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This document is an erratum to a previously published paper on weak lensing of cluster satellite galaxies. The erratum explains that there was a bug in the codes used for data analysis, resulting in underestimation of errorbars in some figures. The affected figures and tables are presented in the erratum, along with the updated values. The authors state that these changes do not impact their conclusions and qualitative inferences. The document includes tables presenting data on various parameters for different ranges, such as R_sat, M_clu, M_sat, M_bary, sigma_mc, and f_orp. The tables also compare constraints on the orphan fraction using different covariance estimation techniques, showing consistent results within errors. [Extracted from the article]

While collisionless cold dark matter models have been largely successful in explaining a wide range of observational data, some tensions still exist, and it remains possible that dark matter possesses a non-negligible level of self-interactions. In this paper, we investigate a possible observable consequence of self-interacting dark matter: offsets between the central galaxy and the centre of mass of its parent halo. We examine 23 relaxed galaxy clusters in a redshift range of 0.1–0.3 drawn from clusters in the Dark Energy Survey and the Sloan Digital Sky Survey which have archival Chandra X-ray data of sufficient depth for centre and relaxation determination. We find that most clusters in our sample show non-zero offsets between the X-ray centre, taken to be the centroid within the cluster core, and the central galaxy position. All of the measured offsets are larger, typically by an order of magnitude, than the uncertainty in the X-ray position due to Poisson noise. In all but six clusters, the measured offsets are also larger than the estimated, combined astrometric uncertainties in the X-ray and optical positions. A more conservative cut on concentration to select relaxed clusters marginally reduces but does not eliminate the observed offset. With our more conservative sample, we find an estimated median X-ray to central galaxy offset of |$\mu = 6.0 ^{+ 1.4}_{- 1.5}$| kpc. Comparing to recent simulations, this distribution of offsets is consistent with some level of dark matter self-interaction, though further simulation work is needed to place constraints. [ABSTRACT FROM AUTHOR]

This paper reports our discovery of the most massive supercluster, termed the King Ghidorah Supercluster (KGSc), at z = 0.50–0.64 in the Third Public Data Release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP PDR3) over 690 deg2, as well as an initial result for a galaxy and dark matter mapping. The primary structure of the KGSc comprises triple broad weak-lensing (WL) peaks over 70 comoving Mpc. Such extensive WL detection at z > 0.5 can only currently be achieved using the wide-field high-quality images produced by the HSC-SSP. The structure is also contiguous with multiple large-scale structures across a ∼400 comoving Mpc scale. The entire field has a notable overdensity (δ = 14.7 ± 4.5) of red-sequence clusters. Additionally, large-scale underdensities can be found in the foreground along the line of sight. We confirmed the overdensities in stellar mass and dark matter distributions to be tightly coupled and estimated the total mass of the main structure to be 1 × 1016 solar masses, according to the mock data analyses based on large-volume cosmological simulations. Further, upcoming wide-field multi-object spectrographs such as the Subaru Prime Focus Spectrograph may aid in providing additional insights into distant superclusters beyond the 100 Mpc scale. [ABSTRACT FROM AUTHOR]

The masses of galaxy clusters can be measured using data obtained exclusively from wide photometric surveys in one of two ways: directly from the amplitude of the weak lensing signal or, indirectly, through the use of scaling relations calibrated using binned lensing measurements. In this paper, we build on a recently proposed idea and implement an alternative method based on the radial profile of the satellite distribution. This technique relies on splashback, a feature associated with the apocentre of recently accreted galaxies that offers a clear window into the phase-space structure of clusters without the use of velocity information. We carry out this dynamical measurement using the stacked satellite distribution around a sample of luminous red galaxies in the fourth data release of the Kilo-Degree Survey and validate our results using abundance-matching and lensing masses. To illustrate the power of this measurement, we combine dynamical and lensing mass estimates to robustly constrain scalar–tensor theories of gravity at cluster scales. Our results exclude departures from General Relativity of the order of unity. We conclude the paper by discussing the implications for future data sets. Because splashback mass measurements scale only with the survey volume, stage-IV photometric surveys are well-positioned to use splashback to provide high-redshift cluster masses. [ABSTRACT FROM AUTHOR]

In this paper, we study the applicability of a set of supervised machine learning (ML) models specifically trained to infer observed related properties of the baryonic component (stars and gas) from a set of features of dark matter (DM)-only cluster-size haloes. The training set is built from the three hundred project that consists of a series of zoomed hydrodynamical simulations of cluster-size regions extracted from the 1 Gpc volume MultiDark DM-only simulation (MDPL2). We use as target variables a set of baryonic properties for the intracluster gas and stars derived from the hydrodynamical simulations and correlate them with the properties of the DM haloes from the MDPL2  N -body simulation. The different ML models are trained from this data base and subsequently used to infer the same baryonic properties for the whole range of cluster-size haloes identified in the MDPL2. We also test the robustness of the predictions of the models against mass resolution of the DM haloes and conclude that their inferred baryonic properties are rather insensitive to their DM properties that are resolved with almost an order of magnitude smaller number of particles. We conclude that the ML models presented in this paper can be used as an accurate and computationally efficient tool for populating cluster-size haloes with observational related baryonic properties in large volume N -body simulations making them more valuable for comparison with full sky galaxy cluster surveys at different wavelengths. We make the best ML trained model publicly available. [ABSTRACT FROM AUTHOR]

