Pith. sign in

REVIEW 3 major objections 4 minor 66 references

Key Physical Parameters Influencing Fragmentation and Multiplicity in Dense Cores of Orion A

T0 review · 3 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read The paper claims that in Orion A, dense cores hosting binary or multiple protostars are significantly denser and more supersonically turbulent than cores hosting single protostars, while turbulence-to-gravity and magnetic-field-to-gravity…

desk verdict Worth a serious referee: new magnetic-field null in Orion A core multiplicity, but the density/Mach result partly replicates Luo et al. and has unresolved beam issues. read the letter →

arxiv 2507.22470 v1 pith:LYPRDYOR submitted 2025-07-30 astro-ph.GA astro-ph.SR

Jo-Shui Kao , Hsi-Wei Yen , Shih-Ping Lai This is my paper · ORCID
classification astro-ph.GAastro-ph.SR
keywords starformationdensecoresfragmentationmultiplicityturbulencemagneticfieldsOrionAMachnumber
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

The paper compares 15 dense cores that host binary or multiple protostars with 38 cores hosting a single protostar in the Orion A cloud, using archival JCMT 850 micron continuum, Herschel dust temperature, and Nobeyama N2H+ line data plus JCMT polarization maps. Its central claim is that the fragmented cores have significantly higher density and Mach number, while their ratios of turbulent pressure to gravitational energy and their mass-to-flux ratios are indistinguishable from single-star cores. If correct, this pins core fragmentation on high density and supersonic turbulence and dismisses magnetic support as a decisive factor in these cores. The result would sharpen the search for what sets stellar multiplicity in low-mass star-forming regions.

What carries the argument

The argument rests on a catalogue of 53 dense cores extracted from the JCMT 850 micron map with astrodendro, classified as single or binary/multiple using the VANDAM ALMA survey's protostar positions at 0.1 arcsecond resolution. Core-averaged density comes from 850 micron flux with Herschel dust temperatures, Mach number and non-thermal velocity dispersion from hyperfine fits to Nobeyama N2H+ spectra, and magnetic field strength from POL-2 polarization using the Davis-Chandrasekhar-Fermi method with unsharp-masked angular dispersions. The statistical engine is a bootstrap-resampled cumulative distribution comparison, with Kolmogorov-Smirnov tests applied to each physical parameter to decide which properties separate the two groups.

What would settle it

Re-measure the density and Mach number of the same 53 cores after convolving all data to a common beam that fully resolves the smallest cores, or observe the sample with a matched high-resolution line survey; if the density and Mach number differences between single and multiple cores disappear, the central claim fails.

Watch

Extended reading notes

Core claim

The paper's central discovery, stated in Sections 5.1 and 6, is that dense cores forming binary or multiple systems in Orion A are statistically denser and more supersonically turbulent than cores forming a single protostar. Kolmogorov-Smirnov tests give p-values of 0.005 for core mass, 0.04 for density, 0.006 for Mach number, and 0.002 and 0.009 for the ratios of core radius to Jeans radius and core mass to Jeans mass, all favoring the binary/multiple group. In contrast, the p-values for core radius (0.21), aspect ratio (0.50), turbulent-to-gravitational energy ratio (0.27), magnetic field strength (0.14), and mass-to-flux ratio (0.64) show no significant difference. The number of protostars per core also correlates with density, Mach number, and the Jeans-based ratios. The authors interpret these results as evidence that high density and supersonic turbulence promote local collapse and fragmentation, while the magnetic field has limited influence on whether a core fragments in Orion A.

Load-bearing premise

The inferred core-averaged density and Mach number faithfully represent the pre-fragmentation physical conditions, even though the JCMT, Nobeyama, and Herschel beams are comparable to or larger than the smallest cores in the sample.

Editorial extensions

If this is right

  • If high density and supersonic turbulence drive fragmentation, surveys of core multiplicity can use density and Mach number as predictors of which cores will split into binary or multiple systems.
  • The absence of a mass-to-flux ratio trend suggests that magnetic support is not the dominant regulator of multiplicity in Orion A, so models of low-mass star formation should treat turbulence and gravity, not magnetic fields, as the main fragmentation switches in such cores.
  • The correlation between protostar number and Mach number supports turbulent core fragmentation scenarios in which supersonic fluctuations create multiple density peaks that exceed the local Jeans mass.
  • The null result on the turbulent-to-gravitational energy ratio indicates that turbulence acts as a fragmentation promoter rather than as a stabilizing support, because gravity dominates in most of these cores.
  • Combined with the earlier sample of Luo et al. (2022), the two studies claim that 91 cores across the Orion complex point to the same drivers of fragmentation: gas density and Mach number.

