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REVIEW 5 major objections 4 minor 71 references

A study of the star clusters' population in the giant molecular cloud G174+2.5

T0 review · 5 major / 4 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read The fate of four young star clusters in G174+2.5 hinges on whether the whole parent cloud counts as part of the system: it is, and all four are bound.

desk verdict Solid region-specific cluster census with new UKIDSS/Gaia results, but the all-cloud boundness claim is dominated by gas self-gravity, not cluster properties. read the letter →

arxiv 2411.14235 v1 pith:6EQ2VUL2 submitted 2024-11-21 astro-ph.GA

T.A. Permyakova (UrFU) , G. Carraro (UniPD) , A.F. Seleznev (UrFU) , A.M. Sobolev (UrFU) , D.A. Ladeyschikov (UrFU) , M.S. Kirsanova (Inasan) This is my paper · ORCID
classification astro-ph.GA
keywords embeddedstarclustersgiantmolecularcloudG174+2.5formationefficiencyGaiaDR3UKIDSSinterstellarreddeningclusterdynamicsgasmass
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper maps the stellar population of the giant molecular cloud G174+2.5 and asks whether its embedded star clusters will stay together. The central finding is that the answer depends on how much gas is counted: using only gas inside each cluster region, two of the four clusters are bound, while adding the mass of the whole cloud makes all four bound. The paper also finds 14 clusters or candidates, six of them previously unknown, and shows that reddening corrections from individual stellar colors give much cleaner color-magnitude diagrams than the NICEST extinction map. If the gas-mass estimates hold, the clusters' survival is controlled by the surrounding cloud reservoir rather than by the stars alone.

What carries the argument

The load-bearing mechanism is a two-component total-energy calculation: each cluster and its gas are treated as homogeneous gravitating spheres with coincident centers, and the total energy is $E = T_1 + \Omega_1 + T_2 + \Omega_2 - \Omega_{12}$, with the interaction potential $\Omega_{12}$. The gas masses entering this equation come from $^{12}$CO and $^{13}$CO maps converted to column density through LTE, using an isotopic ratio $R = 80$ and a fixed $[\mathrm{CO}]/[\mathrm{H}_2]$ abundance of $8 \cdot 10^{-5}$. Supporting machinery includes KDE surface-density maps to find clusters, UPMASK for membership probabilities, the Q-method for individual reddening, and Kroupa IMF extrapolation for cluster masses.

What would settle it

Recompute the gas mass in the same 18-arcmin region using dust continuum emission or another CO-independent tracer; if it comes out substantially below 21,560 solar masses, the negative total energies for clusters 10 and 11 would flip positive, and the paper's 'all bound' claim would fail.

Watch

Extended reading notes

Core claim

The paper's central claim is that the four studied clusters in G174+2.5 — S235 North-West, S235 A-B-C, S235 Central, and S235 East1+East2 — should be viewed as 'stars + gas' systems. The total energy of each system is negative when the whole 18-arcmin cloud, about 21,560 solar masses of molecular gas, is included, meaning all four are gravitationally bound; with only local gas, the energies of S235 North-West and S235 A-B-C become positive, meaning they would not be bound. The cluster star subsystems alone have positive total energies in every case. The paper interprets this as the gas providing the gravitational glue that currently holds the proto-clusters together.

Load-bearing premise

The binding conclusion rests on assuming that CO emission, a fixed CO-to-H2 ratio, and an 18-arcmin hand-selected region give the true gas mass gravitationally attached to the clusters.

Editorial extensions

If this is right

  • If the whole-cloud gas mass is real, the four clusters are currently gravitationally bound and may retain more stars than the local-gas estimate would predict when the gas is removed.
  • The star formation efficiencies of 0.04–0.17 fall inside the Milky Way range, with the lowest values in the two clusters likely formed by the expanding HII region.
  • Previous identifications from 2MASS change with deeper UKIDSS data: S235 East1 and East2 appear as one object, and BDSB 71–73 are sub-clusters of S235 A-B-C that may later merge.
  • The positive energies of the stellar subsystems alone imply that once the gas disperses, the clusters will lose a significant number of stars or dissolve entirely.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Editorial inference: the same two-region test could be applied to other embedded clusters, since the 'bound versus unbound' answer in the literature may depend on the arbitrary choice of gas aperture.
  • Editorial inference: a dust-based gas mass over the same area would test the fixed CO-to-H2 and isotope-ratio assumptions, because those scalings dominate the derived gas mass.
  • Editorial inference: because the Gaia proper-motion dispersions are much larger than the gas dispersions, the clusters may be out of virial equilibrium; radial-velocity measurements would show whether the stars are actually expanding or falling.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

5 major / 4 minor

Summary. The paper presents a census of star clusters and cluster candidates in the giant molecular cloud G174+2.5 using UKIDSS Galactic Plane Survey photometry and Gaia DR3 astrometry. It identifies 14 stellar overdensities, six of which are proposed as previously unknown embedded cluster candidates, and carries out a detailed analysis of four clusters (S235 North-West, S235 A-B-C, S235 Central, S235 East1+East2). For these four clusters the authors derive reddening maps, membership probabilities with UPMASK, distances from isochrone fitting and Gaia parallaxes, proper motions, photometric and dynamical masses, gas masses from CO observations, star formation efficiencies, and estimates of the total energy of the stellar-plus-gas system. The central dynamical conclusion is that the clusters are gravitationally bound when the mass of the entire molecular cloud is included, while only two of them appear bound when only local gas is considered.

