Abstract:We report 1,656 new star clusters found in the Galactic disk (|b|<20 degrees) beyond 1.2 kpc, using Gaia EDR3 data. Based on an unsupervised machine learning algorithm, DBSCAN, and followed our previous studies, we utilized a unique method to do the data preparation and obtained the clustering coefficients, which proved to be an effective way to search blindly for star clusters. We tabulated the physical parameters and member stars of the new clusters, and presented some interesting examples, including a globu… Show more
“…An even higher number have recently been discovered in EDR3 data (Castro-Ginard et al 2022), while other authors have reported similar numbers of new discoveries (e.g. Hao et al 2022;He et al 2022). These new cluster candidates discovered in Gaia data now rival in number the clusters known before its launch.…”
Context. Automated analysis of Gaia astrometric data has led to the discovery of many new high-quality open cluster candidates. With a good determination of their parameters, these objects become excellent tools to investigate the properties of our Galaxy. Aims. We explore whether young open clusters can be readily identified from Gaia data alone by studying the properties of their Gaia colour-magnitude diagrams. We also want to compare the results of a traditional cluster analysis with those of automated methods. Methods. We selected three young open cluster candidates from the UBC catalogue, ranging from a well-populated object with a well-defined sequence to a poorly-populated, poorly-defined candidate. We obtained classification spectra for the brightest stars in each. We redetermined members based on EDR3 data and fitted isochrones to derive age, distance and reddening. Results. All three candidates are real clusters with age below 100 Ma. UBC 103 is a moderately populous cluster, with an age around 70 Ma. At a distance of ∼ 3 kpc, it forms a binary cluster with the nearby NGC 6683. UBC 114 is a relatively nearby (∼ 1.5 kpc) poorly-populated cluster containing two early-B stars. UBC 587 is a dispersed, very young (≤ 10 Ma) cluster located at ∼ 3 kpc, behind the Cygnus X region, and may be a valuable tracer of the Orion arm. Conclusions. The OCfinder methodology for the identification of new open clusters is extremely successful, with even poor candidates resulting in interesting detections. The presence of an almost vertical photometric sequence in the Gaia colour-magnitude diagram is a safe way to identify young open clusters. Automated methods for the determination of cluster properties give approximate solutions, but are still subject to some difficulties. There is some evidence suggesting that artificial intelligence systems may systematically underestimate extinction, which may impact in the age determination.
“…An even higher number have recently been discovered in EDR3 data (Castro-Ginard et al 2022), while other authors have reported similar numbers of new discoveries (e.g. Hao et al 2022;He et al 2022). These new cluster candidates discovered in Gaia data now rival in number the clusters known before its launch.…”
Context. Automated analysis of Gaia astrometric data has led to the discovery of many new high-quality open cluster candidates. With a good determination of their parameters, these objects become excellent tools to investigate the properties of our Galaxy. Aims. We explore whether young open clusters can be readily identified from Gaia data alone by studying the properties of their Gaia colour-magnitude diagrams. We also want to compare the results of a traditional cluster analysis with those of automated methods. Methods. We selected three young open cluster candidates from the UBC catalogue, ranging from a well-populated object with a well-defined sequence to a poorly-populated, poorly-defined candidate. We obtained classification spectra for the brightest stars in each. We redetermined members based on EDR3 data and fitted isochrones to derive age, distance and reddening. Results. All three candidates are real clusters with age below 100 Ma. UBC 103 is a moderately populous cluster, with an age around 70 Ma. At a distance of ∼ 3 kpc, it forms a binary cluster with the nearby NGC 6683. UBC 114 is a relatively nearby (∼ 1.5 kpc) poorly-populated cluster containing two early-B stars. UBC 587 is a dispersed, very young (≤ 10 Ma) cluster located at ∼ 3 kpc, behind the Cygnus X region, and may be a valuable tracer of the Orion arm. Conclusions. The OCfinder methodology for the identification of new open clusters is extremely successful, with even poor candidates resulting in interesting detections. The presence of an almost vertical photometric sequence in the Gaia colour-magnitude diagram is a safe way to identify young open clusters. Automated methods for the determination of cluster properties give approximate solutions, but are still subject to some difficulties. There is some evidence suggesting that artificial intelligence systems may systematically underestimate extinction, which may impact in the age determination.