Reading between the lines

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

  • A direct test this paper leaves implicit is a matched-resolution reanalysis: convolving all data to a common beam that covers the smallest cores and re-measuring density and Mach number would show whether the single-versus-multiple differences are robust or partly a resolution artifact.
  • If the trend holds generally, multiplicity fraction should increase toward the densest, most turbulent parts of any star-forming cloud, offering a cloud-scale diagnostic for predicting where wide binaries and higher-order multiples are born.
  • The authors argue that outflow or infall energy is unlikely to inflate the line widths in multiple cores; an independent check using outflow tracers such as CO or SiO would verify whether any of the Mach number excess is feedback-related rather than intrinsic turbulence.
  • Extending the same comparison to other clouds with measured mass-to-flux ratios would test whether Orion A's null magnetic-field result generalizes or is peculiar to its magnetic environment.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. This paper compares the physical properties of 38 dense cores hosting single protostars and 15 dense cores hosting binary or multiple systems in Orion A, using JCMT 850 micron continuum and polarimetry, Herschel dust temperatures, Nobeyama N2H+ line data, and VANDAM multiplicity measurements. The authors derive core mass, density, Jeans length and mass, Mach number, turbulent pressure, DCF magnetic field strength, and mass-to-flux ratio, and then compare the two groups with cumulative distributions and KS tests. The central claim is that fragmented cores have significantly higher density and Mach number, and larger ratios of core radius/mass to Jeans radius/mass, while the energy ratios of turbulence and magnetic field to gravity show no significant difference. The paper interprets this as evidence that density and supersonic turbulence drive core fragmentation in Orion A and that magnetic support is not a dominant factor.

Significance. If the central result holds, the paper provides a valuable observational constraint on the fragmentation of low-mass cores: it supports the turbulent core fragmentation scenario and challenges a strong role for magnetic fields at the ~0.1 pc scale in Orion A. The study extends the work of Luo et al. (2022) by adding magnetic field measurements and by using the high-resolution VANDAM multiplicity catalog. Strengths include a clearly described sample selection, full tables of core properties, Monte Carlo treatment of CDF uncertainties, and a transparent statistical comparison. The main novel contribution is the comparison of the mass-to-flux ratio and turbulent-to-gravitational energy ratio between fragmented and unfragmented cores. However, the headline conclusions depend on resolution-related assumptions and on the treatment of multiple statistical tests, both of which need to be demonstrated before the result can be considered robust.

major comments (3)
  1. [§3.1–3.2, Eq. (1)] The paper states that unresolved cores smaller than the JCMT beam are excluded, yet Table 1 lists many cores with radii well below the 14.6 arcsec FWHM beam (~5800 au at 400 pc), e.g., indices 45 (3200 au), 52 (3400 au), 53 (4400 au). It is not stated whether the reported radii are beam-deconvolved. If they are not, the fitted 2D Gaussian sizes should be at least the beam's own 2-sigma width (~4900 au), so either the radii are deconvolved by an unspecified procedure or the claimed exclusion was not applied. Since the core density in Section 3.2 is computed as M/(4/3 pi R^3), a biased R for the smallest cores could directly produce the apparent density difference between the single and multiple groups. In addition, the N2H+ beam (23.4 arcsec) and Herschel temperature beam (37 arcsec) average over regions 3-5 times the radius of the smallest cores, so the core-averaged Mach number and dust temperature may be contaminated by surrounding gas. The statement in Section 3 that the resolution impact is 'minimal' is asserted rather than demonstrated. Please provide a resolution-matched subsample analysis, a synthetic beam-convolution test, or a clear description of any deconvolution procedure.
  2. [§4, Table 3] The KS tests in Table 3 involve 11 parameters, and no correction for multiple comparisons is applied. The density p-value is 0.04 with an upper uncertainty of 0.15, and the Mach number p-value is 0.006; with a Bonferroni threshold of 0.0045 neither would be individually significant. The abstract and §5.1 highlight these parameters as the key evidence, so the paper should either apply a multiple-testing correction or reframe the conclusion around the more robust Jeans-ratio test (p=0.002) and the mass test (p=0.005), noting that the density and Mach number results are suggestive trends. The Spearman correlations in §4.5 and Figure 7 also involve multiple tests and are reported without adjustment.
  3. [§3.6 and §4.4, Table 2] Magnetic field strengths and mass-to-flux ratios are measured for only 27 of the 53 cores, with different detection fractions for the two groups: 17 of 38 single systems (45%) and 10 of 15 multiple systems (67%). Because polarization detection requires sufficiently bright and polarized emission, the magnetic subsample may be biased toward the same dense, massive cores that drive the main result, so the null KS results for B_pos (p=0.14) and lambda (p=0.64) could be a selection artifact rather than a physical absence of magnetic effects. The authors should test whether restricting the density and Mach number comparisons to the 27 cores with magnetic detections reproduces their headline differences, and should discuss the impact of the unequal detection fractions, possibly by using upper limits for the nondetections.
minor comments (4)
  1. [§3.1] The sentence 'we note that dense core with sizes smaller than the JCMT beam size may not be fully resolved' contains a typo ('core' should be 'cores'), and the exclusion criterion should be stated precisely, e.g., whether 'smaller than the beam' refers to the FWHM or to the 2-sigma width of the fitted Gaussian.
  2. [§3.4] When two velocity components are fitted, the paper selects the component with higher optical depth; the potential bias introduced by this choice should be briefly justified or tested, since the higher-optical-depth component may preferentially trace the densest gas and thus affect the derived velocity dispersion and Mach number.
  3. [§3.6] The angular dispersion is measured after subtracting a smoothed field with a 3x3 pixel (36 arcsec) kernel that is said to correspond to the median core size; the sensitivity of the derived B_pos and mass-to-flux ratio to the kernel choice is not discussed and could be checked, especially for the smallest cores.
  4. [§5.3] The discussion of mass-to-flux ratios in the context of other surveys would benefit from stating explicitly that the DCF-derived B_pos is a plane-of-sky lower limit, so the conclusion that magnetic fields are relatively weak is partly projection-dependent; the text makes this point earlier but the summary and abstract do not.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the paper compares measured core properties across independently classified single and multiple protostar groups, with no fitted parameter renamed as a prediction and no load-bearing self-citation.