Significance. If the results hold, the paper provides a useful, deeper UKIDSS-based census of a relatively nearby star-forming complex and adds six new cluster candidates. The combination of extinction-corrected density maps, membership probabilities, Gaia proper motions, and externally anchored distance checks (Pleiades/Praesepe for the Q-method, Gaia parallaxes, and the maser parallax) is a methodological strength, and the authors are unusually transparent about several limitations. However, the headline boundness claim is not established on the evidence presented: the all-cloud total energies are dominated by the adopted gas sphere's self-gravity rather than by the interaction between the clusters and the gas. The dynamic mass estimates are also overestimated by orders of magnitude and are used in the energy budget, so the quantitative energy values in Table 5 must be treated with caution.

major comments (5)
  1. [Section 8, Eq. (17), Table 5] The abstract's claim that all four clusters are bound when the entire cloud is considered is not supported as a statement about the stellar clusters, because the negative E_allcloud values are dominated by the gas self-energy term -3GM2^2/(5R2) in Omega2. With M2 = 21560 M_sun and R2 = 9.7 pc (18 arcmin at 1.86 kpc), this term is approximately -1.2e5 in the units of Table 5, comparable to every E_allcloud entry (-5.5e4 to -1.07e5); if the cluster membership radius is used instead of 18 arcmin, the term is even more negative. Clusters 10 and 11 have positive E with local gas (+2.1e4 and +4.7e4) and become negative only after this same self-gravitating gas sphere is added to each system, so the sign change is nearly automatic for any object embedded in the adopted cloud model and does not measure the cluster's own binding.
  2. [Section 8, final paragraph] The paper acknowledges the spherical-symmetry and center-coincidence approximations but does not identify that the gas self-energy term in Eq. (17) dominates the computed total energy and makes the sign of E_allcloud largely independent of the cluster's own mass, radius, and kinematics. The authors should report the gas self-energy and the interaction term Omega12 separately, and should rephrase the conclusion to say that the stars-plus-gas system is bound under the adopted cloud model, not that the stellar clusters are bound.
  3. [Section 6.2, Eq. (3), Table 4] The dynamical masses are overestimated by factors of roughly one to three orders of magnitude relative to the photometric masses (e.g., 186000 M_sun versus 209 M_sun for cluster 10), and the authors note this in the text. Since the same velocity dispersions are then used in Eq. (14) for the kinetic energy T1 in Section 8, the quantitative total energies in Table 5 are systematically uncertain even though an overestimated T1 is conservative for the boundness sign; the paper should propagate this systematic uncertainty into the energy values or use an explicitly labeled upper limit.
  4. [Section 7, Eq. (12), Table 5] The gas masses, including the all-cloud mass of 21560 M_sun, are derived with a fixed [CO]/[H2] abundance ratio of 8e-5, a fixed isotope ratio R = 80, and a hand-selected 18-arcmin integration radius; this radius defines what the paper calls the 'entire cloud' and is load-bearing for E_allcloud. The authors should test the sensitivity of the boundness conclusion to the integration radius and to the conversion factors, and should show how E_allcloud changes if the gas mass is integrated over, say, twice or half the adopted radius.
  5. [Section 4.2, Table 2] The photometric distances are obtained by fitting isochrones to broad pre-main-sequence sequences by eye, and the quoted uncertainties are derived by shifting the sequences by color-index errors; this gives an incomplete description of the fitting uncertainty. Because the gas mass in Eq. (12) scales as the square of the adopted distance, the systematic distance error propagates directly into the gas mass and the total energy, and it should be quantified alongside the statistical errors.
minor comments (4)
  1. [Throughout] There are several typographical issues, such as 'North-W est' in Section 3 and 'T able' in the table captions; a careful proofreading pass is needed.
  2. [Section 6.2, Eq. (4)] The assumption that the radial-velocity dispersion equals the dispersion in one tangential direction, multiplied by 1.5, should be justified or relaxed, since it directly affects the dynamical masses and the kinetic energy term.
  3. [Section 7, SFE discussion] The star formation efficiencies quoted in Table 5 include only statistical errors; the systematic uncertainty from ionized gas not traced by CO and from the CO conversion factor is likely larger than the statistical errors and should be reflected in the reported SFE values.
  4. [Section 8] The word 'boundness' should be replaced with 'binding' or 'bound state' in several places, including the abstract and conclusions.

