internal dark matter (DM) velocity dispersions, which in turn can be observationally inferred from satellite galaxy velocities. However, galaxies are biased tracers of the DM, and the bias can vary over host halo and galaxy properties as well as time. We precisely calibrate the velocity bias, bv – defined as the ratio of galaxy and DM velocity dispersions – as a function of redshift, host halo mass, and galaxy stellar mass threshold ($M_{\rm \star , sat}$), for massive haloes ($M_{\rm 200c}\gt 10^{13.5} \, {\rm M}_\odot$) from five cosmological simulations: IllustrisTNG, Magneticum, Bahamas + Macsis, The Three Hundred Project, and MultiDark Planck-2. We first compare scaling relations for galaxy and DM velocity dispersion across simulations; the former is estimated using a new ensemble velocity likelihood method that is unbiased for low galaxy counts per halo, while the latter uses a local linear regression. The simulations show consistent trends of bv increasing with M200c and decreasing with redshift and $M_{\rm \star , sat}$. The ensemble-estimated theoretical uncertainty in bv is 2–3 per cent, but becomes percent-level when considering only the three highest resolution simulations. We update the mass–richness normalization for an SDSS redMaPPer cluster sample, and find our improved bv estimates reduce the normalization uncertainty from 22 to 8 per cent, demonstrating that dynamical mass estimation is competitive with weak lensing mass estimation. We discuss necessary steps for further improving this precision. Our estimates for $b_v(M_{\rm 200c}, M_{\rm \star , sat}, z)$ are made publicly available.

Cosmological parameter estimation and inference using deep summaries

The ability to obtain reliable point estimates of model parameters is of crucial importance in many fields of physics. This is often a difficult task given that the observed data can have a very high number of dimensions. In order to address this problem, we propose a novel approach to construct parameter estimators with a quantifiable bias using an order expansion of highly compressed deep summary statistics of the observed data. These summary statistics are learned automatically using an information maximising loss. Given an observation, we further show how one can use the constructed estimators to obtain approximate Bayes computation (ABC) posterior estimates and their corresponding uncertainties that can be used for parameter inference using Gaussian process regression even if the likelihood is not tractable. We validate our method with an application to the problem of cosmological parameter inference of weak lensing mass maps. We show in that case that the constructed estimators are unbiased and have an almost optimal variance, while the posterior distribution obtained with the Gaussian process regression is close to the true posterior and performs better or equally well than comparable methods.

Weak-lensing Mass Reconstruction of Galaxy Clusters with a Convolutional Neural Network

Abstract We introduce a novel method for reconstructing the projected matter distributions of galaxy clusters with weak-lensing (WL) data based on a convolutional neural network (CNN). Training data sets are generated with ray-tracing through cosmological simulations. We control the noise level of the galaxy shear catalog such that it mimics the typical properties of the existing ground-based WL observations of galaxy clusters. We find that the mass reconstruction by our multilayered CNN with the architecture of alternating convolution and trans-convolution filters significantly outperforms the traditional reconstruction methods. The CNN method provides better pixel-to-pixel correlations with the truth, restores more accurate positions of the mass peaks, and more efficiently suppresses artifacts near the field edges. In addition, the CNN mass reconstruction lifts the mass-sheet degeneracy when applied to our projected cluster mass estimation from sufficiently large fields. This implies that this CNN algorithm can be used to measure the cluster masses in a model-independent way for future wide-field WL surveys.