Massive Clusters Research Articles

Co-moving groups around massive stars in the nuclear stellar disk

Context. Over the last ∼30 Myr, the nuclear stellar disk in the Galactic center has been the most prolific star-forming region of the Milky Way when averaged by volume. Remarkably, the combined mass of the only three clusters present today in the nuclear stellar disk adds up to only ∼10% of the total expected mass of young stars formed in this period. Several causes could explain this apparent absence of clusters and stellar associations. The stellar density in the area is so high that only the most massive clusters would be detectable against the dense background of stars. The extreme tidal forces reigning in the Galactic center could dissolve even the most massive of the clusters in just a few megayears. Close encounters with one of the massive molecular clouds, which are abundant in the nuclear stellar disk, can also rapidly make any massive cluster or stellar association dissolve beyond recognition. However, traces of some dissolving young clusters and associations could still be detectable as co-moving groups. Aims. It is our aim to identify so far unknown clusters or groups of young stars in the Galactic center. We focus our search on known, spectroscopically identified massive young stars to see whether their presence can pinpoint such structures. Methods. We created an algorithm to detect over-densities in the 5D space spanned by proper motions, positions on the plane of the sky, and line-of-sight distances, using reddening as a proxy for the distances. Since co-moving groups must be young in this environment, proper motions provide a good means to search for young stars in the Galactic center. As such, we combined publicly available data from three different surveys of the Galactic center, covering an area of ∼160 arcmin2 on the nuclear stellar disk. Results. We find four co-moving groups around massive stars, two of which are very close in position and velocity to the Arches’ most likely orbit. Conclusions. These co-moving groups are strong candidates to be clusters or associations of recently formed stars, showing that not all the apparently isolated massive stars are run-away former members of any of the three known clusters in the Galactic center or simply isolated massive stars. Our simulations show that these groups or clusters may dissolve beyond our limits of detection in less than ∼6 Myr.

COOL-LAMPS. VI. Lens Model and New Constraints on the Properties of COOL J1241+2219, a Bright z = 5 Lyman Break Galaxy and its z = 1 Cluster Lens

We present a strong lensing analysis of COOL J1241+2219, the brightest known gravitationally lensed galaxy at z ≥ 5, based on new multiband Hubble Space Telescope (HST) imaging data. The lensed galaxy has a redshift of z = 5.043, placing it shortly after the end of the “Epoch of Reionization,” and an AB magnitude z AB = 20.47 mag (Khullar et al.). As such, it serves as a touchstone for future research of that epoch. The high spatial resolution of HST reveals internal structure in the giant arc, from which we identify 15 constraints and construct a robust lens model. We use the lens model to extract the cluster mass and lensing magnification. We find that the mass enclosed within the Einstein radius of the z = 1.001 cluster lens is M(<5.″77)=1.079−0.007+0.023×1013M☉ , significantly lower than other known strong lensing clusters at its redshift. The average magnification of the giant arc is 〈μ arc〉 = 76−20+40 , a factor of 2.4−0.7+1.4 greater than previously estimated from ground-based data; the flux-weighted average magnification is 〈μ arc〉 = 92−31+37 . We update the current measurements of the stellar mass and star formation rate (SFR) of the source for the revised magnification to log(M⋆/M⊙)= 9.7 ± 0.3 and SFR = 10.3−4.4+7.0 M ⊙ yr−1, respectively. The powerful lensing magnification acting upon COOL J1241+2219 resolves the source and enables future studies of the properties of its star formation on a clump-by-clump basis. The lensing analysis presented here will support upcoming multiwavelength characterization with HST and JWST data of the stellar mass assembly and physical properties of this high-redshift lensed galaxy.

