Cluster Candidates Research Articles

Bias and Deviation Map-Based Weighted Graph Search for NLOS Indoor RTLS Calibration

Recently, UWB-based technology providing centimeter-level accuracy has been developed and widely utilized in indoor real-time location tracking systems. However, location accuracy varies due to factors such as frequency interference, collisions, reflected signals, and whether line-of-sight (LOS) conditions are met, and it can be challenging to ensure high accuracy in specific environments. Fortunately, when anchor positions are fixed, the locations of large obstacles such as columns or furniture remain relatively stable, leading to similar patterns of positioning bias at specific points. This study proposes an algorithm that corrects inaccurate positioning to more closely reflect the actual location based on bias and deviation maps generated using natural neighbor interpolation. Initially, positioning bias and deviations at specific points are sampled, and bias and deviation maps are created using natural neighbor interpolation. During location tracking, the algorithm detects candidate clusters and determines the centroid to estimate the actual location by applying the bias and deviation maps to the measured positions derived through trilateration. To validate the proposed algorithm, experiments were conducted in a non-LOS (NLOS) indoor environment. The results demonstrate that the proposed algorithm can reduce the positioning bias of a UWB-based RTLS by approximately 71.34% compared to an uncalibrated system.

Prospects for Revealing Intermediate-mass Black Holes in NGC 1399 Using SKA

This study investigates the detectability of intermediate-mass black holes (IMBHs) within the mass range 102 M ⊙ ≤ M BH ≤ 105 M ⊙ in the globular star clusters of NGC 1399 at a frequency of 300.00 MHz. Employing the theoretical Bondi accretion model and the empirical fundamental plane (FP) of black hole accretion, we estimate IMBH masses based on bolometric luminosity and X-ray/radio luminosities, respectively. By simulating a 3 hr observation of 77 globular cluster (GC) candidates using the Square Kilometre Array, we identify radio detection benchmarks indicative of accretion onto IMBHs. Our results show that IMBHs inside the globular star clusters located in NGC 1399 are indeed detectable, with the Bondi accretion model providing IMBH mass estimates ranging from 2.93 × 103.0±0.39 M ⊙ to 7.43 × 104.0±0.39 M ⊙ and the empirical FP relation suggesting IMBH mass estimation with 3.41 × 105.0±0.96 M ⊙. These findings highlight the presence and detectability of IMBHs in GCs, offering insights into their role as precursors to supermassive black holes and enriching our understanding of black hole formation and evolution in astrophysical environments.

The ACT-DR5 MCMF galaxy cluster catalog

Galaxy clusters are useful cosmological probes and interesting astrophysical laboratories. As the cluster samples continue to grow in size, a deeper understanding of the sample characteristics and improved control of systematics becomes more crucial. For this analysis we created a new and larger ACT-DR5-based thermal Sunyaev–Zel’dovich Effect- (tSZE-) selected galaxy cluster catalog with improved control over sample purity and completeness. We employed the red sequence based cluster redshift and confirmation tool MCMF together with optical imaging data from the Legacy Survey DR-10 and infrared data from the WISE satellite to systematically identify true clusters from a new cluster candidate detection run on the ACT-DR5 dataset. The resulting ACT-DR5 MCMF sample contains 6,237 clusters with a residual contamination of 10.7%. This is an increase of 49% compared to the previous ACT-DR5 cluster catalog, making this new catalog the largest tSZE-selected cluster catalog to date. The zphot>1 subsample contains 703 clusters, three times more than in the previous ACT-DR5 catalog. Cross-matching the ACT-DR5 MCMF cluster catalog with a deeper tSZE sample from SPTpol 500d allows us to confirm the completeness and purity of the new ACT-DR5 MCMF sample. Cross-matching to the two largest X-ray-selected cluster samples, the all-sky RASS MCMF and the western Galactic hemisphere survey eRASS1, confirms the sample purity of the RASS MCMF sample and in the case of eROSITA eRASS1 reveals that 43% of the matched clusters are designated in eRASS1 as X-ray point sources rather than groups and clusters. Cross-correlating the ACT-DR5 MCMF cluster catalog with ACT-DR6 lensing maps results in a 16.4σ detection of Cosmic Microwave Background (CMB) lensing around the clusters, corresponding to the strongest signal found so far for a galaxy cluster sample. Repeating the measurement for the z > 1 cluster subsample yields a significance of 4.3σ, which is the strongest CMB lensing detection in a z>1 cluster sample to date.

