Halo Clusters Research Articles

Topological bias: how haloes trace structural patterns in the cosmic web

ABSTRACT We trace the connectivity of the cosmic web as defined by haloes in the Planck-Millennium simulation using a persistence and Betti curve analysis. We normalize clustering up to the second-order correlation function and use our systematic topological analysis to correlate local information and properties of haloes with their multiscale geometrical environment of the cosmic web (elongated filamentary bridges and sheetlike walls). We capture the multiscale topology traced by the halo distribution through filtrations of the corresponding Delaunay tessellation. The resulting nested alpha shapes are sensitive to the local density, perfectly outline the local geometry, and contain the complete information on the multiscale topology. We find a remarkable linear relationship between halo masses and topology: haloes of different mass trace environments with different topological signature. This is a topological bias, an environmental structure bias independent of the halo clustering bias associated with the two-point correlation function. This mass-dependent linear scaling relation allows us to take clustering into account and determine the overall connectivity from a limited sample of galaxies. The presence of topological bias has major implications for the study of voids and filaments in the observed distribution of galaxies. The (infra)structure and shape of these key cosmic web components will strongly depend on the underlying galaxy sample. Their use as cosmological probes, with their properties influenced by cosmological parameters, will have to account for the subtleties of topological bias. This is of particular relevance with the large upcoming galaxy surveys such as DESI, Euclid, and the Vera Rubin telescope surveys.

A two-stage clustering ensemble algorithm applicable to risk assessment of railway signaling faults

Knowledge graph (KG) modeling constructs a connected network of hazard/fault events by drawing on historical reports, helping extract risk factors and propagation features in railway signaling safety. For the huge graph structure of the knowledge system, efficiently and accurately transforming the event information with text for risk level prediction is the crucial topic of this paper. To establish a quantitative risk assessment method based on KG modeling, we innovatively introduce text clustering technology to intelligently divide the entity short text data set in the KG, assign standardized entity names to the cluster partitions, and then complete the calculation and analysis according to the characteristic parameter formula, greatly reducing the labor and time consumption of data annotation and approximate text repetitive processing. Significantly, a two-stage clustering ensemble algorithm (TSCEA) integrating base clusterer optimization and hierarchical clustering prediction is proposed, whose innovative approach lies in describing sample similarity by the co-association matrix, while considering the contribution discrepancy of samples for decision-making. Specifically, Stage One selects and optimizes various base clusterers with different method kernels, while Stage Two emphasizes the contribution discrepancy of the cluster core and the cluster halo to make the final clustering decision, with the ensemble strategy serving as the bridge between these two. The KG established on field investigation is used to complete the experiment and analysis of the novel algorithm. Another clustering ensemble algorithm (based on a direct weighting strategy) and each base clusterer are applied to verify clustering performance, while the evaluation depends on external indicators. The results indicate that the proposed clustering ensemble algorithm outperforms others in various indicators, significantly improving clustering accuracy and robustness.

Taming assembly bias for primordial non-Gaussianity

Primordial non-Gaussianity of the local type induces a strong scale-dependent bias on the clustering of halos in the late-time Universe. This signature is particularly promising to provide constraints on the non-Gaussianity parameter f NL from galaxy surveys, as the bias amplitude grows with scale and becomes important on large, linear scales. However, there is a well-known degeneracy between the real prize, the f NL parameter, and the (non-Gaussian) assembly bias i.e., the halo formation history-dependent contribution to the amplitude of the signal, which could seriously compromise the ability of large-scale structure surveys to constrain f NL. We show how the assembly bias can be modeled and constrained, thus almost completely recovering the power of galaxy surveys to competitively constrain primordial non-Gaussianity. In particular, studying hydrodynamical simulations, we find that a proxy for the halo properties that determine assembly bias can be constructed from photometric properties of galaxies. Using a prior on the assembly bias guided by this proxy degrades the statistical errors on f NL only mildly compared to an ideal case where the assembly bias is perfectly known. The systematic error on f NL that the proxy induces can be safely kept under control.