The Emergence of a Brightest Cluster Galaxy in a Protocluster Core at z = 2.24

We report the detection of a pair of massive quiescent galaxies likely in the process of merging at the center of the spectroscopically confirmed, extremely massive protocluster BOSS1244 at z = 2.24 ± 0.02. These galaxies, BOSS1244-QG1 and BOSS1244-QG2, were detected with Hubble Space Telescope grism slitless spectroscopic observations. These two quiescent galaxies are among the brightest member galaxies, with z = 2.223–2.255 in BOSS1244, and reside at redshifts z = 2.244 and z = 2.242, with a half-light radius of 6.76 ± 0.50 kpc and 2.72 ± 0.16 kpc, respectively. BOSS1244-QG1 and BOSS1244-QG2 are separated by a projected distance of about 70 physical kpc, implying that the two galaxies likely merge to form a massive brightest cluster galaxy (BCG) with size and mass similar to the most massive BCGs in the local Universe. We thus infer that BCG formation through dry major mergers may happen earlier than the full assembly of a cluster core, which broadens our previous understanding of the coevolution of mature galaxy clusters and BCGs in the nearby Universe. Moreover, we find a strong density–star formation relation over a scale of ∼18 comoving Mpc in BOSS1244, i.e., star formation activity decreases as density increases, implying that the quenching of star formation in BCGs and their progenitors is likely governed by environment-related processes before the virialization of the cluster core.

Identifying galaxy cluster mergers with deep neural networks using idealized Compton-y and X-ray maps

ABSTRACT We present a novel approach to identify galaxy clusters that are undergoing a merger using a deep learning approach. This paper uses massive galaxy clusters spanning 0 ≤ z ≤ 2 from The Three Hundred project, a suite of hydrodynamic resimulations of 324 large galaxy clusters. Mock, idealized Compton-y and X-ray maps were constructed for the sample, capturing them out to a radius of 2R200. The idealized nature of these maps mean they do not consider observational effects such as foreground or background astrophysical objects, any spatial resolution limits or restriction on X-ray energy bands. Half of the maps belong to a merging population as defined by a mass increase ΔM/M ≥ 0.75, and the other half serves as a controlled, relaxed population. We employ a convolutional neural network architecture and train the model to classify clusters into one of the groups. A best-performing model was able to correctly distinguish between the two populations with a balanced accuracy (BA) and recall of 0.77, ROC-AUC of 0.85, PR-AUC of 0.55, and F1 score of 0.53. Using a multichannel model relative to a single-channel model, we obtain a 3 per cent improvement in BA score, and a 6 per cent improvement in F1 score. We use a saliency interpretation approach to discern the regions most important to each classification decision. By analysing radially binned saliency values we find a preference to utilize regions out to larger distances for mergers with respect to non-mergers, greater than ∼1.2R200 and ∼0.7R200 for SZ and X-ray, respectively.

Risk factors for non-participation in ivermectin and dihydroartemisinin-piperaquine mass drug administration for malaria control in the MASSIV trial.

Mass Drug Administration (MDA) has become a mainstay for the control of several diseases over the last two decades. Successful implementation of MDA programmes requires community participation and can be threatened by systematic non-participation. Such concerns are particularly pertinent for MDA programmes against malaria, as they require multi-day treatment over several consecutive months. Factors associated with non-participation to the MDA campaign with ivermectin (IVM) and dihydroartemisinin-piperaquine (DHP) implemented within the MASSIV cluster randomized trial were determined. Coverage data was extracted from the MASSIV trial study database, with every datapoint being a directly observed therapy (DOT). A complete month of MDA was classified as receiving all three daily doses of treatment. For both ivermectin and DHP, ordinal logistic regression was used to identify individual and household level variables associated with non-participation. For ivermectin, 51.5% of eligible participants received all 3months of treatment while 30.7% received either one or two complete months. For DHP, 56.7% of eligible participants received all 3months of treatment and 30.5% received either one or two complete months. Children aged 5-15years and adults aged more than 50years were more likely to receive at least one complete month of MDA than working age adults, both for ivermectin (aOR 4.3, 95% CI 3.51-5.28 and aOR of 2.26, 95% CI 1.75-2.95) and DHP (aOR 2.47, 95%CI 2.02-3.02 and aOR 1.33, 95%CI 1.01-1.35), respectively. Members of households where the head received a complete month of MDA were more likely to themselves have received a complete month of MDA, both for ivermectin (aOR 1.71, 95%CI 1.35-2.14) and for DHP (aOR 1.64, 95%CI 1.33-2.04). Personal and household-level variables were associated with participation in the MDA programme for malaria control. Specific strategies to (increase participation amongst some groups may be important to ensure maximum impact of MDA strategies in achieving malaria elimination. The MASSIV trial is registered under NCT03576313.