JWST Observations of Starbursts: Massive Star Clusters in the Central Starburst of M82

We present a near-infrared (NIR) candidate star cluster catalog for the central kiloparsec of M82 based on new JWST NIRCam images. We identify star cluster candidates using the F250M filter, finding 1357 star cluster candidates with stellar masses >104 M ⊙. Compared to previous optical catalogs, nearly all (87%) of the candidates we identify are new. The star cluster candidates have a median intrinsic cluster radius of ≈1 pc and stellar masses up to 106 M ⊙. By comparing the color–color diagram to dust-free yggdrasil stellar population models, we estimate that the star cluster candidates have A V ∼ 3−24 mag, corresponding to A 2.5μm ∼ 0.3−2.1 mag. There is still appreciable dust extinction toward these clusters into the NIR. We measure the stellar masses of the star cluster candidates, assuming ages of 0 and 8 Myr. The slope of the resulting cluster mass function is β = 1.9 ± 0.2, in excellent agreement with studies of star clusters in other galaxies.

Selective multiple kernel fuzzy clustering with locality preserved ensemble

Multiple kernel fuzzy clustering (MKFC) has demonstrated promising performance in capturing the non-linear relationships within data. However, its effectiveness relies heavily on the appropriate selection of the fuzzification coefficient and kernel functions. To address this challenge, this paper proposes a novel clustering ensemble approach for improving the robustness and accuracy of the MKFC algorithm. The proposed method employs a multi-objective evolutionary optimization approach to heuristically select the optimal fuzzification and kernel coefficients. By employing the selected coefficients, the MKFC algorithm generates a diverse set of accurate candidate clustering results. Subsequently, a locality preserved ensemble mechanism is introduced to derive the final partition matrix, ensuring that all candidate clusterings within the Pareto non-dominated set contribute to the final consensus matrix. Moreover, this mechanism incorporates the knowledge about the locality of the dataset via a graph regularization term, thereby further enhancing the clustering performance. Comprehensive experiments conducted on widely adopted benchmark datasets demonstrate the superiority of the proposed method over the state-of-the-art approaches.

The SRG/eROSITA All-Sky Survey

The first SRG/eROSITA All-Sky Survey (eRASS1) provides the largest intracluster medium-selected galaxy cluster and group catalog covering the western Galactic hemisphere. Compared to samples selected purely on X-ray extent, the sample purity can be enhanced by identifying cluster candidates using optical and near-infrared data from the DESI Legacy Imaging Surveys. Using the red-sequence-based cluster finder eROMaPPer, we measured individual photometric properties (redshift zλ, richness λ, optical center, and BCG position) for 12000 eRASS1 clusters over a sky area of 13 116 deg2, augmented by 247 cases identified by matching the candidates with known clusters from the literature. The median redshift of the identified eRASS1 sample is z = 0.31, with 10% of the clusters at z > 0.72. The photometric redshifts have an accuracy of δz/(1 + z) ≲ 0.005 for 0.05 < z < 0.9. Spectroscopic cluster properties (redshift zspec and velocity dispersion σ) were measured a posteriori for a subsample of 3210 and 1499 eRASS1 clusters, respectively, using an extensive compilation of spectroscopic redshifts of galaxies from the literature. We infer that the primary eRASS1 sample has a purity of 86% and optical completeness >95% for z > 0.05. For these and further quality assessments of the eRASS1 identified catalog, we applied our identification method to a collection of galaxy cluster catalogs in the literature, as well as blindly on the full Legacy Surveys covering 24069 deg2. Using a combination of these cluster samples, we investigated the velocity dispersion-richness relation, finding that it scales with richness as log(λnorm) = 2.401 × log(σ) − 5.074 with an intrinsic scatter of δin = 0.10 ± 0.01 dex. The primary product of our work is the identified eRASS1 cluster catalog with high purity and a well-defined X-ray selection process, opening the path for precise cosmological analyses presented in companion papers.