The mass distribution in the outskirts of clusters of galaxies as a probe of the theory of gravity

We show that ς, the radial location of the minimum in the differential radial mass profile M′(r) of a galaxy cluster, can probe the theory of gravity. We derived M′(r) of the dark matter halos of galaxy clusters from N-body cosmological simulations that implement two different theories of gravity: standard gravity in the ΛCDM model, and f(R). We extracted 49 169 dark matter halos in 11 redshift bins in the range 0 ≤ z ≤ 1 and in three different mass bins in the range 0.9 < M200c/1014 h−1 M⊙ < 11. We investigated the correlation of ς with the redshift and the mass accretion rate (MAR) of the halos. We show that ς decreases from ∼3R200c to ∼2R200c when z increases from 0 to 1 in the ΛCDM model. At z ∼ 0.1, ς decreases from 2.8R200c to ∼2.5R200c when the MAR increases from ∼104 h−1 M⊙ yr−1 to ∼2 × 105 h−1 M⊙ yr−1. In the f(R) model, ς is ∼15% larger than in ΛCDM. The median test shows that for samples of ≳400 dark matter halos at z ≤ 0.8, ς is able to distinguish between the two theories of gravity with a p-value ≲10−5. Upcoming advanced spectroscopic and photometric programs will allow a robust estimation of the mass profile of enormous samples of clusters up to large clustercentric distances. These samples will allow us to statistically exploit ς as probe of the theory of gravity, which complements other large-scale probes.

Accurate halo mass functions from the simplest excursion set theory

ABSTRACT Excursion set theory is a powerful and widely used tool for describing the distribution of dark matter haloes, but it is normally applied with simplifying approximations. We use numerical sampling methods to study the mass functions predicted by the theory without approximations. With a spherical top-hat window and a constant δ = 1.5 threshold, the theory accurately predicts mass functions with the M200 mass definition, both unconditional and conditional, in simulations of a range of matter-dominated cosmologies. For Λ cold dark matter at the present epoch, predictions lie between the M200m and M200c mass functions. In contrast, with the same window function, a non-constant threshold based on ellipsoidal collapse predicts uniformly too few haloes. This work indicates a new way to simply and accurately evaluate halo mass functions, clustering bias, and assembly histories for a range of cosmologies. We provide a fitting function that accurately represents the predictions of the theory for a wide range of parameters.

Cluster halo shapes in CDM and SIDM models: unveiling the DM particle nature using a weak-lensing approach

ABSTRACT Self-interacting dark matter (SIDM) is an alternative to the standard collisionless cold dark matter model (CDM), allowing for interactions between the dark-matter particles through the introduction of a self-scattering cross-section. However, the observable effects between these two scenarios are hard to detect. In this work, we present a detailed analysis of an application of galaxy–galaxy lensing to measure with high precision the shapes of cluster haloes and how this approach can be used to obtain information regarding the nature of the dark-matter particle. Using two sets of simulated data, SIDM and CDM simulations, we compute stacked shear maps centred on several subsets of haloes with masses ≳1013.5 M⊙. From these maps, we obtain the quadrupole profiles related to the mean projected elongation of the particle distribution from which the shape parameters are derived. Accounting for a radial shape variation, this technique provides an enhancement of the observed differences between the simulated data sets. In particular, we obtain a higher slope of the power law for the shape-radial relation for the haloes identified in the SIDM simulation, which are rounder towards the centre. Also, as approaching to the mean virial radius, the projected semi-axis ratios converge to similar values than in the CDM simulation. Moreover, we account for the impact of the neighbouring mass, where more strongly elongated distributions are found for the haloes in the SIDM simulation, indicating that under dark matter self interaction, the large-scale structure imprints a more coherent accretion process.

Dynamical properties and detectability of the magneto-thermal instability in the intracluster medium