Dynamic building thermal mass clustering for energy flexibility assessment: An application to demand response events

Demand response programs encompass a range of externally control strategies designed to modify consumer end-use load according to specific grid demands. In the current renewable integration context, power systems need to implement such demand strategies to provide energy flexibility during grid stress periods. Nevertheless, the extensive adoption of demand response initiatives in the building sector is confronted by notable obstacles, mainly due to the absence of standardized assessment methods and metrics, and the lack of established regulatory frameworks, all of which hinder the formation of competitive flexibility asset portfolios. Indeed, energy flexibility quantification frameworks are not unified and are usually based on the control objectives and quantification indicators. In this framework, this paper proposes a methodology to cluster residential buildings based on the analytical assessment of their dynamic thermal response, regardless the boundary conditions (i.e., weather data, occupancies, …) and the type of demand response event. The proposed methodology provides a quick and simple quantification of how a building is expected to respond under different demand response events and durations, which is critical for both customers and demand response agents to decide and select the involvement of buildings in each event and potentially to design personalized demand response events for each building.An extensive analysis was conducted to evaluate the methodology based on 28 real residential buildings, whose data were presented in a previous study. Results provide the potential effectiveness and application for energy flexibility purposes of this methodology based on dynamic thermal building clustering. Moreover, it can be concluded that it is not possible to deduce a thermal inertia available classification exclusively based on design thermal and geometric characteristics of the building; being necessary to consider the duration of involvement, since they highly influence on the residential building thermal behavior, and thus, on the corresponding clustering.

Mining the colossal patterns using ISSA based KMC with VGHHO clustering model for high dimensional data

High-dimensional datasets comprise a few rows but a huge total of features. The increased difficulty data scientists have in efficiently gleaning insights from high-dimensional large data is a direct outcome of this trend. Therefore, a K-Means clustering method (KMC) must be implemented to cleanse this data, with the centroid of KMC being ideally chosen by improved squirrel search algorithm (ISSA). The suggested algorithm features not one but two different types of searches: the leaping search and the progressive search. The linear regression selection strategy is utilised to automatically choose the applicable approach during the evolutionary phase; this increases SSA's stability. Harris Hawks Optimizer (HHO), which replicates the behaviour of a Harris hawk during rabbit predation, is applied to the cleaned data to cluster the massive pattern. However, HHO has problems with low accuracy and early convergence because of its inability to strike a good balance among exploitation. A new variant of HHO, dubbed velocity-guided HHO (VGHHO), including three improvements is proposed to address these drawbacks. By including a velocity operator and an inertia weight into the search equation, we are able to create a unique modified position search equation for use during the exploitation phase. Then, we incorporate a learning mechanism based on refraction and opposition to provide the promising resolutions and aid the swarm in escaping the local optimal solution. After the massive cluster has been built with VGHHO, uproot technology is used to uncover massive patterns. We run the tests on a wide variety of high-dimensional datasets and employ a number of different efficiency metrics. Evidence from these investigations shows that the proposed method produces high-quality mining results.

Searching for cold gas traced by MgII quasar absorbers in massive X-ray-selected galaxy clusters

Almost 50&lt;!PCT!&gt; of galaxies in the local Universe are in clusters or groups coexisting with both hot and cold gas components. In the present study, we observationally probed the cold-gas content of X-ray-selected massive galaxy clusters with spectroscopic redshift measured from the SDSS/SPIDERS survey. This paper focuses on the most massive structures: galaxy clusters with a mean mass of M$_ 500c $ M$_ odot We used a large number of background quasar optical spectra from SDSS DR16 to probe the diffuse T$=$10$^4$K gas in their intracluster medium. We first analysed a sample of spectra with known MgII absorbers, and then blindly stacked about 16\,000 archival spectra at the redshifts of the foreground galaxy clusters. We tentatively ($3.7 significance) detect MgII in the clusters with an equivalent width EW(MgII lambda 2796) of 0.056pm 0.015 corresponding to a column density of log N(MgII)/cm$^ We tested our methodology by generating 22\,000 mock SDSS spectra with MgII absorbers from Illustris-TNG50 cosmological magnetohydrodynamical simulations, combining photo-ionisation modelling and ray tracing. We also performed bootstrapping stacking at different cluster redshifts and stacked quasar spectra with no intervening clusters in the line of sight to measure the significance of our detection. These results are in line with the findings of recent, similar observational studies but challenge predictions from Illustris-TNG simulations. Together, our findings indicate that large amounts of cold gas may be found in the most massive structures of the Universe.