full rationale

The paper's central claim is a statistical comparison between two groups defined by the independent VANDAM protostar catalog, using physical parameters measured from separate archival data sets (JCMT 850 um continuum, Herschel dust temperature, Nobeyama N2H+ line data, and JCMT POL-2 polarization). Core density is computed from mass and radius; Mach number is computed from non-thermal line width and sound speed; turbulent and magnetic energy ratios are computed from these measured quantities. No parameter is fitted to the fragmentation outcome, and no quantity is defined in terms of the target result. The reported correlations in Sections 4 and 5 are direct comparisons of measured distributions, not predictions from a model whose inputs were calibrated to the same data. The derived ratios R/λ_Jeans and M/M_Jeans are algebraically related to density and sound speed, but the paper presents them as consequences of the density difference rather than as independent evidence, which is not circularity. The concern that the JCMT, Nobeyama, and Herschel beams are larger than some of the smallest cores is a measurement-validity issue, not a circularity issue: it does not make any claimed result equal to its input by construction or by self-citation. There are no load-bearing self-citations; the cited works are external surveys, simulations, and methods. The paper is self-contained in its derivation of the compared quantities, so the circularity score is 0.

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

The paper uses standard observational recipes. The primary load-bearing choices are the dust opacity kappa_850, the DCF correction Q, the 3x3 pixel unsharp-masking kernel, and the assumptions of spherical geometry and gas-dust temperature equality. No new entities are introduced.

free parameters (4)
  • DCF correction factor Q = 0.5
    Adopted from Ostriker et al. (2001); directly scales Bpos and hence mass-to-flux ratio in Section 3.6.
  • Dust opacity kappa_850 = 0.0125 cm2/g
    Adopted from Johnstone et al. (2017) with 32% uncertainty; linearly scales core mass and density (Eq. 1), the central parameters.
  • Unsharp masking kernel size = 3x3 pixels (36 arcsec)
    Chosen as the median core size; determines the angular dispersion Delta phi_B in Eq. 8 and therefore Bpos.
  • Distance D = 383-392 pc
    From Tobin et al. (2020); enters mass via D^2 in Eq. 1.
assumptions (5)
  • domain assumption Gas temperature equals dust temperature
    Section 3.3 uses T_gas = T_dust to compute sound speed and Jeans length; dust temperatures come from Herschel SED fits.
  • domain assumption Dense cores are spherical for density and gravitational energy estimates
    Sections 3.2 and 3.5 assume spherical geometry to convert mass and radius into density and to compute uG.
  • domain assumption DCF method and Q=0.5 yield valid Bpos
    Section 3.6 assumes energy equipartition between turbulence and magnetic field; no correction for projection or inclination.
  • domain assumption N2H+ line width traces core turbulence, not outflows or infall
    Section 5.1 argues N2H+ is insensitive to warm outflow gas and shows sigma_NT is constant with distance from protostar (Figure 8).
  • domain assumption 850 um dust emission is optically thin
    Section 3.2 verifies tau<0.02 for all cores, so this assumption is supported by their data.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Key Physical Parameters Influencing Fragmentation and Multiplicity in Dense Cores of Orion A." pith.science (2026). https://pith.science/paper/LYPRDYOR