The paper presents the analysis of optically selected GAMA groups and clusters in the SRG/eROSITA X-ray map of eROSITA Final Equatorial Depth Survey, in the halo mass range 1013−5 × 1014 M⊙ and at z < 0.2. All X-ray detections have a clear GAMA counterpart, but most of the GAMA groups in the halo mass range 1013−1014 M⊙ remain undetected. We compare the X-ray surface brightness profiles of the eROSITA detected groups with the mean stacked profile of the undetected low-mass haloes at fixed halo mass. Overall, we find that the undetected groups exhibit less concentrated X-ray surface brightness, dark matter, and galaxy distributions with respect to the X-ray-detected haloes. The mean gas mass fraction profiles are consistent in the two samples within 1.5σ, indicating that the gas follows the dark matter profile. The low-mass concentration and the magnitude gap indicate that these systems are young. They reside with a higher probability in filaments while X-ray-detected groups favour the nodes of the Cosmic Web. Because of the lower central emission, the undetected systems tend to be X-ray underluminous at fixed halo mass and to lie below the LX − M halo relation. Interestingly, the X-ray-detected systems inhabiting the nodes scatter the less around the relation, while those in filaments tend to lie below it. We do not observe any strong relationship between the system X-ray appearance and the active galactic nucleus (AGN) activity. We cannot exclude the role of the past AGN feedback in affecting the gas distribution over the halo lifetime. However, the data suggests that the observed differences might be related to the halo assembly bias. [ABSTRACT FROM AUTHOR]

We present the measurement of total and stellar/dark matter decomposed mass density profile around a sample of galaxy groups and clusters with dynamical masses derived from integral-field stellar kinematics from the MaNGA survey in Paper I and weak lensing derived from the DECaLS imaging survey. Combining the two data sets enables accurate measurement of the radial density distribution from several kpc to Mpc scales. Intriguingly, we find that the excess surface density derived from stellar kinematics in the inner region cannot be explained by simply adding an NFW dark matter halo extrapolated from lensing measurement at a larger scale to a stellar mass component derived from the NASA-Sloan Atlas (NSA) catalogue. We find that a good fit to both data sets requires a stellar mass normalization about three times higher than that derived from the NSA catalogue, which would require an unrealistically too-heavy initial mass function for stellar mass estimation. If we keep the stellar mass normalization to that of the NSA catalogue but allow a varying inner dark matter density profile, we obtain an asymptotic slope of γgnfw =  |$1.82_{-0.25}^{+0.15}$| and γgnfw =  |$1.48_{-0.41}^{+0.20}$| for the group bin and the cluster bin, respectively, significantly steeper than the NFW case. We also compare the total mass inner density slopes with those from TNG300 and find that the values from the simulation are lower than the observation by about 2σ level. [ABSTRACT FROM AUTHOR]

The article titled "Correction to: Redshift drift and strong gravitational lensing" acknowledges a mistake made in a recent paper by the author. The mistake relates to the measurement of the Hubble constant using the difference in redshift between images of a gravitational-lens system. The author clarifies that the redshift difference can still be used to measure other cosmological parameters without knowledge of the Hubble constant. The rest of the paper remains unaffected, discussing various aspects of standard cosmology and gravitational lensing. No new data is associated with the article. [Extracted from the article]

The abundance of galaxy clusters is a sensitive probe to the amplitude of matter density fluctuations, the total amount of matter in the Universe as well as its expansion history. Inferring correct values and accurate uncertainties of cosmological parameters requires accurate knowledge of cluster abundance statistics, encoded in the likelihood function. In this paper, we test the accuracy of cluster abundance likelihoods used in the literature, namely the Poisson and Gaussian likelihoods as well as the more complete description of the Gauss–Poisson Compound likelihood. This is repeated for a variety of binning choices and analysis setups. In order to evaluate the accuracy of a given likelihood, this work compares individual posterior covariances to the covariance of estimators over the 1000 simulated dark matter halo catalogues obtained from PINOCCHIO algorithm. We find that for Rubin/ LSST and Euclid -like surveys the Gaussian likelihood gives robust constraints over a large range of binning choices. The Poisson likelihood, that does not account for sample covariance, always underestimates the errors on the parameters, even when the sample volume is reduced or only high-mass clusters are considered. We find no benefit in using the more complex Gauss–Poisson Compound likelihood as it gives essentially the same results as the Gaussian likelihood, but at a greater computational cost. Finally, in this ideal setup, we note only a small gain on the parameter error bars when using a large number of bins in the mass–redshift plane. [ABSTRACT FROM AUTHOR]