The xenobiotic transporter ABCC4/MRP4 promotes epithelial mesenchymal transition in pancreatic cancer.

The xenobiotic transporter ABCC4/MRP4 is highly expressed in pancreatic ductal adenocarcinoma (PDAC) and correlates with a more aggressive phenotype and metastatic propensity. Here, we show that ABCC4 promotes epithelial-mesenchymal transition (EMT) in PDAC, a hallmark process involving the acquisition of mesenchymal traits by epithelial cells, enhanced cell motility, and chemoresistance. Modulation of ABCC4 levels in PANC-1 and BxPC-3 cell lines resulted in the dysregulation of genes present in the EMT signature. Bioinformatic analysis on several cohorts including tumor samples, primary patient-derived cultured cells, patient-derived xenografts, and cell lines, revealed a positive correlation between ABCC4 expression and EMT markers. We also characterized the ABCC4 cistrome and identified four candidate clusters in the distal promoter and intron one that showed differential binding of pro-epithelial FOXA1 and pro-mesenchymal GATA2 transcription factors in low ABCC4-expressing HPAF-II and high ABCC4-expressing PANC-1 xenografts. HPAF-II xenografts showed exclusive binding of FOXA1, and PANC-1 xenografts exclusive binding of GATA2, at ABCC4 clusters, consistent with their low and high EMT phenotype respectively. Our results underscore ABCC4/MRP4 as a valuable prognostic marker and a potential therapeutic target to treat PDAC subtypes with prominent EMT features, such as the basal-like/squamous subtype, characterized by worse prognosis and no effective therapies.

The contribution of silencer variants to human diseases

BackgroundAlthough disease-causal genetic variants have been found within silencer sequences, we still lack a comprehensive analysis of the association of silencers with diseases. Here, we profiled GWAS variants in 2.8 million candidate silencers across 97 human samples derived from a diverse panel of tissues and developmental time points, using deep learning models.ResultsWe show that candidate silencers exhibit strong enrichment in disease-associated variants, and several diseases display a much stronger association with silencer variants than enhancer variants. Close to 52% of candidate silencers cluster, forming silencer-rich loci, and, in the loci of Parkinson’s-disease-hallmark genes TRIM31 and MAL, the associated SNPs densely populate clustered candidate silencers rather than enhancers displaying an overall twofold enrichment in silencers versus enhancers. The disruption of apoptosis in neuronal cells is associated with both schizophrenia and bipolar disorder and can largely be attributed to variants within candidate silencers. Our model permits a mechanistic explanation of causative SNP effects by identifying altered binding of tissue-specific repressors and activators, validated with a 70% of directional concordance using SNP-SELEX. Narrowing the focus of the analysis to individual silencer variants, experimental data confirms the role of the rs62055708 SNP in Parkinson’s disease, rs2535629 in schizophrenia, and rs6207121 in type 1 diabetes.ConclusionsIn summary, our results indicate that advances in deep learning models for the discovery of disease-causal variants within candidate silencers effectively “double” the number of functionally characterized GWAS variants. This provides a basis for explaining mechanisms of action and designing novel diagnostics and therapeutics.

A multi-view ensemble clustering approach using joint entropy

Multi-view clustering can capture complementary and consistent information from different views, which is a core research topic in the fields of machine learning and pattern recognition. However, existing multi-view clustering methods ignore the quality of each base clustering cluster, which may affect the clustering performance. In this study, a multi-view ensemble clustering approach is proposed using joint entropy to evaluate the base clustering clusters. Firstly, an uncertainty index of base clustering clusters is defined using joint entropy which characterizes the importance and quality of each cluster. Secondly, a weighted co-association matrix is constructed using the uncertainty index, and useless entries are removed from the matrix, making the co-association matrix more reasonable. Thirdly, a candidate clusters selection strategy based on the stability index and a Multi-view Ensemble Clustering (MvEC-DoS) algorithm is proposed. In the end, experiments on five benchmark datasets validate the efficacy of our approach compared to other state-of-the-art methods.