@misc{pith2026250722470,
  author       = {Pith},
  title        = {Pith review of: Key Physical Parameters Influencing Fragmentation and Multiplicity in Dense Cores of Orion A},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/LYPRDYOR}},
  note         = {Machine review of arXiv:2507.22470}
}
abstract

When dense cores in molecular clouds or filamentary structures collapse and form protostars, they may undergo fragmentation and form binary or multiple systems. In this paper, we investigated the key mechanisms influencing fragmentation by comparing the physical conditions of fragmented and unfragmented dense cores (~0.1 pc) in Orion A. Utilizing archival submillimeter continuum data from the James Clerk Maxwell Telescope (JCMT) and the Atacama Large Millimeter/Submillimeter Array survey of Class 0 and I protostars at a 0.''1 resolution, we identified 38 dense cores hosting single protostars and 15 cores hosting binary or multiple systems. We measured the dense cores properties with the Herschel dust temperature, Nobeyama 45m N$_2$H$^+$ J=1-0, and JCMT polarization data. Our results reveal that the dense cores hosting binary/multiple systems exhibit significantly higher density and Mach number compared to those hosting single protostars, while there are no correlations between the occurrence of fragmentation and the energy ratios of turbulence and magnetic field to gravity. Our results suggest that the higher density and supersonic turbulence of the dense cores can lead to local collapse and fragmentation to form binary/multiple systems, while the magnetic field has limited influence on fragmentation in the dense cores in Orion A.

Figures

Figures reproduced from arXiv: 2507.22470 by the authors.

Figure 1
Figure 1. 850 µm continuum map observed with JCMT. The blank area is outside the field of views of the observations. The yellow segments show the magnetic field orientations obtained by rotating the observed polarization orientations by 90◦ . The pixel size of the polarization map is 12 ′′, and there are 5523 polarization detections in total in this map. The zoomed-in view of the green box is shown in the following figure [P… view at source ↗
Figure 2
Figure 2. Zoomed-in view to the green box in [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Cumulative distributions (solid lines) of the (a) radius, (b) aspect ratio, (c) mass, and (d) density of the dense cores with single (red) and binary/multiple (blue) systems in our sample. The light-blue and pink shaded regions represent the 1σ errors of the cumulative distributions. The data points denote the original cumulative distributions directly extracted from the measurements before accounting for the measur… view at source ↗
Figures from the paper (8 more)
Figure 4
Figure 4. Figure 4: (a) core mass and (b) density versus core radii. The blue dots show the cores with single protostar. The red dots show the cores with binary/multiple system. Solid lines show the best-fit power-law relations derived via bootstrap￾ping. Shaded regions represent the 1σ c…
Figure 5
Figure 5. Figure 5: Same as [PITH_FULL_IMAGE:figures/full_fig_p014_5.png]
Figure 6
Figure 6. Figure 6: (a) Ratio of the major to minor axes of the dense cores (aspect ratio) versus their magnetic field strengths. (b) Angle between the magnetic field orientation and ma￾jor axis of the dense cores (∆θB,core) versus the magnetic field strength. at an angular resolution 0. …
Figure 7
Figure 7. Figure 7: Numbers of protostars in the dense cores versus (a) mass density, (b) ratio of core radius to Jeans radius, (c) non-thermal velocity dispersion, and (d) Mach number of the dense cores [PITH_FULL_IMAGE:figures/full_fig_p017_7.png]
Figure 8
Figure 8. Figure 8: Mean non-thermal line width as a function of pro￾jected angular distance to the nearest protostar, measured in 5 ′′ bins. Error bars show the standard deviation within each bin. The red dashed line shows the best-fit linear trend. 0.0005+0.0002 −0.0001 and 0.0007+0.000…
Figure 9
Figure 9. Figure 9: (a) Herschel Dust Temperature Map and (b) N2H + (1–0) velocity and (c) velocity dispersion map from the Nobeyama 45-m data overlaid with the JCMT 850 µm map (contours). The black contour levels are 0.2, 1, and 3 Jy beam−1 [PITH_FULL_IMAGE:figures/full_fig_p020_9.png]
Figure 10
Figure 10. Figure 10: The examples of the N2H + (1–0) spectra and hyperfine fitting with one and two velocity components. Black histograms are the observed spectra. Red lines present our best-fit spectra. One and two velocity components are adopted in the left and right panels, respectivel…
Figure 11
Figure 11. Figure 11: Same as [PITH_FULL_IMAGE:figures/full_fig_p022_11.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

66 extracted references · 18 canonical work pages

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix "arXiv" = new.block " " eprint * " " * new.block " " eprint * " " * if if if FUNCTION format.doi doi empty "" " " doi * " " * if FUNCTION format.pid doi empty eprint empty ur...