Context.Amongst the many plasma processes potentially relevant to the dynamics of the intracluster medium (ICM), turbulence driven at observable scales by internal magnetised buoyancy instabilities such as the magneto-thermal instability (MTI) stands out in the outskirts of the ICM, where the background temperature decreases with the radius.Aims.We characterise the statistical properties of MTI turbulence in the ICM and assess whether such large-scale magnetised plasma dynamics would be detectable with the future X-ray calorimeter X-IFU on board Athena.Methods.We made use of scaling laws previously derived to phenomenologically estimate the observable turbulent saturation levels and injection length of MTI turbulence for different ICM thermodynamic profiles, and performed a numerical magnetohydrodynamic simulation of the dynamics with Braginskii heat and momentum diffusion. As a prospective exercise, we used the simulation to virtually observe MTI turbulence through the X-IFU.Results.In bright enough regions amenable to X-ray observations, the MTI drives mild turbulence up to ∼5% and ∼100 km s−1(root-mean square temperature fluctuation and velocity). However, the measurable integrated temperature fluctuation and line-of-sight velocity fields, the latter being essentially the azimuthal velocity component in cluster haloes, hardly exceed 1% and 10 km s−1, respectively (root-mean square). We show that such moderate signals would be difficult to detect with upcoming X-ray telescopes. We also find that MTI turbulence is anisotropic in the direction of gravity and develops at scales ≳0.2 Mpc. If the fluctuation intensities were to be stronger than the current theoretical estimates, MTI fluctuations would be detectable and their anisotropy discernible with the X-IFU.Conclusions.Finding direct signatures of magnetised plasma dynamics in the ICM, even at observable scales typical of the fluid MTI, remains challenging. This study only marks a first step in this direction. Several numerical and observational strategies are discussed to make further progress in the future.

Graph model for the clustering of dark matter halos

Graph model for the clustering of dark matter halos

Exploring the origins of mega radio halos

We present a first attempt to investigate the origin of radio-emitting electrons in the newly discovered class of mega radio halos in clusters of galaxies. We study the evolution of relativistic electrons accreted by the external regions of a simulated cluster of galaxies at high resolution, including the effect of radiative losses and turbulent reacceleration acting on relativistic electrons. We conclude that turbulent reacceleration induced by structure formation, if sufficiently prolonged, has the potential to produce a large reservoir of radio-emitting electrons in the large regions illuminated by mega radio halos observed by LOFAR.

Exotic image formation in strong gravitational lensing by clusters of galaxies – IV. Elliptical NFW lenses and hyperbolic umbilics

ABSTRACT A source lying near a hyperbolic umbilic (HU) singularity leads to a ring-like image formation, constituting four images with high magnification factors and lying in a small region of the lens plane. Since (based on our earlier work) the observed number of HU image formations in cluster lenses is expected to increase in the future, it is timely to investigate them in more detail. Like fold and cusp singularities, HU also satisfies the magnification relation, i.e. the signed magnification sum of the four images equals zero. This work presents a detailed study of the HU magnification relation (Rhu) considering the elliptical Navarro–Frenk–White (eNFW) lens profile suitable for cluster scale dark matter haloes. Our results show that for an isolated eNFW lens, Rhu is more sensitive to ellipticity than its mass or concentration parameter. An ellipticity greater than 0.3 results in Rhu lying close to zero with a small scatter around it. A substructure near the HU image formation causes the average Rhu value to deviate from zero and increases the scatter, with the amount of deviation depending on the image type near which the substructure lies. However, a population of substructures in the lens plane (equivalent to the galaxies inside the cluster) does not significantly shift the average Rhu value from zero but increases the scatter around it. We find that Rhu ≃ 0 for HU image formation in the Abell 1703 cluster. Repeating this test in other clusters with HU formations can be a useful indicator of substructure in cluster haloes.

A Novel Clustering Method Based on Adjacent Grids Searching.

Clustering is used to analyze the intrinsic structure of a dataset based on the similarity of datapoints. Its widespread use, from image segmentation to object recognition and information retrieval, requires great robustness in the clustering process. In this paper, a novel clustering method based on adjacent grid searching (CAGS) is proposed. The CAGS consists of two steps: a strategy based on adaptive grid-space construction and a clustering strategy based on adjacent grid searching. In the first step, a multidimensional grid space is constructed to provide a quantization structure of the input dataset. The noise and cluster halo are automatically distinguished according to grid density. Moreover, the adaptive grid generating process solves the common problem of grid clustering, in which the number of cells increases sharply with the dimension. In the second step, a two-stage traversal process is conducted to accomplish the cluster recognition. The cluster cores with arbitrary shapes can be found by concealing the halo points. As a result, the number of clusters will be easily identified by CAGS. Therefore, CAGS has the potential to be widely used for clustering datasets with different characteristics. We test the clustering performance of CAGS through six different types of datasets: dataset with noise, large-scale dataset, high-dimensional dataset, dataset with arbitrary shapes, dataset with large differences in density between classes, and dataset with high overlap between classes. Experimental results show that CAGS, which performed best on 10 out of 11 tests, outperforms the state-of-the-art clustering methods in all the above datasets.