The Optical Properties of Galaxy Cluster Abell 2319

The optical photometric and spectroscopic investigations of the massive and merging galaxy cluster Abell 2319 (A2319) are presented here. RTT150 telescope of TÜBİTAK, Antalya, Türkiye used CCD imaging and spectroscopic observations. In this paper, 110 galaxies were determined in A2319 and defined as the magnitudes of the Bessel B and R filters in each cluster member galaxy. Spectral observations were done of the brightest cluster galaxy (BCG) and six additional brilliant galaxies. We estimated the Luminosity Function (LF) of galaxies for each filter. The resulting LF of cluster galaxies for each filter is well-fitted by the Double Schechter function. The best-fit parameter values derived as the characteristic absolute magnitudes are -21.08 ± 0.03, and -20.84 ± 0.01, -21.43 ± 0.02, and -20.54 ± 0.02, and the slopes at the faint end of the LF were -1.34 ± 0.04 and -1.12 ± 0.03, -1.47 ± 0.05 and -1.18 ± 0.03 for B and R filters, respectively.

Transport and Potential Sources Regions of Double High Pollution in Nanjing by Different Synoptic Situations

Based on the hourly concentration data of fine particulate matter （PM2.5） and ozone （O3） in Nanjing from 2015 to 2019， the synoptic situation that occurred in Nanjing， in which high PM2.5 and high O3 coexisted （hereinafter referred to as double high pollution （DHP））， was typed using T-mode principal component analysis. Additionally， the backward trajectory clustering analysis method， potential source contribution method （PSCF）， and concentration weight trajectory analysis method （CWT） were used to study the transport paths and potential source region distribution of the DHP of Nanjing by different synoptic situations. The synoptic situations favorable to the DHP in Nanjing were the control of weak low-pressure type （Type1） and high-pressure center （Type2）. Synoptic situations could have had an effect on the directional origin of the backward trajectory. In Type1， the Nanjing area was affected by two low pressures in the northeast and southwest， and the clustering trajectories of the Nanjing air mass mainly came from the eastern and western directions. The average concentrations of PM2.5 and O3 in the trajectory were 83.48 μg·m-3 and 106.85 μg·m-3， respectively. In Type 2， Nanjing and its surroundings were at the edge of the high-pressure center， and the air mass cluster trajectories mainly came from the north and east. The average concentrations of PM2.5 and O3 in the trajectory were 94.47 μg·m-3 and 92.32 μg·m-3， respectively. Most of the two types of backward trajectories belonged to short and medium-distance regional transportation， indicating that the pollution of neighboring provinces was one of the main factors affecting the DHP in Nanjing. PSCF and CWT analysis showed that the distribution of the most important potential sources of PM2.5 and O3 in Type1 and Type2 were not completely consistent， which indicates that the two pollutants did not come from the same area in the DHP.