Circularity Check

1 steps flagged · score 2.0 of 10

Minor definitional dependency in all-cloud boundness; otherwise self-contained and externally anchored.

  1. self definitional [Abstract; Section 8, Eqs. 15-17 and Table 5]
    "The gravitational bound strongly depends on the region for which we estimate the gas mass. If we consider the mass of the entire cloud, all these four clusters turn out to be bound. ... (here we consider a `cluster' as the system `stars + gas'). ... Ω2 = −3GM2^2/(5R2) − 3GM1M2/(2R2)(1 − R1^2/(5R2^2))."

    The headline all-cloud boundness follows by construction from the adopted definition 'cluster = stars + gas', not from cluster properties. For M2=21560 Msun and R2≈9.7 pc, the gas self-gravity term −3GM2^2/(5R2) in Eq. 16 contributes about −1.2e5 in Table 5 units, comparable to or more negative than every E_allcloud value (−5.5e4 to −1.07e5). Clusters 10 and 11 are unbound with local gas only (+21100, +47300) and become bound solely after adding the same self-gravitating cloud mass to each system, making E<0 nearly automatic for any embedded object. The paper discloses this: it states the stars+gas definition, reports the local-gas alternative, and flags the spherical/coincident-center approximations.

full rationale

No significant circular derivation was found in the cluster parameters, distances, masses, kinematics, or SFE. Distances are anchored by Gaia DR3 parallaxes and agree with the Burns et al. (2015) maser parallax. The Q-method reddening sequence is built from Pleiades/Praesepe photometry with an external extinction law; its smaller CMD scatter is partly a self-consistency effect of dereddening onto the fitted sequence, but it is not a target prediction and the distances are independently checked. Gas masses come from LTE CO analysis with fixed abundance and isotope ratios and external references, not fitted to the boundness conclusion. The velocity-dispersion correction follows Kulesh et al. (2024), a co-authored self-citation, but the equations are reproduced in the text and the corrected dispersions enter only the small kinetic terms; the all-cloud energy is dominated by the gas self-energy. The paper explicitly acknowledges the spherical-symmetry and center-coincidence limitations and the dependence of the boundness result on the chosen gas region. The only noteworthy issue is the definitional character of the entire-cloud boundness claim described in the step above; because it is transparent and accompanied by the local-gas case, it warrants a low score rather than a charge of forced circularity.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

The analysis is built on several fitted calibration parameters (Q-method sequence, IMF normalization, KDE widths) and domain assumptions (spherical symmetry, Gaussianity, CO conversion) that are standard but not independently verified here. The hand-set gas integration radius is the most consequential choice, since it directly controls the headline boundness result.

free parameters (4)
  • Q-method zero-reddening sequence coefficients = A2: 0.1573, 0.2338, 0.0157; A3: 0.0337, -0.4941, 0.3561
    Fitted by least squares to Pleiades and Praesepe colors; these coefficients define intrinsic colors used to deredden all target stars, affecting distances and masses.
  • Kroupa IMF normalization per cluster = not quoted, per cluster in Section 6.1
    Normalized to the observed number of stars with M > 0.6 Msun; used to extrapolate the unseen low-mass population, doubling to tripling cluster masses and feeding SFE and energy estimates.
  • KDE kernel half-widths for velocity distributions = manual, varied by coordinate
    Chosen by eye so the peak of the distribution is clear (Section 6.2); the true velocity dispersion after deconvolution depends on these widths.
  • Gas integration radius for whole cloud = 18 arcmin
    Hand-selected region centered at RA 85.255, Dec 35.76; using this radius for gas mass makes all four systems bound, while smaller radii leave two unbound.
assumptions (5)
  • domain assumption The cluster and gas components can be treated as homogeneous, spherically symmetric spheres with coincident centers for energy calculations.
    Section 8 states that the real clusters are elongated or hierarchical, so the energy equations from Danilov (2024) are only approximate.
  • domain assumption The radial velocity distribution equals the distribution in one tangential direction, allowing 3D dispersion from proper motions via Eq. 4.
    Section 6.2 uses this to convert observed proper-motion dispersions to a 3D velocity dispersion.
  • domain assumption Observed and error distributions are Gaussian, so the true dispersion is the quadrature difference of observed and error dispersions.
    The Kulesh et al. (2024) method, described in Section 6.2, assumes Gaussianity and uses a KDE with manually chosen widths.
  • domain assumption The CO-to-H2 abundance ratio is 8e-5 and the 12C/13C isotope ratio is R=80.
    Section 7 uses these to convert CO line intensities into gas mass; a different ratio changes gas masses and the energy balance.
  • domain assumption The Pleiades and Praesepe zero-reddening sequence in the Q-method is representative of the intrinsic colors of the young cluster stars in G174+2.5, including pre-main-sequence stars and YSOs.
    Appendix A derives dereddened colors using this sequence; YSOs with infrared excess may deviate from it, biasing extinctions and distances.