The VISCACHA survey

The chemical evolution history of the Small Magellanic Cloud (SMC) has been a matter of debate for decades. The challenges in understanding the SMC chemical evolution are related to a very slow star formation rate (SFR) combined with bursts triggered by the multiple interactions between the SMC and the Large Magellanic Cloud, a significant (∼0.5 dex) metallicity dispersion for the SMC cluster population younger than about 7.5 Gyr, and multiple chemical evolution models tracing very different paths through the observed age–metallicity relation of the SMC. There is no doubt that these processes were complex. Therefore, a step-by-step strategy is required in order to better understand the SMC chemical evolution. We adopted an existing framework to split the SMC into regions on the sky, and we focus on the west halo in this work, which contains the oldest and most metal-poor stellar populations and is moving away from the SMC, that is, in an opposite motion with respect to the Magellanic Bridge. We present a sample containing ∼60% of all west halo clusters to represent the region well, and we identify a clear age–metallicity relation with a tight dispersion that exhibits a 0.5 dex metallicity dip about 6 Gyr ago. We ran chemical evolution models and discuss possible scenarios to explain this metallicity dip, the most likely being a major merger accelerating the SFR after the event. This merger should be combined with inefficient internal gas mixing within the SMC and different SFRs in different SMC regions because the same metallicity dip is not seen in the AMR of the SMC combining clusters from all regions. We try to explain the scenario to better understand the SMC chemo-dynamical history.

Multiphase condensation in cluster haloes: interplay of cooling, buoyancy, and mixing

ABSTRACT Gas in the central regions of cool-core clusters and other massive haloes has a short cooling time (≲1 Gyr). Theoretical models predict that this gas is susceptible to multiphase condensation, in which cold gas is expected to condense out of the hot phase if the ratio of the thermal instability growth time-scale (tti) to the free-fall time (tff) is tti/tff ≲ 10. The turbulent mixing time tmix is another important time-scale: if tmix is short enough, the fluctuations are mixed before they can cool. In this study, we perform high-resolution (5122 × 768–10242 × 1536 resolution elements) hydrodynamic simulations of turbulence in a stratified medium, including radiative cooling of the gas. We explore the parameter space of tti/tff and tti/tmix relevant to galaxy and cluster haloes. We also study the effect of the steepness of the entropy profile, the strength of turbulent forcing and the nature of turbulent forcing (natural mixture versus compressive modes) on multiphase gas condensation. We find that larger values of tti/tff or tti/tmix generally imply stability against multiphase gas condensation, whereas larger density fluctuations (e.g. due to compressible turbulence) promote multiphase gas condensation. We propose a new criterion min (tti/min (tmix, tff)) ≲ c2 × exp (c1σs) for when the halo becomes multiphase, where σs denotes the amplitude of logarithmic density fluctuations and c1 ≃ 6, c2 ≃ 1.8 from an empirical fit to our results.

Binary Star Evolution in Different Environments: Filamentary, Fractal, Halo, and Tidal Tail Clusters

Using membership of 85 open clusters from previous studies based on Gaia Data Release 3 data, we identify binary candidates in the color–magnitude diagram for systems with mass ratio q > 0.4. The binary fraction is corrected for incompleteness at different distances due to the Gaia angular resolution limit. We find a decreasing binary fraction with increasing cluster age, with substantial scatter. For clusters with a total mass >200 M ⊙, the binary fraction is independent of cluster mass. The binary fraction depends strongly on stellar density. Among the four types of cluster environments, the lowest-density filamentary and fractal stellar groups have the highest mean binary fraction: 23.6% and 23.2%, respectively. The mean binary fraction in tidal tail clusters is 20.8% and is lowest in the densest halo-type clusters: 14.8%. We find clear evidence of early disruptions of binary stars in the cluster sample. The radial binary fraction depends strongly on the clustercentric distance across all four types of environments, with the smallest binary fraction within the half-mass radius r h and increasing toward a few r h. Only hints of mass segregation are found in the target clusters. The observed amounts of mass segregation are not significant enough to generate a global effect inside the target clusters. We evaluate the bias of unresolved binary systems (assuming a primary mass of 1 M ⊙) in 1D tangential velocity, which is 0.1–1 km s−1. Further studies are required to characterize the internal star cluster kinematics using Gaia proper motions.