Examining baryonic Faber–Jackson relation in galaxy groups

ABSTRACT We investigate the baryonic Faber–Jackson relation (BFJR), examining the correlation between baryonic mass and velocity dispersion in galaxy groups and clusters. Originally analysed in elliptical galaxies, the BFJR is derivable from the empirical radial acceleration relation (RAR) and MOdified Newtonian Dynamics (MOND), both showcasing a characteristic acceleration scale $\mathrm{g}_\mathrm{\dagger }=1.2\times 10^{-10}\, \mathrm{m}\, \mathrm{s}^{-2}$. Recent interpretations within MOND suggest that galaxy group dynamics can be explained solely by baryonic mass, hinting at a BFJR with g† in these systems. To explore this BFJR, we combined X-ray and optical measurements for 6 galaxy clusters and 13 groups, calculating baryonic masses by combining X-ray gas and stellar mass estimates. Simultaneously, we computed spatially resolved velocity dispersion profiles from membership data using the biweight scale in radial bins. Our results indicate that the BFJR in galaxy groups, using total velocity dispersion, aligns with MOND predictions. Conversely, galaxy clusters exhibit a parallel BFJR with a larger acceleration scale. Analysis using tail velocity dispersion in galaxy groups shows a leftward deviation from the BFJR. Additionally, stacked velocity dispersion profiles reveal two distinct types: declining and flat, based on two parallel BFJRs. The declining profile, if not due to the anisotropy parameters or the incomplete membership, suggests a deviation from standard dark matter (DM) density profiles. We further identify three galaxy groups with unusually low DM fractions.

Galaxy cluster mass bias from projected mass maps

The determination of the mass of galaxy clusters from observations is subject to systematic uncertainties. Beyond the errors due to instrumental and observational systematic effects, in this work we investigate the bias introduced by modelling assumptions. In particular, we consider the reconstruction of the mass of galaxy clusters from convergence maps employing spherical mass density models. We made use of THE THREE HUNDRED simulations, selecting clusters in the same redshift and mass range as the NIKA2 Sunyaev-Zel’dovich Large Programme sample: 3 ≤ M500/1014 M⊙ ≤ 10 and 0.5 ≤ z ≤ 0.9. We studied different modelling and intrinsic uncertainties that should be accounted for when using the single cluster mass estimates for scaling relations. We confirm that the orientation of clusters and the radial ranges considered for the fit have an important impact on the mass bias. The effect of the projection adds uncertainties to the order of 10–16% to the mass estimates. We also find that the scatter from cluster to cluster in the mass bias when using spherical mass models is less than 9% of the true mass of the clusters.

A Massive Protocluster Anchored by a Luminous Quasar at z = 6.63

Protoclusters, the progenitors of galaxy clusters, trace large scale structures in the early Universe and are important to our understanding of structure formation and galaxy evolution. To date, only a handful of protoclusters have been identified in the Epoch of Reionization. As one of the rarest populations in the early Universe, distant quasars that host active supermassive black holes are thought to reside in the most massive dark matter halos at that cosmic epoch and could thus potentially pinpoint some of the earliest protoclusters. In this Letter, we report the discovery of a massive protocluster around a luminous quasar at z = 6.63. This protocluster is anchored by the quasar and includes three [C ii] emitters at z ∼ 6.63, 12 spectroscopically confirmed Lyα emitters (LAEs) at 6.54 < z ≤ 6.64, and a large number of narrow-band-imaging selected LAE candidates at the same redshift. This structure has an overall overdensity of δ=3.3−0.9+1.1 within ∼35 × 74 cMpc2 on the sky and an extreme overdensity of δ > 30 in its central region (i.e., R ≲ 2 cMpc). We estimate that this protocluster will collapse into a galaxy cluster with a mass of 6.9−1.4+1.2×1015M⊙ at the current epoch, more massive than the most massive clusters known in the local Universe such as Coma. In the quasar vicinity, we discover a double-peaked LAE, which implies that the quasar has a UV lifetime greater than 0.8 Myrs and has already ionized its surrounding intergalactic medium.

The eROSITA Final Equatorial-Depth Survey (eFEDS): A machine learning approach to inferring galaxy cluster masses from eROSITA X-ray images

We have developed a neural network-based pipeline to estimate masses of galaxy clusters with a known redshift directly from photon information in X-rays. Our neural networks were trained using supervised learning on simulations of eROSITA observations, focusing on the Final Equatorial Depth Survey (eFEDS). We used convolutional neural networks that have been modified to include additional information on the cluster, in particular, its redshift. In contrast to existing works, we utilized simulations that include background and point sources to develop a tool that is directly applicable to observational eROSITA data for an extended mass range – from group size halos to massive clusters with masses in between 1013 M⊙ &lt; M &lt; 1015 M⊙. Using this method, we are able to provide, for the first time, neural network mass estimations for the observed eFEDS cluster sample from Spectrum-Roentgen-Gamma/eROSITA observations and we find a consistent performance with weak-lensing calibrated masses. In this measurement, we did not use weak-lensing information and we only used previous cluster mass information, which was used to calibrate the cluster properties in the simulations. When compared to the simulated data, we observe a reduced scatter with respect to luminosity and count rate based scaling relations. We also comment on the application for other upcoming eROSITA All-Sky Survey observations.