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Pith. "Pith review of A study of the star clusters' population in the giant molecular cloud G174+2.5." pith.science (2026). https://pith.science/paper/6EQ2VUL2

@misc{pith2026241114235,
  author       = {Pith},
  title        = {Pith review of: A study of the star clusters' population in the giant molecular cloud G174+2.5},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/6EQ2VUL2}},
  note         = {Machine review of arXiv:2411.14235}
}
read the original abstract

We study the structure, interstellar absorption, color-magnitude diagrams, kinematics, and dynamical state of embedded star clusters in the star-forming region associated with the giant molecular cloud G174+2.5. Our investigation is based on photometric data from the UKIDSS Galactic Plane Survey catalog and astrometric data from the Gaia DR3 catalogs. First, we recover all the known embedded clusters and candidate clusters in the region using surface density maps. Then, for the detected clusters, we determine their general parameters: the center positions, radii, number of stars, and reddening. To evaluate the reddening, we use both the NICEST algorithm and the Q-method. Both methods produce consistent extinction maps in the regions of the four studied clusters. However, the Q-method yields a much smaller color scatter in the CMD. For four clusters in particular (S235~North-West, S235~A-B-C, S235~Central, and S235~East1+East2), we were able to compute individual membership probabilities, the cluster distances, the cluster masses, and their average proper motions. By building on these results, we have studied the clusters' kinematics and dynamics. Moreover, we estimate the mass of the gas component and the star formation efficiency (SFE) in the regions of these four clusters. Finally, we provide an estimate of the total energy of the stellar and gas components in the area of these four clusters to determine whether the clusters are bound (here we consider a `cluster' as the system `stars + gas'). The gravitational bound strongly depends on the region for which we estimate the gas mass. If we consider the mass of the entire cloud, all these four clusters turn out to be bound.

Figures

Figures reproduced from arXiv: 2411.14235 by the authors.

Figure 1
Figure 1. Histogram of the stellar magnitudes in the J, H, and K bands for a sample from the UKIDSS catalog in the G174+2.5 region. clouds (Schisano et al. 2014; K¨onyves et al. 2015) has a multi-scale, fractal structure. At close distances, we can clearly distinguish the fine structure of clouds – thin filaments with stars forming in them. For more distant regions, on the contrary, small structures are not resolved well duri… view at source ↗
Figure 2
Figure 2. Star distribution maps for the UKIDSS sample of the G174+2.5 region; stars without magnitude data in the J (a) and H (b) bands. Burns et al. (2019) marked that star clusters in the G174+2.5 complex are connected with the filaments twisted around Sh2-235 HII region. They proposed that clusters S235 East 1, S235 East 2, S235 Central, and S235 A-B-C could belong to the filament directed approximately along the line-of-… view at source ↗
Figure 3
Figure 3. The left panel shows the absorption distribution in the star forming region G174+2.5 obtained by the NICEST method. The yellow circles show the areas occupied by clusters, the numbers are the cluster IDs in this work. The right panel shows a map of the filaments identified in the star forming region G174+2.5 using the GetFilaments algorithm (Men’shchikov 2013). Filaments of different scales are shown in different co… view at source ↗
Figures from the paper (13 more)
Figure 4
Figure 4. Figure 4: Stellar density maps of the G174+2.5 region based on UKIDSS data. Red numbers indicate areas of increased stellar density considered in the work. Shades of gray indicate the levels of surface density of stars (see the scales corresponding to the pictures). In [PITH_FU…
Figure 5
Figure 5. Figure 5: Radial density profiles of the clusters. The profile is shown by thick black line, the confidence interval is shown by thin gray lines, the cluster radius position is marked by red, and the background level is plotted by blue. The number of cluster is shown at the top …
Figure 6
Figure 6. Figure 6: Color - magnitude diagrams of clusters 10 (S235 North-West), 11 (S235 A-B-C), 12 (S235 Central) and 14 (S235 East1+East2), combined with isochrones (Bressan et al. 2012). The color excesses and absorption in the K band were obtained by the Q-method (see description in …
Figure 7
Figure 7. Figure 7: Color - magnitude diagrams of clusters 10 (S235 North-West), 11 (S235 A-B-C), 12 (S235 Central) and 14 (S235 East1+East2), combined with isochrones (Bressan et al. 2012). The color excesses and absorption in the K band were obtained by the NICEST method (see Section 3)…
Figure 8
Figure 8. Figure 8: The left figure shows a map of residual velocities of YSO. Class I YSOs are shown in red, class II YSOs in blue. Filled markers are YSO of the clusters, unfilled markers are YSO of the field. The right figure shows a map of the residual velocities of clusters (red) and…
Figure 9
Figure 9. Figure 9: Plots ‘tangential component – positional angle’, ‘radial component – positional angle’, ‘tangential component – distance’ and ‘radial component – distance’ for cluster 10 (S235 North-West). Class I YSOs are shown in red, class II YSOs in blue, other stars in black. • T…
Figure 10
Figure 10. Figure 10: The same as Fig.9 for cluster 11 (S235 A-B-C). Since we know the probabilities of membership of stars in clusters 10 (S235 North-West), 11 (S235 A-B-C), 12 (S235 Central), and 14 (S235 East1+East2), we can attempt to estimate their masses. In order to achieve this, we…
Figure 11
Figure 11. Figure 11: The same as Fig.9 for cluster 14 (S235 East1+East2). • We may erroneously consider a massive star to be low-mass one due to an underestimation of the absorption value. The outcome of the computation of the photometric mass Mph is summarized in [PITH_FULL_IMAGE:figure…
Figure 12
Figure 12. Figure 12: Map of the positions of stars in clusters 10 (S235 North-West), 11 (S235 A-B-C), 12 (S235 Central) and 14 (S235 East1+East2). The color indicates the mass obtained by comparing the positions of stars on CMD with evolutionary tracks. IMF, we can calculate the number of…
Figure 13
Figure 13. Figure 13: Mass functions of clusters 10 (S235 North-West), 11 (S235 A-B-C), 12 (S235 Central) and 14 (S235 East1+East2) (in black). The Kroupa initial mass function is shown in green. mass interval and the average mass of the interval. To estimate the total mass of the cluster,…
Figure 14
Figure 14. Figure 14: Distribution of proper motions of stars and their errors in cluster 14 (S235 East1+East2) (black). Functions that approximate distributions are shown in red. Eq. 7 and 4. To find the dynamic masses of clusters, we substitute the resulting dispersions and radii of the …
Figure 15
Figure 15. Figure 15: The zero-reddening sequence. The Pleiades and Praesepe stars are shown by the gray dots, the non-reddened sequence described by the Eq.(A2) and Eq.(A3) is shown by solid black lines. Blue lines are the boundaries of the non-reddened sequence. The red dotted lines show…
Figure 16
Figure 16. Figure 16: Combined luminosity functions of cluster 11 (S235 A-B-C) and the Pleiades. The luminosity function of the Pleiades stars belonging to the left segment is shown in orange, and the luminosity function of the right segment is shown in blue. The luminosity function of clu…