This paper explores the role of small-scale environment (<1 Mpc) in modulating accretion events on to supermassive black holes by studying the incidence of active galactic nuclei (AGNs) in massive clusters of galaxies. A flexible, data-driven semi-empirical model is developed based on a minimal set of parameters and under the zero-order assumption that the incidence of AGNs in galaxies is independent of environment. This is used to predict how the fraction of X-ray selected AGN among galaxies in massive dark matter haloes (⁠|$\gtrsim 3\times 10^{14}\, \mathrm{M}_{\odot }$|⁠) evolves with redshift and reveal tensions with observations. At high redshift, z ∼ 1.2, the model underpredicts AGN fractions, particularly at high X-ray luminosities, |$L_X(\rm 2\rm{-}10\, keV) \gtrsim 10^{44}\, erg \, s^{-1}$|⁠. At low redshift, z ∼ 0.2, the model estimates fractions of moderate luminosity AGN (⁠|$L_X(\rm 2\rm{-}10\, keV) \gtrsim 10^{43}\, erg \, s^{-1}$|⁠) that are a factor of 2–3 higher than the observations. These findings reject the zero-order assumption on which the semi-empirical model hinges and point to a strong and redshift-dependent influence of the small-scale environment on the growth of black holes. Cluster of galaxies appear to promote AGN activity relative to the model expectation at z ∼ 1.2 and suppress it close to the present day. These trends could be explained by the increasing gas content of galaxies towards higher redshift combined with an efficient triggering of AGNs at earlier times in galaxies that fall on to clusters. [ABSTRACT FROM AUTHOR]

As established in previous papers of this series, observables in highly distorted and magnified multiple images caused by the strong gravitational lensing effect can be used to constrain the distorting properties of the gravitational lens at the image positions. If the background source is extended and contains substructure, like star forming regions, which is resolved in multiple images, all substructure that can be matched across a minimum of three multiple images can be used to infer the local distorting properties of the lens. In this work, we replace the manual feature selection by an automated feature extraction based on SExtractor for Python and show its superior performance. Despite its aimed development to improve our lens reconstruction, it can be employed in any other approach, as well. Valuable insights on the definition of an 'image position' in the presence of noise are gained from our calibration tests. Applying it to observations of a five-image configuration in galaxy cluster CL0024 and the triple-image configuration containing Hamilton's object, we determine local lens properties for multiple wavebands separately. Within current confidence bounds, all of them are consistent with each other, corroborating the wavelength-independence of strong lensing and offering a tool to detect deviations caused by micro-lensing and dust in further examples. [ABSTRACT FROM AUTHOR]

In this paper, we explore the use of spatial clustering algorithms as a new computational approach for modelling the cosmic web. We demonstrate that such algorithms are efficient in terms of computing time needed. We explore three distinct spatial methods which we suitably adjust for (i) detecting the topology of the cosmic web and (ii) categorizing various cosmic structures as voids, walls, clusters, and superclusters based on a variety of topological and physical criteria such as the physical distance between objects, their masses, and local densities. The methods explored are (1) a new spatial method called Gravity Lattice ; (2) a modified version of another spatial clustering algorithm, the abacus ; and (3) the well known spatial clustering algorithm hdbscan. We utilize hdbscan in order to detect cosmic structures and categorize them using their overdensity. We demonstrate that the abacus method can be combined with the classic dtfe method to obtain similar results in terms of the achieved accuracy with about an order of magnitude less computation time. To further solidify our claims, we draw insights from the computer science domain and compare the quality of the results with and without the application of our method. Finally, we further extend our experiments and verify their effectiveness by showing their ability to scale well with different cosmic web structures that formed at different redshifts. [ABSTRACT FROM AUTHOR]

We demonstrate how the total luminosity in satellite galaxies is a powerful probe of dark matter haloes around central galaxies. The method cross-correlates central galaxies in spectroscopic galaxy samples with fainter galaxies detected in photometric surveys. Using models, we show that the total galaxy luminosity, L sat, scales linearly with host halo mass, making L sat an excellent proxy for M h. L sat is also sensitive to the formation time of the halo. We demonstrate that probes of galaxy large-scale environment can break this degeneracy. Although this is an indirect probe of the halo, it yields a high signal-to-noise ratio measurement for galaxies expected to occupy haloes at <1012 M⊙, where other methods suffer from larger errors. In this paper, we focus on observational and theoretical systematics in the L sat method. We test the robustness of our method of finding central galaxies and our methods of estimating the number of background galaxies. We implement this method on galaxies in the Sloan Digital Sky Survey (SDSS) data, with satellites identified in fainter imaging data. We find excellent agreement between our theoretical predictions and the observational measurements. Finally, we compare our L sat measurements to weak lensing estimates of M h for red and blue subsamples. In the stellar mass range where the measurements overlap, we find consistent results, where red galaxies live in larger haloes. However, the L sat approach allows us to probe significantly lower mass galaxies. At these masses, the L sat values are equivalent. This example shows the potential of L sat as a probe of dark haloes. [ABSTRACT FROM AUTHOR]