“…Since there is no relevant proper motion parameter in the data, we have to only compare the mean parameters within 5σ (whereσ is the uncertainty listed in both catalogs for each quantity) using sky coordinates. To eliminate as many OCs as possible that have already been found and obtain OC candidates that have not been unnoticed before, we consider an OC to be positionally matched to a cataloged one if their astrometric mean parameters (l, b, , µ α , µ δ ) are compatible within 5 σ (where σ is the uncertainty quoted in both catalogs for each quantity) which is consistent with He et al (2022a), He et al (2022c) and Hao et al (2022a). The list of previously published sources including LP, Ferreira Series, CWNU, Hao Series, UBC, and so on is presented in Table 1.…”
Section: Cross-matchmentioning
confidence: 99%
“…Since a real OC should have clear main sequence features on the CMDs, reference Cantat-Gaudin et al ( 2020) and He et al (2022a), to screen out the most reliable candidates, we performed manual visual inspections on spatial distributions (SDs), proper motion distributions (PMDs), parallax distributions (PDs) and vs µ α , and their isochrone fits results to further check the quality of candidate clusters.…”
Section: Comprehensive Analysis Based On Visual Insectionmentioning
confidence: 99%
“…A series of studies have searched for OCs using the GAIA 1 and subsequent catalogs. More than 6,000 Galactic star clusters (SCs) have been detected in published Gaia data catalogs (He et al 2022a). About 1,200 pre-Gaia open clusters (OCs) have been reidentified (Cantat-Gaudin et al 2018) based on Gaia Data Release 2 (Gaia Collaboration et al 2018).…”
Section: Introductionmentioning
confidence: 99%
“…RVs are useful to assess the reliability of the classification of the OC candidate (Castro-Ginard et al 2022a). More abundant stellar radial velocity and physical information provide an opportunity to study cluster membership and kinematics (He et al 2022a).…”
Studying open clusters (OCs) is essential for a comprehensive understanding of the structure and evolution of the Milky Way. Many previous studies have systematically searched for OCs near the solar system within 1.2 kpc or 20 degrees of galactic latitude. However, few studies searched for OCs at higher galactic latitudes and deeper distances. In this study, based on a hybrid unsupervised clustering algorithm (Friends-of-Friends and pyUPMASK) and a binary classification algorithm (Random Forest), we extended the search region (i.e., galactic latitude |b| ≥ 20 • ) and performed a fine-grained blind search of Galactic clusters in Gaia DR3. After cross-matching, the newly discovered cluster candidates are fitted using isochrone fitting to estimate the main physical parameters (age and metallicity) of these clusters. These cluster candidates were then checked using manual visual inspection. Their statistical properties were compared with previously exposed cluster catalogs as well. In the end, we found 1,179 new clusters with considerable confidence within 5kpc.
It remains unclear how galactic environment affects star formation and stellar cluster properties. This is difficult to address in Milky Way-mass galaxy simulations because of limited resolution and less accurate feedback compared to cloud-scale models. We carry out zoom-in simulations to re-simulate 100–300pc regions of a Milky Way-like galaxy using smoothed particle hydrodynamics, including finer resolution (0.4M⊙ per particle), cluster-sink particles, ray-traced photoionization from O stars, H2/CO chemistry, and ISM heating/cooling. We select ∼106M⊙ cloud complexes from a galactic bar, inner spiral arm, outer arm, and inter-arm region (in order of galactocentric radius), retaining the original galactic potentials. The surface densities of star formation rate and neutral gas follow $\Sigma _\mathrm{SFR}\propto \Sigma _\mathrm{gas}^{1.3}$, with the bar lying higher up the relation than the other regions. However, the inter-arm region forms stars 2–3x less efficiently than the arm models at the same Σgas. The bar produces the most massive cluster, the inner arm the second, and the inter-arm the third. Almost all clusters in the bar and inner arm are small (radii <5pc), while 30-50 per cent of clusters in the outer arm and inter-arm have larger radii more like associations. Bar and inner arm clusters rotate at least twice as fast, on average, than clusters in the outer arm and inter-arm regions. The degree of spatial clustering also decreases from bar to inter-arm. Our results indicate that young massive clusters, potentially progenitors of globular clusters, may preferentially form near the bar/inner arm compared to outer arm/inter-arm regions.
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