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Works this paper leans on

71 extracted references · 30 canonical work pages

  1. [1]

    J., & Hills, J

    Aarseth, S. J., & Hills, J. G. 1972, A&A, 21, 255

    work page 1972

  2. [2]

    E., Hora, J

    Allen, L. E., Hora, J. L., Megeath, S. T., et al. 2005, in Massive Star Birth: A Crossroads of Astrophysics, ed. R. Cesaroni, M. Felli, E. Churchwell, & M. Walmsley, Vol. 227, 352–357, doi: 10.1017/S1743921305004734 Andr´ e, P., Di Francesco, J., Ward-Thompson, D., et al. 2014, in Protostars and Planets VI, ed. H. Beuther, R. S

    work page doi:10.1017/s1743921305004734 2005

  3. [3]

    Klessen, C. P. Dullemond, & T. Henning, 27, doi: 10.2458/azu uapress 9780816531240-ch002

    doi:10.2458/azu

  4. [4]

    2011, A&A, 529, L6, doi: 10.1051/0004-6361/201116596 29

    Arzoumanian, D., Andr´ e, P., Didelon, P., et al. 2011, A&A, 529, L6, doi: 10.1051/0004-6361/201116596 29

    doi:10.1051/0004-6361/201116596 2011

  5. [5]

    2002, A&A, 387, 931, doi: 10.1051/0004-6361:20020319

    Beuther, H., Schilke, P., Gueth, F., et al. 2002, A&A, 387, 931, doi: 10.1051/0004-6361:20020319

    work page doi:10.1051/0004-6361:20020319 2002

  6. [6]

    M., & Barbuy, B

    Bica, E., Dutra, C. M., & Barbuy, B. 2003a, A&A, 397, 177, doi: 10.1051/0004-6361:20021479

    doi:10.1051/0004-6361:20021479

  7. [7]

    M., Soares, J., & Barbuy, B

    Bica, E., Dutra, C. M., Soares, J., & Barbuy, B. 2003b, A&A, 404, 223, doi: 10.1051/0004-6361:20030486

    doi:10.1051/0004-6361:20030486

  8. [8]

    H., Patel, S., Peters, W

    Bieging, J. H., Patel, S., Peters, W. L., et al. 2016, ApJS, 226, 13, doi: 10.3847/0067-0049/226/1/13

    work page doi:10.3847/0067-0049/226/1/13 2016

Show all 71 references
  1. [9]

    A., Sobolev, A

    Boley, P. A., Sobolev, A. M., Krushinsky, V. V., et al. 2009, MNRAS, 399, 778, doi: 10.1111/j.1365-2966.2009.15308.x

    2009

  2. [10]