The Galactic Center Lobe as an H ii Region

The Galactic center lobe (GCL) is an object ∼1° across that is located north of the Galactic center. In the mid-infrared (MIR) the GCL appears as two 8.0 μm filaments between which there is strong 24 μm and radio continuum emission. Due to its morphology and location in the sky, previous authors have argued that the GCL is located in the Galactic center region, created by outflows from star formation or by activity of the central black hole Sagittarius A*. In an associated paper, low-frequency radio emission indicates that the GCL must instead lie foreground to the Galactic center. If the GCL is foreground to the Galactic center, it is likely to be a type of object common throughout the Galactic disk; we here investigate whether its properties are similar to those of Galactic H ii regions. We find that the GCL’s MIR morphology, MIR flux densities, dust temperatures, and radio recombination line properties as traced by the Green Bank Telescope Diffuse Ionized Gas Survey are consistent with those of known Galactic H ii regions, although the derived electron temperature is low. We search for the ionizing source(s) of the possible H ii region and identify a stellar cluster candidate (Camargo #1092/Ryu & Lee #532) and a cluster of young stellar objects (the SPICY cluster G359.3+0.3) whose members have Gaia parallaxes distances of 1.7 ± 0.4 kpc. Taken together, the results of our companion paper and those shown here suggest that the GCL has properties consistent with those of an H ii region located ∼2 kpc from the Sun.

Statistical and density-based clustering of geographical flows for crowd movement patterns recognition

With the rapid development of sensors and communication technologies, it has become easy to collect large-scale and long-term crowd movement positioning data, which brings new opportunities for studying crowd movement patterns. This paper proposes a novel Statistical and Density-Based Clustering algorithm (SDBC) to identify implicit significant spatial aggregation patterns in geographical flow data. Unlike existing flow clustering algorithms, this method identifies the hot spots of origin-destination (OD) flows based on local spatial statistics and density-growing clustering. It also evaluates the significance of the identified geographic flow clusters, effectively reducing the identification of spurious clusters generated by chance in data. In our method, the spatial neighborhood of each flow is first obtained based on spatial proximity, temporal similarity, and directional similarity. Then, the number of flows in the spatial neighborhood of each flow is calculated and used as the density measure. Based on this, high-density flows are automatically detected using local spatial aggregation statistics, and a hierarchical density-based clustering strategy is developed to merge adjacent high-density flows to generate candidate flow clusters. Finally, we perform permutation tests to infer the statistical significance of each flow cluster and eliminate the candidate clusters generated by chance. Experiments on synthetic data and real-world taxi trajectory data were conducted to evaluate the effectiveness of the proposed method. Results show that the proposed method can accurately identify the statistically significant flow clusters of different shapes and densities and performs better than the available state-of-the-art flow clustering algorithms.

AMICO-COSMOS galaxy cluster and group catalogue up to z = 2: Sample properties and X-ray counterparts

Aims. We present the results of a new galaxy cluster search in the COSMOS field obtained using the Adaptive Matched Identifier of Clustered Objects (AMICO). Our aim was to produce a new cluster and group catalogue up to z = 2 by performing an innovative application of AMICO with respect to previous successful applications to wide-field surveys in terms of depth (down to r < 26.7), small area covered (∼1.69 deg2 of unmasked effective area), and redshift extent. This sample and the comparative analysis we performed with the X-rays, allowed for the calibration of mass-proxy scaling relations up to z = 2 and down to less than 1013 M⊙, and constitutes the basis for the refinement of the cluster model for future applications of AMICO, such as the analysis of upcoming Euclid data. Methods. The AMICO algorithm is based on an optimal linear matched filter and detects clusters in photometric galaxy catalogues using galaxy location, photometric redshift and, in the simplest case, one galaxy property. We chose to use a single magnitude as the galaxy property, avoiding the explicit use of galaxy colour for the selection of clusters. We used three different magnitudes by performing three independent runs in the r-, Y-, and H-bands using both COSMOS2020 and COSMOS2015 galaxy catalogues. We created a composite visibility mask and cluster models for the signal to detect, and we estimated the noise directly from the data. Results. We performed a matching of the catalogues resulting from the three runs and merged them to produce a final catalogue that contains 1269 and 666 candidate clusters and groups with S/N > 3.0 and > 3.5, respectively. A total of 490 candidates are detected in all three runs. Most of the detections unmatched between runs have S/N < 3.5, which can be set as a threshold for selecting a more robust sample. We assigned X-ray properties to our detections by matching the catalogue with a public X-ray selected group sample and by estimating, for unmatched detections, the X-ray properties at the location of AMICO candidates using Chandra+XMM-Newton data. There are in total 622 candidate clusters and groups with an X-ray flux estimate. This large sample of candidates with X-ray properties allowed the calibration of the scaling relations between two AMICO mass-proxies (richness and cluster amplitude) and X-ray mass and the study of their redshift dependence for the selection of the most stable photometric bands.