Physical Evolution of Dark Matter Halo around the Depletion Boundary

We investigate the buildup of the halo profile out to large scale in a cosmological simulation, focusing on the roles played by the recently proposed depletion radii. We explicitly show that halo growth is accompanied by the depletion of the environment, with the inner depletion radius demarcating the two. This evolution process is also observed via the formation of a trough in the bias profile, with the two depletion radii identifying key scales in the evolution. The ratio between the inner depletion radius and the virial radius is approximately a constant factor of 2 across redshifts and halo masses. The ratio between their enclosed densities is also close to a constant of 0.18. These simple scaling relations reflect the largely universal scaled mass profile on these scales, which only evolves weakly with redshift. The overall picture of the boundary evolution can be broadly divided into three stages according to the maturity of the depletion process, with cluster halos lagging behind low-mass ones in the evolution. We also show that the traditional slow and fast accretion dichotomy of halo growth can be identified as accelerated and decelerated depletion phases, respectively.

Clash of Titans: The Impact of Cluster Mergers in the Galaxy Cluster Red Sequence.

Abstract Merging of galaxy clusters are some of the most energetic events in the Universe, and they provide a unique environment to study galaxy evolution. We use a sample of 84 merging and relaxed SPT galaxy clusters candidates, observed with the Dark Energy Camera in the 0.11 < z < 0.88 redshift range, to build colour-magnitude diagrams to characterize the impact of cluster mergers on the galaxy population. We divided the sample between relaxed and disturbed, and in two redshifts bin at z = 0.55. When comparing the high-z to low-z clusters we find the high-z sample is richer in blue galaxies, independently of the cluster dynamical state. In the high-z bin we find that disturbed clusters exhibit a larger scatter in the Red Sequence, with wider distribution and an excess of bluer galaxies compared to relaxed clusters, while in the low-z bin we find a complete agreement between the relaxed and disturbed clusters. Our results support the scenario in which massive cluster halos at z < 0.55 galaxies are quenched as satellites of another structure, i.e. outside the cluster, while at z ≥ 0.55 the quenching is dominated by in-situ processes.

The MillenniumTNG Project: high-precision predictions for matter clustering and halo statistics

ABSTRACT Cosmological inference with large galaxy surveys requires theoretical models that combine precise predictions for large-scale structure with robust and flexible galaxy formation modelling throughout a sufficiently large cosmic volume. Here, we introduce the millenniumTNG (MTNG) project which combines the hydrodynamical galaxy formation model of illustrisTNG with the large volume of the millennium simulation. Our largest hydrodynamic simulation, covering $(500 \, h^{-1}{\rm Mpc})^3 \simeq (740\, {\rm Mpc})^3$, is complemented by a suite of dark-matter-only simulations with up to 43203 dark matter particles (a mass resolution of $1.32\times 10^8 \, h^{-1}{\rm M}_\odot$) using the fixed-and-paired technique to reduce large-scale cosmic variance. The hydro simulation adds 43203 gas cells, achieving a baryonic mass resolution of $2\times 10^7 \, h^{-1}{\rm M}_\odot$. High time-resolution merger trees and direct light-cone outputs facilitate the construction of a new generation of semi-analytic galaxy formation models that can be calibrated against both the hydro simulation and observation, and then applied to even larger volumes – MTNG includes a flagship simulation with 1.1 trillion dark matter particles and massive neutrinos in a volume of $(3000\, {\rm Mpc})^3$. In this introductory analysis we carry out convergence tests on basic measures of non-linear clustering such as the matter power spectrum, the halo mass function and halo clustering, and we compare simulation predictions to those from current cosmological emulators. We also use our simulations to study matter and halo statistics, such as halo bias and clustering at the baryonic acoustic oscillation scale. Finally we measure the impact of baryonic physics on the matter and halo distributions.