    2012, MNRAS, 427, 127, doi: 10.1111/j.1365-2966.2012.21948.x

    Bressan, A., Marigo, P., Girardi, L., et al. 2012, MNRAS, 427, 127, doi: 10.1111/j.1365-2966.2012.21948.x

    2012

  3. [11]

    2004, in Astronomical Society of the Pacific Conference Series, Vol

    Brunt, C. 2004, in Astronomical Society of the Pacific Conference Series, Vol. 317, Milky Way Surveys: The Structure and Evolution of our Galaxy, ed. D. Clemens, R. Shah, & T. Brainerd, 79

    2004

  4. [12]

    A., Imai, H., Handa, T., et al

    Burns, R. A., Imai, H., Handa, T., et al. 2015, MNRAS, 453, 3163, doi: 10.1093/mnras/stv1836

    2015 doi

  5. [13]

    A., Handa, T., Omodaka, T., et al

    Burns, R. A., Handa, T., Omodaka, T., et al. 2019, PASJ, 71, 91, doi: 10.1093/pasj/psz074

    2019 doi

  6. [14]

    2016, MNRAS, 455, 3126, doi: 10.1093/mnras/stv2517

    Camargo, D., Bica, E., & Bonatto, C. 2016, MNRAS, 455, 3126, doi: 10.1093/mnras/stv2517

    2016 doi

  7. [16]

    Campello, R. J. G. B., Moulavi, D., & Sander, J. 2013, in Advances in Knowledge Discovery and Data Mining, ed. J. Pei, V. S. Tseng, L. Cao, H. Motoda, & G. Xu (Berlin, Heidelberg: Springer Berlin Heidelberg), 160–172

    2013

  8. [17]

    A., Clayton, G

    Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245, doi: 10.1086/167900

    1989 doi

  9. [18]

    A., Mathis, J

    Cardelli, J. A., Mathis, J. S., Ebbets, D. C., & Savage, B. D. 1993, ApJL, 402, L17, doi: 10.1086/186689

    1993 doi

  10. [19]

    2020, Boletin de la Asociacion Argentina de Astronomia La Plata Argentina, 61C, 11

    Carraro, G. 2020, Boletin de la Asociacion Argentina de Astronomia La Plata Argentina, 61C, 11

    2020

  11. [20]

    2007, A&A, 467, 777, doi: 10.1051/0004-6361:20066514 Chavarr ´ ıa, L., Allen, L., Brunt, C., et al

    Casali, M., Adamson, A., Alves de Oliveira, C., et al. 2007, A&A, 467, 777, doi: 10.1051/0004-6361:20066514 Chavarr ´ ıa, L., Allen, L., Brunt, C., et al. 2014, MNRAS, 439, 3719, doi: 10.1093/mnras/stu224

    2007 doi

  12. [21]

    2024, MNRAS, 527, 4297, doi: 10.1093/mnras/stad3459

    Chen, E., Gao, Y., Zhang, S., et al. 2024, MNRAS, 527, 4297, doi: 10.1093/mnras/stad3459

    2024 doi

  13. [22]

    Danilov, V. M. 1984, in Metody Astron.-Geod. Issled. (Sverdlovsk: UrSU), 94–117

    1984

  14. [23]

    Danilov, V. M. 2024, Astrophysical Bulletin, 79, 71, doi: 10.1134/S1990341323600321

    2024 doi

  15. [24]

    M., & Seleznev, A

    Danilov, V. M., & Seleznev, A. F. 2020, Astrophysical Bulletin, 75, 407, doi: 10.1134/S1990341320040045

    2020 doi

  16. [25]

    K., & Anandarao, B

    Dewangan, L. K., & Anandarao, B. G. 2011, MNRAS, 414, 1526, doi: 10.1111/j.1365-2966.2011.18487.x

    2011

  17. [26]

    K., Ojha, D

    Dewangan, L. K., Ojha, D. K., Luna, A., et al. 2016, ApJ, 819, 66, doi: 10.3847/0004-637X/819/1/66

    2016 doi

  18. [27]

    J., I., & Blair, G

    Evans, N. J., I., & Blair, G. N. 1981, ApJ, 246, 394, doi: 10.1086/158937

    1981 doi

  19. [28]

    Foster, T., & Brunt, C. M. 2015, AJ, 150, 147, doi: 10.1088/0004-6256/150/5/147

    2015 doi

  20. [29]

    Froebrich, D., Scholz, A., & Raftery, C. L. 2007, MNRAS, 374, 399, doi: 10.1111/j.1365-2966.2006.11148.x Gaia Collaboration, Prusti, T., de Bruijne, J. H. J., et al. 2016, A&A, 595, A1, doi: 10.1051/0004-6361/201629272 Gaia Collaboration, Vallenari, A., Brown, A. G. A., et al....