A Type Ia Supernova near a Globular Cluster in the Early-type Galaxy NGC 5353

No progenitor of a Type Ia supernova (SN Ia) is known, but in old-population early-type galaxies, one may find SNe Ia associated with globular clusters, yielding a population age and metallicity. It also provides insight into the formation path and the SN enhancement rate in globular clusters. We sought to find such associations and identified SN 2019ein to be within the ground-based optical positional uncertainty of a globular cluster candidate within the early-type galaxy NGC 5353 at D ≈ 30 Mpc. We reduced the positional uncertainties by obtaining Hubble Space Telescope images with the Advanced Camera for Surveys, using filters F475W and F814W obtained in 2020 June. We find that the globular cluster candidate has a magnitude, color, and angular extent that are consistent with it being a typical globular cluster. The separation between the globular cluster and SN 2019ein is 0.″43, or 59 pc in projection. The chance occurrence with a random globular cluster is ≈3%, favoring but not proving an association. If the SN progenitor originated in the globular cluster, one scenario is that SN 2019ein was previously a double-degenerate white dwarf binary that was dynamically ejected from the globular cluster and exploded within 10 Myr; models do not predict this to be common. Another, but less likely scenario is where the progenitor remained bound to the globular cluster, allowing the double-degenerate binary to inspiral on a much longer timescale before producing an SN.

The Massive and Distant Clusters of WISE Survey 2: Equatorial First Data Release

The Massive and Distant Clusters of WISE Survey 2 (MaDCoWS2) is a new survey designed as the successor of the original MaDCoWS survey. MaDCoWS2 improves upon its predecessor by using deeper optical and infrared data and a more powerful detection algorithm (PZWav). As input to the search, we use grz photometry from the DECam Legacy Survey (DECaLS) in combination with W1 and W2 photometry from the CatWISE2020 catalog to derive the photometric redshifts with full redshift probability distribution functions for Wide-field Infrared Survey Explorer (WISE)-selected galaxies. Cluster candidates are then detected using the PZWav algorithm to find three-dimensional galaxy overdensities from the sky positions and photometric redshifts. This paper provides the first MaDCoWS2 data release, covering 1461 (1838 without masking) deg2 centered on the Hyper-SuprimeCam Subaru Strategic Program equatorial fields. Within this region, we derive a catalog of 22,970 galaxy cluster candidates detected at a signal-to-noise ratio (S/N) > 5. These clusters span the redshift range 0.1 < z < 2, including 1312 candidates at z > 1.5. We compare MaDCoWS2 to six existing catalogs in the area. We rediscover 60%–92% of the clusters in these surveys at S/N > 5. The medians of the absolute redshift offset are <0.02 relative to these surveys, while the standard deviations are less than 0.06. The median offsets between the detection position from MaDCoWS2 and other surveys are less than 0.25 Mpc. We quantify the relation between S/N and gas mass, total mass, luminosity, and richness from other surveys using a redshift-dependent power law relation. We find that the S/N-richness relation exhibits the lowest scatter.