The 3D Kinematics of the Orion Nebula Cluster. II. Mass-dependent Kinematics of the Inner Cluster

We present the kinematic analysis of 246 stars within 4′ from the center of Orion Nebula Cluster (ONC), the closest massive star cluster with active star formation across the full mass range, which provides valuable insights in the formation and evolution of star cluster on an individual-star basis. High-precision radial velocities and surface temperatures are retrieved from spectra acquired by the NIRSPEC instrument used with adaptive optics (NIRSPAO) on the Keck II 10 m telescope. A 3D kinematic map is then constructed by combining with the proper motions previously measured by the Hubble Space Telescope Advanced Camera for Surveys/WFPC2/WFC3IR and Keck II NIRC2. The measured root-mean-squared velocity dispersion is 2.26 ± 0.08 km s−1, significantly higher than the virial equilibrium’s requirement of 1.73 km s−1, suggesting that the ONC core is supervirial, consistent with previous findings. Energy equipartition is not detected in the cluster. Most notably, the velocity of each star relative to its neighbors is found to be negatively correlated with stellar mass. Low-mass stars moving faster than their surrounding stars in a supervirial cluster suggests that the initial masses of forming stars may be related to their initial kinematic states. Additionally, a clockwise rotation preference is detected. A weak sign of inverse mass segregation is also identified among stars excluding the Trapezium stars, although it could be a sample bias. Finally, this study reports the discovery of four new candidate spectroscopic binary systems.

Magnetic Fields in the Central Molecular Zone Influenced by Feedback and Weakly Correlated with Star Formation

Magnetic fields of molecular clouds in the central molecular zone (CMZ) have been relatively under-observed at sub-parsec resolution. Here, we report JCMT/POL2 observations of polarized dust emission in the CMZ, which reveal magnetic field structures in dense gas at ∼0.5 pc resolution. The 11 molecular clouds in our sample include two in the western part of the CMZ (Sgr C and a farside cloud candidate), four around the Galactic longitude 0 (the 50 km s−1 cloud, CO 0.02−0.02, the Stone, and the Sticks and Straw among the Three Little Pigs), and five along the Dust Ridge (G0.253+0.016, clouds b, c, d, and e/f), for each of which we estimate the magnetic field strength using the angular dispersion function method. The morphologies of magnetic fields in the clouds suggest potential imprints of feedback from expanding H ii regions and young massive star clusters. A moderate correlation between the total viral parameter versus the star formation rate (SFR) and the dense gas fraction of the clouds is found. A weak correlation between the mass-to-flux ratio and the SFR, and a weak anticorrelation between the magnetic field and the dense gas fraction are also found. Comparisons between magnetic fields and other dynamic components in clouds suggest a more dominant role of self-gravity and turbulence in determining the dynamical states of the clouds and affecting star formation at the studied scales.

Comparing SCUBA-2 and ALMA Selections of Faint Dusty Star-forming Galaxies in A2744

We make a comparison of deep SCUBA-2 450 and 850 μm imaging on the massive lensing cluster field A2744 with Atacama Large Millimeter/submillimeter Array (ALMA) 1.2 mm data. Our primary goal is to assess how effective the wider-field SCUBA-2 sample, in combination with red JWST priors, is for finding faint dusty star-forming galaxies (DSFGs) compared to the much more expensive mosaicked ALMA observations. We cross-match our previously reported direct (>5σ) SCUBA-2 sample and red JWST NIRCam prior-selected (>3σ) SCUBA-2 sample to direct ALMA sources from the DUALZ survey. We find that roughly 95% are confirmed by ALMA. The red priors also allow us to probe deeper in the ALMA image. Next, by measuring the 450 and 850 μm properties of the full ALMA sample, we show that 46/69 of the ALMA sources are detected at 850 μm and 24/69 are detected at 450 μm in the SCUBA-2 images, with a total detection fraction of nearly 75%. All of the robust (>5σ) ALMA sources that are not detected in at least one SCUBA-2 band lie at 1.2 mm fluxes ≲0.6 mJy and are undetected primarily due to the higher SCUBA-2 flux limits. We also find that the SCUBA-2 detection fraction drops slightly beyond z = 3, which we attribute to the increasing 1.2 mm to 850 μm and 1.2 mm to 450 μm flux ratios combined with the ALMA selection. The results emphasize the power of combining SCUBA-2 data with JWST colors to map the faint DSFG population.