    2007

  21. [30]

    M., Georgelin, Y

    Georgelin, Y. M., Georgelin, Y. P., & Roux, S. 1973, A&A, 25, 337

    1973

  22. [31]

    G., Bally, J., Yan, C.-H., & Williams, J

    Ginsburg, A. G., Bally, J., Yan, C.-H., & Williams, J. P. 2009, ApJ, 707, 310, doi: 10.1088/0004-637X/707/1/310

    2009 doi

  23. [33]

    C., Warren, S

    Hewett, P. C., Warren, S. J., Leggett, S. K., & Hodgkin, S. T. 2006, MNRAS, 367, 454, doi: 10.1111/j.1365-2966.2005.09969.x

    2006

  24. [35]

    P., & Felli, M

    Israel, F. P., & Felli, M. 1978, A&A, 63, 325

    1978

  25. [36]

    L., & Morgan, W

    Johnson, H. L., & Morgan, W. W. 1953, ApJ, 117, 313, doi: 10.1086/145697

    1953 doi

  26. [37]

    2012, AJ, 143, 75, doi: 10.1088/0004-6256/143/3/75

    Kang, J.-h., Koo, B.-C., & Salter, C. 2012, AJ, 143, 75, doi: 10.1088/0004-6256/143/3/75

    2012 doi

  27. [38]

    S., Salii, S

    Kirsanova, M. S., Salii, S. V., Sobolev, A. M., et al. 2017, Open Astronomy, 26, 99, doi: 10.1515/astro-2017-0020

    2017 doi

  28. [40]

    S., Wiebe, D

    Kirsanova, M. S., Wiebe, D. S., Sobolev, A. M., Henkel, C., & Tsivilev, A. P. 2014, MNRAS, 437, 1593, doi: 10.1093/mnras/stt1991 K¨ onyves, V., Andr´ e, P., Men’shchikov, A., et al. 2015, A&A, 584, A91, doi: 10.1051/0004-6361/201525861

    2014 doi

  29. [41]

    E., Glushkova, E

    Koposov, S. E., Glushkova, E. V., & Zolotukhin, I. Y. 2008, A&A, 486, 771, doi: 10.1051/0004-6361:20078630

    2008 doi

  30. [42]

    2014, A&A, 561, A57, doi: 10.1051/0004-6361/201321143

    Krone-Martins, A., & Moitinho, A. 2014, A&A, 561, A57, doi: 10.1051/0004-6361/201321143

    2014 doi

  31. [43]

    2001, MNRAS, 322, 231, doi: 10.1046/j.1365-8711.2001.04022.x

    Kroupa, P. 2001, MNRAS, 322, 231, doi: 10.1046/j.1365-8711.2001.04022.x

    2001

  32. [44]

    V., Samirkhanova, A

    Kulesh, M. V., Samirkhanova, A. E., Carraro, G., et al. 2024, AJ, 167, 212, doi: 10.3847/1538-3881/ad32cc

    2024 doi

  33. [45]

    Kumar, M. S. N., Keto, E., & Clerkin, E. 2006, A&A, 449, 1033, doi: 10.1051/0004-6361:20053104

    2006 doi

  34. [46]

    J., & Lada, E

    Lada, C. J., & Lada, E. A. 2003, ARA&A, 41, 57, doi: 10.1146/annurev.astro.41.011802.094844

    2003 arXiv

  35. [47]

    Lada, E. A. 1992, ApJL, 393, L25, doi: 10.1086/186442 30

    1992 doi

  36. [48]

    A., Kirsanova, M

    Ladeyschikov, D. A., Kirsanova, M. S., Sobolev, A. M., et al. 2021, MNRAS, 506, 4447, doi: 10.1093/mnras/stab1821

    2021 doi

  37. [49]

    Sobolev, A. M. 2016, Astrophysical Bulletin, 71, 208, doi: 10.1134/S1990341316020085

    2016 doi

  38. [50]

    J., Almaini, O., et al

    Lawrence, A., Warren, S. J., Almaini, O., et al. 2007, MNRAS, 379, 1599, doi: 10.1111/j.1365-2966.2007.12040.x

    2007

  39. [51]

    L., & Silvotti, R

    Lodieu, N., P´ erez-Garrido, A., Smart, R. L., & Silvotti, R. 2019, A&A, 628, A66, doi: 10.1051/0004-6361/201935533

    2019 doi

  40. [52]

    2009, A&A, 493, 735, doi: 10.1051/0004-6361:200810519

    Lombardi, M. 2009, A&A, 493, 735, doi: 10.1051/0004-6361:200810519

    2009 doi

  41. [53]

    W., Hoare, M

    Lucas, P. W., Hoare, M. G., Longmore, A., et al. 2008, MNRAS, 391, 136, doi: 10.1111/j.1365-2966.2008.13924.x

    2008

  42. [54]

    G., & Shirley, Y

    Mangum, J. G., & Shirley, Y. L. 2015, PASP, 127, 266, doi: 10.1086/680323

    2015 doi

  43. [55]