Partitioned uneven cluster routing algorithm based on gray wolf optimization in WSNs

WSNs have various uses across numerous industries and are one of the essential technologies of modern life. Energy consumption is the issue that has drawn the greatest attention and still has to be resolved because the nodes that comprise WSNs have a limited amount of energy. Numerous factors influence energy consumption, and our algorithm design considerations are centered on extending the network lifetime and energy efficiency through the resolution of imbalance and hotspot issues related to WSNs clustering. Because of this, we suggest a partitioned uneven cluster routing algorithm based on gray wolf optimization. To find the ideal cluster head, we first divide the network into areas with distinct important influence factors, then we improve the final cluster head election function and the candidate cluster head competition radius. Subsequently, to reduce the energy consumption resulting from multiple rounds of clustering, similarity determination is introduced. Finally, the optimal transmission path in the multi-hop process is obtained by combining the Gray Wolf optimization algorithm with the relay node selection function. Simulation results show that the network lifetime of the proposed algorithm is extended by 54.6 %, 46.2 %, 58.6 %, and 18.5 % compared to LEACH, DEBUC, LEACH-EDP, and LEACH-IM, respectively. The energy efficiency of the proposed algorithm is extended by 40.8 %, 7.1 %, 22.7 %, and 34.0 %, respectively. The proposed algorithm significantly extends the network lifetime and improves the energy efficiency of the network.

Searching for Hypercompact Star Clusters in the Milky Way Using LAMOST and Gaia

During the early merger of the Milky Way, intermediate-mass black holes (BHs) in merged dwarf galaxies may have been ejected from the center of their host galaxies due to gravitational waves, carrying some central stars along. This process can lead to the formation of hypercompact star clusters, potentially hosting BHs in the mass range of 104–105 solar masses. These clusters are crucial targets for identifying and investigating intermediate-mass BHs. However, no hypercompact star clusters in the Milky Way have been identified so far. In this paper, taking advantage of the high spatial resolution power of Gaia, we used data from Gaia Early Data Release (EDR) 3 and Large-Area Multi-Object Fiber Optic Spectroscopic Telescope Data Release 7, along with additional data from Pan-STARRS and the Sloan Digital Sky Survey, to conduct an initial screening of 6,138,049 sources using various parameters of Gaia EDR3. A total of 4786 sources were selected for in-depth analysis. Each of these sources was meticulously scrutinized by examining their images, spectra, and nearby celestial objects to exclude various false positives, such as contaminations, galaxies, wide binaries, or wrong matches. We finally identified one likely hypercompact star cluster candidate in the Milky Way, laying the foundation for further high-resolution imaging and spectral verification.

Spectroscopic evidence of a possible young stellar cluster at the Galactic Center

Context. The nuclear stellar disk has been the most prolific star-forming region in the Milky Way over the past ∼30 million years. Notably, the cumulative mass of the three clusters currently found in the nuclear stellar disk, the Quintuplet, the Arches, and the Nuclear clusters, amounts to just 10% of the total anticipated mass of young stars that formed in this period. This discrepancy, known as the missing cluster problem, is attributed to factors such as high stellar density and tidal forces. Traces of dissolving clusters may exist as comoving groups of stars, providing insights into the star formation history of the region. Recently, a new cluster candidate associated with an HII region was reported through the analysis of kinematic data Aims. Our aim is to determine whether the young and massive stellar objects in the region share proper motion, positions in the plane of the sky, and line-of-sight distances. We use reddening as a proxy for the distances. Methods. We reduced and analyzed integral field spectroscopy data from the KMOS instrument at the ESO VLT to locate possible massive young stellar objects in the field. Then, we identified young massive stars with astrophotometric data from the two different catalogs to analyze their extinction and kinematics. Results. We present a group of young stellar objects that share velocities, are close together in the plane of the sky, and are located at a similar depth in the nuclear stellar disk. Conclusions. The results presented here offer valuable insights into the missing clusters problem. They indicate that not all young massive stars in the Galactic center form in isolation; some of them seem to be the remnants of dissolved clusters or stellar associations.

The Gaia-ESO Survey: Calibrating the lithium–age relation with open clusters and associations