Extratidal Members of Segue 3 are Rare and Difficult to Confirm

We simulate extratidal members of Segue 3, a sparse, faint, and small, ∼2.6 Gyr halo cluster, and investigate their observational detectability. Using the Gala package to simulate Segue 3's potential tidal tails, we find that the tails are narrow, linear, and around 4°–6° in length: the tails’ position angles and width are most sensitive to the uncertainties in the cluster's distance and mean proper motion. Post-processing the synthetic tail particles to assign realistic observational properties, we infer that Segue 3 would have close to 25 extra-tidal members with G ≤ 23, concentrated ≲1.°33 from the center of the cluster. The 11 candidate extratidal members identified by Fadely and collaborators are comparable in number, but significantly closer to the cluster center (d ∼ 4′) than these simulations predict. This analysis demonstrates the difficulty of identifying extratidal stars in the Milky Way's halo clusters, even in deep photometric surveys.

Deep Synoptic Array Science: Two Fast Radio Burst Sources in Massive Galaxy Clusters

The hot gas that constitutes the intracluster medium (ICM) has been studied at X-ray and millimeter/submillimeter wavelengths (Sunyaev–Zel’dovich effect) for decades. Fast radio bursts (FRBs) offer an additional method of directly measuring the ICM and gas surrounding clusters via observables such as dispersion measure (DM) and Faraday rotation measure. We report the discovery of two FRB sources detected with the Deep Synoptic Array whose host galaxies belong to massive galaxy clusters. In both cases, the FRBs exhibit excess extragalactic DM, some of which likely originate in the ICM of their respective clusters. FRB 20220914A resides in the galaxy cluster A2310 at z = 0.1125 with a projected offset from the cluster center of 520 ± 50 kpc. The host of a second source, FRB 20220509G, is an elliptical galaxy at z = 0.0894 that belongs to the galaxy cluster A2311 at the projected offset of 870 ± 50 kpc. These sources represent the first time an FRB has been localized to a galaxy cluster. We combine our FRB data with archival X-ray, Sunyaev–Zel'dovich (SZ), and optical observations of these clusters in order to infer properties of the ICM, including a measurement of gas temperature from DM and y SZ of 0.8–3.9 keV. We then compare our results to massive cluster halos from the IllustrisTNG simulation. Finally, we describe how large samples of localized FRBs from future surveys will constrain the ICM, particularly beyond the virial radius of clusters.

Galaxy clustering from the bottom up: a streaming model emulator I

ABSTRACT In this series of papers, we present a simulation-based model for the non-linear clustering of galaxies based on separate modelling of clustering in real space and velocity statistics. In the first paper, we present an emulator for the real-space correlation function of galaxies, whereas the emulator of the real-to-redshift space mapping based on velocity statistics is presented in the second paper. Here, we show that a neural network emulator for real-space galaxy clustering trained on data extracted from the dark quest suite of N-body simulations achieves sub-per cent accuracies on scales 1 < r < 30 $h^{-1} \, \mathrm{Mpc}$, and better than 3 per cent on scales r < 1 $h^{-1}\, \mathrm{Mpc}$ in predicting the clustering of dark-matter haloes with number density 10−3.5$(h^{-1}\, \mathrm{Mpc})^{-3}$, close to that of SDSS LOWZ-like galaxies. The halo emulator can be combined with a galaxy–halo connection model to predict the galaxy correlation function through the halo model. We demonstrate that we accurately recover the cosmological and galaxy–halo connection parameters when galaxy clustering depends only on the mass of the galaxies’ host halos. Furthermore, the constraining power in σ8 increases by about a factor of 2 when including scales smaller than 5 $h^{-1} \, \mathrm{Mpc}$. However, when mass is not the only property responsible for galaxy clustering, as observed in hydrodynamical or semi-analytic models of galaxy formation, our emulator gives biased constraints on σ8. This bias disappears when small scales (r < 10 $h^{-1}\, \mathrm{Mpc}$) are excluded from the analysis. This shows that a vanilla halo model could introduce biases into the analysis of future data sets.