    T., Gutermuth, R., Muzerolle, J., et al

    Megeath, S. T., Gutermuth, R., Muzerolle, J., et al. 2016, AJ, 151, 5, doi: 10.3847/0004-6256/151/1/5 Men’shchikov, A. 2013, A&A, 560, A63, doi: 10.1051/0004-6361/201321885 M¨ uller, H. S. P., Thorwirth, S., Roth, D. A., &

    2016 doi

  44. [56]

    2001, A&A, 370, L49, doi: 10.1051/0004-6361:20010367 O’Donnell, J

    Winnewisser, G. 2001, A&A, 370, L49, doi: 10.1051/0004-6361:20010367 O’Donnell, J. E. 1994, ApJ, 422, 158, doi: 10.1086/173713

    2001 doi

  45. [57]

    2011, Journal of Machine Learning Research, 12, 2825

    Pedregosa, F., Varoquaux, G., Gramfort, A., et al. 2011, Journal of Machine Learning Research, 12, 2825

    2011

  46. [58]

    2000, A&A, 361, 660

    Porras, A., Cruz-Gonz´ alez, I., & Salas, L. 2000, A&A, 361, 660

    2000

  47. [59]

    Ryu, J., & Lee, M. G. 2018, ApJ, 856, 152, doi: 10.3847/1538-4357/aab1ff

    2018 doi

  48. [60]

    J., Teuben, P

    Sault, R. J., Teuben, P. J., & Wright, M. C. H. 1995, in Astronomical Society of the Pacific Conference Series, Vol. 77, Astronomical Data Analysis Software and Systems IV, ed. R. A. Shaw, H. E. Payne, & J. J. E. Hayes, 433, doi: 10.48550/arXiv.astro-ph/0612759

    1995 doi arXiv

  49. [61]

    D., & Sembach, K

    Savage, B. D., & Sembach, K. R. 1996, ARA&A, 34, 279, doi: 10.1146/annurev.astro.34.1.279

    1996 doi

  50. [62]

    Schisano, E., Rygl, K. L. J., Molinari, S., et al. 2014, ApJ, 791, 27, doi: 10.1088/0004-637X/791/1/27

    2014 doi

  51. [63]

    Seleznev, A. F. 2016, MNRAS, 456, 3757, doi: 10.1093/mnras/stv2874

    2016 doi

  52. [64]

    2017, MNRAS, 467, 2517, doi: 10.1093/mnras/stx177

    Monaco, L., & Baume, G. 2017, MNRAS, 467, 2517, doi: 10.1093/mnras/stx177

    2017 doi

  53. [65]

    2018, ApJ, 855, 45, doi: 10.3847/1538-4357/aaaccd

    Shimoikura, T., Dobashi, K., Nakamura, F., Matsumoto, T., & Hirota, T. 2018, ApJ, 855, 45, doi: 10.3847/1538-4357/aaaccd

    2018 doi

  54. [66]

    Silverman, B. W. 1986, Density estimation for statistics and data analysis

    1986

  55. [67]

    Heyer, M. H. 2001, ApJ, 551, 747, doi: 10.1086/320230

    2001 doi

  56. [68]

    F., Cutri, R

    Skrutskie, M. F., Cutri, R. M., Stiening, R., et al. 2006, AJ, 131, 1163, doi: 10.1086/498708

    2006 doi

  57. [69]

    Sobolev, A. M. 2017, in Astronomical Society of the Pacific Conference Series, Vol. 510, Stars: From Collapse to Collapse, ed. Y. Y. Balega, D. O. Kudryavtsev, I. I. Romanyuk, & I. A. Yakunin, 20

    2017

  58. [70]

    J., Lauroesch, J

    Sofia, U. J., Lauroesch, J. T., Meyer, D. M., & Cartledge, S. I. B. 2004, ApJ, 605, 272, doi: 10.1086/382592

    2004 doi

  59. [71]

    2012, A&A, 542, A3, doi: 10.1051/0004-6361/201118531

    Solin, O., Ukkonen, E., & Haikala, L. 2012, A&A, 542, A3, doi: 10.1051/0004-6361/201118531

    2012 doi

  60. [72]

    2018, Astrophysics and Space Science

    Stahler, S., ed. 2018, Astrophysics and Space Science

    2018

  61. [73]

    424, The Birth of Star Clusters, doi: 10.1007/978-3-319-22801-3

    Library, Vol. 424, The Birth of Star Clusters, doi: 10.1007/978-3-319-22801-3

    doi

  62. [74]

    Taylor, M. B. 2005, in Astronomical Society of the Pacific Conference Series, Vol. 347, Astronomical Data Analysis Software and Systems XIV, ed. P. Shopbell, M. Britton, & R. Ebert, 29

    2005

  63. [75]

    W., Roellig, T

    Werner, M. W., Roellig, T. L., Low, F. J., et al. 2004, ApJS, 154, 1, doi: 10.1086/422992

    2004 doi

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