Mass bias in clusters of galaxies: Projection effects on the case study of Virgo replica

When measuring the observed pressure, density, or temperature profiles of the intracluster gas, and hence the mass of clusters of galaxies, projection effects or departures from the spherical symmetry hypothesis may induce biases. To estimate how strongly the cluster’s observed properties depend on the direction of observation, we use a constrained hydrodynamical simulation of the Virgo cluster that replicates the actual cluster of galaxies. In this case study, we analysed Virgo properties when projected in different directions, including along the Milky Way-Virgo axis, which mimics our observation direction. We compared the hydrostatic mass and the hydrostatic mass bias from the projection along the different observation directions to that derived from the 3D simulation. We show that projection effects impact the determination of Virgo mass. We particularly demonstrate that the mass and pressure along the line of sight correlate with the 2D- and 3D-deprojected electron density and pressure profiles intensity and thus impact the derived hydrostatic mass. We also show that the deviations to the hydrostatic equilibrium induced by pressure discontinuities within the cluster are emphasised by the deprojection process and thus make the hydrostatic mass estimation invalid at these radii.

The hydrostatic-to-lensing mass bias from resolved X-ray and optical-IR data

An accurate reconstruction of galaxy cluster masses is key to use this population of objects as a cosmological probe. In this work we present a study on the hydrostatic-to-lensing mass scaling relation for a sample of 53 clusters whose masses were reconstructed homogeneously in a redshift range between z = 0.05 and 1.07. The M500 mass for each cluster was indeed inferred from the mass profiles extracted from the X-ray and lensing data, without using a priori observable-mass scaling relations. We assessed the systematic dispersion of the masses estimated with our reference analyses with respect to other published mass estimates. Accounting for this systematic scatter does not change our main results, but enables the propagation of the uncertainties related to the mass reconstruction method or used dataset. Our analysis gives a hydrostatic-to-lensing mass bias of (1−b) = 0.739−0.070+0.075 and no evidence of evolution with redshift. These results are robust against possible subsample differences.

Goodbye to Chi by Eye: A Bayesian Analysis of Photometric Binaries in Six Open Clusters

We present a robust methodology for identifying photometric binaries in star clusters. Using Gaia DR3, Pan-STARRS, and Two Micron All Sky Survey data, we self-consistently define the cluster parameters and binary demographics for the open clusters (OCs) NGC 2168 (M35), NGC 7789, NGC 6819, NGC 2682 (M67), NGC 188, and NGC 6791. These clusters span in age from ∼200 Myr (NGC 2168) to more than ∼8 Gyr (NGC 6791) and have all been extensively studied in the literature. We use the Bayesian Analysis of Stellar Evolution software suite to derive the age, distance, reddening, metallicity, binary fraction, and binary mass-ratio posterior distributions for each cluster. We perform a careful analysis of our completeness and also compare our results to previous spectroscopic surveys. For our sample of main-sequence stars with masses between 0.6 and 1 M ⊙, we find that these OCs have similar binary fractions that are also broadly consistent with the field multiplicity fraction. Within the clusters, the binary fraction increases dramatically toward the cluster centers, likely a result of mass segregation. Furthermore nearly all clusters show evidence of mass segregation within the single and binary populations. The OC binary fraction increases significantly with cluster age in our sample, possibly due to a combination of mass-segregation and cluster-dissolution processes. We also find a hint of an anticorrelation between binary fraction and cluster central density as well as total cluster mass, possibly due to an increasing frequency of higher-energy close stellar encounters that inhibit long-period binary survival and/or formation.