Context. The Li abundance observed in pre-main sequence and main sequence late-type stars is strongly age-dependent, but also shows a complex pattern depending on several parameters, such as rotation, chromospheric activity, and metallicity. The best way to calibrate these effects, and with the aim of studying Li as an age indicator for FGK stars, is to calibrate coeval groups of stars, such as open clusters (OCs) and associations. Aims. We present a considerable target sample of 42 OCs and associations – with an age range from 1 Myr to 5 Gyr – observed within the Gaia-ESO survey (GES), and using the latest data provided by GES iDR6 and the most recent release of Gaia that was then available, EDR3. As part of this study, we update and improve the membership analysis for all 20 OCs presented in our previous article. Methods. We perform detailed membership analyses for all target clusters to identify likely candidates, using all available parameters provided by GES, complemented with detailed bibliographical searches, and based on numerous criteria: from radial velocity distributions, to the astrometry (proper motions and parallaxes) and photometry provided by Gaia, to gravity indicators (log g and the γ index), [Fe/H] metallicity, and Li content in diagrams of (Li equivalent widths) EW(Li) versus Teff. Results. We obtain updated lists of cluster members for the whole target sample, as well as a selection of Li-rich giant contaminants obtained as an additional result of the membership process. Each selection of cluster candidates was thoroughly contrasted with numerous existing membership studies using data from Gaia to ensure the most robust results. Conclusions. These final cluster selections will be used in the third and last paper of this series, which reports the results of a comparative study characterising the observable Li dispersion in each cluster and analysing its dependence on several parameters, allowing us to calibrate a Li–age relation and obtain a series of empirical Li envelopes for key ages in our sample.

BSEC Method for Unveiling Open Clusters and its Application to Gaia DR3: 83 New Clusters

Open clusters (OCs) are common in the Milky Way, but most of them remain undiscovered. There are numerous techniques, including some machine-learning algorithms, available for the exploration of OCs. However, each method has its limitations and therefore, different approaches to discovering OCs hold significant values. We develop a comprehensive approach method to automatically explore the data space and identify potential OC candidates with relatively reliable membership determination. This approach combines the techniques of Hierarchical Density-Based Spatial Clustering of Applications with Noise, Gaussian mixture model, and a novel cluster member identification technique, color excess constraint. The new method exhibits efficiency in detecting OCs while ensuring precise determination of cluster memberships. Because the main feature of this technique is to add an extra constraint (EC) for the members of cluster candidates using the homogeneity of color excess, compared to typical blind search codes, it is called Blind Search-Extra Constraint (BSEC) method. It is successfully applied to the Gaia Data Release 3, and 83 new OCs are found, whose color–magnitude diagrams (CMDs) are fitted well to the isochrones. In addition, this study reports 621 new OC candidates with discernible main sequence or red giant branch. It is shown that BSEC technique can discard some false negatives of previous works, which takes about three percentage of known clusters. It shows that as an EC, the color excess (or two-color) constraint is useful for removing fake cluster member stars from the clusters that are identified from the positions and proper motions of stars, and getting more precise CMDs, when differential reddening of member stars of a cluster is not large (e.g., ΔE(G BP − G RP) < 0.5 mag). It makes the CMDs of 15% clusters clearer (in particular for the region near turnoff) and therefore is helpful for CMD and stellar population studies. Our result suggests that the color excess constraint is more appropriate for clusters with small differential reddening, such as globular clusters or older OCs, and clusters that the distances of member stars cannot be determined accurately.

Optical Photometric Indicators of Galaxy Cluster Relaxation

The most dynamically relaxed clusters of galaxies play a special role in cosmological studies as well as astrophysical studies of the intracluster medium (ICM) and active galactic nucleus feedback. While high-spatial-resolution imaging of the morphology of the ICM has long been the gold standard for establishing a cluster’s dynamical state, such data are not available from current or planned surveys, and thus require separate, pointed follow-up observations. With optical and/or near-IR photometric imaging, and red-sequence cluster finding results from those data, expected to be ubiquitously available for clusters discovered in upcoming optical and millimeter-wavelength surveys, it is worth asking how effectively photometric data alone can identify relaxed cluster candidates, before investing in, e.g., high-resolution X-ray observations. Here we assess the ability of several simple photometric measurements, based on the redMaPPer cluster finder run on Sloan Digital Sky Survey data, to reproduce X-ray classifications of dynamical state for an X-ray selected sample of massive clusters. We find that two simple metrics contrasting the bright central galaxy (BCG) to other cluster members can identify a complete sample of relaxed clusters with a purity of ∼40% in our data set. Including minimal ICM information in the form of a center position increases the purity to ∼60%. However, all three metrics depend critically on correctly identifying the BCG, which is presently a challenge for optical red-sequence cluster finders.