  3. [3]

    0 Ded)Iʐ ߹ <ߍ^a 9 ?d۬ Ү8 1gS /\8r8Zhk-\)(_;Cju)Ob I Oc 0P

    thebibliography [1] 20pt to REFERENCES 6pt =0pt -12pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command E...

    2021

  4. [4]

    M., et al

    A \ n ez-L \'o pez , N., Busquet , G., Koch , P. M., et al. 2020, , 644, A52, 10.1051/0004-6361/202039152

    work page doi:10.1051/0004-6361/202039152 2020

  5. [5]

    2010, , 518, L102, 10.1051/0004-6361/201014666

    Andr \'e , P., Men'shchikov , A., Bontemps , S., et al. 2010, , 518, L102, 10.1051/0004-6361/201014666

    doi:10.1051/0004-6361/201014666 2010

  6. [6]

    S., Mac Low , M

    Ballesteros-Paredes , J., Klessen , R. S., Mac Low , M. M., & Vazquez-Semadeni , E. 2007, in Protostars and Planets V, ed. B. Reipurth , D. Jewitt , & K. Keil , 63, 10.48550/arXiv.astro-ph/0603357

    arXiv doi:10.48550/arxiv.astro-ph/0603357 2007

  7. [7]

    1984, , 139, 378

    Benz , W. 1984, , 139, 378

    work page 1984

  8. [8]

    S., et al

    Berry , D., Graves , S., Bell , G. S., et al. 2022, in Astronomical Society of the Pacific Conference Series, Vol. 532, Astronomical Data Analysis Software and Systems XXX, ed. J. E. Ruiz , F. Pierfedereci , & P. Teuben , 559

    work page 2022

Show all 66 references
  1. [9]

    D., et al

    Beuther , H., Gieser , C., Soler , J. D., et al. 2024, , 682, A81, 10.1051/0004-6361/202348117

    2024 doi

  2. [10]

    Boss , A. P. 2000, , 545, L61, 10.1086/317332

    2000 doi

  3. [11]

    P., Fisher , R

    Boss , A. P., Fisher , R. T., Klein , R. I., & McKee , C. F. 2000, , 528, 325, 10.1086/308160

    2000 doi

  4. [12]

    2016, , 819, 139, 10.3847/0004-637X/819/2/139

    Busquet , G., Estalella , R., Palau , A., et al. 2016, , 819, 139, 10.3847/0004-637X/819/2/139

    2016 doi

  5. [13]

    1953, , 118, 113, 10.1086/145731

    Chandrasekhar , S., & Fermi , E. 1953, , 118, 113, 10.1086/145731

    1953 doi

  6. [15]

    2010, , 510, L3, 10.1051/0004-6361/200913597

    Commer c on , B., Hennebelle , P., Audit , E., Chabrier , G., & Teyssier , R. 2010, , 510, L3, 10.1051/0004-6361/200913597

    2010 doi

  7. [16]

    S., Reipurth , B., & Tokunaga , A

    Connelley , M. S., Reipurth , B., & Tokunaga , A. T. 2008, , 135, 2526, 10.1088/0004-6256/135/6/2526

    2008 doi

  8. [17]

    Crutcher , R. M. 2012, , 50, 29, 10.1146/annurev-astro-081811-125514

    2012 doi

  9. [18]

    J., Berry , D

    Currie , M. J., Berry , D. S., Jenness , T., et al. 2014, in Astronomical Society of the Pacific Conference Series, Vol. 485, Astronomical Data Analysis Software and Systems XXIII, ed. N. Manset & P. Forshay , 391

    2014

  10. [19]

    1951, Physical Review, 81, 890, 10.1103/PhysRev.81.890.2

    Davis , L. 1951, Physical Review, 81, 890, 10.1103/PhysRev.81.890.2

    1951 doi

  11. [21]

    1982, , 114, 151

    Dorfi , E. 1982, , 114, 151

    1982

  12. [22]

    2007, , 476, 229, 10.1051/0004-6361:20077270

    Duch \^e ne , G., Bontemps , S., Bouvier , J., et al. 2007, , 476, 229, 10.1051/0004-6361:20077270

    2007 doi

  13. [23]

    2013, , 51, 269, 10.1146/annurev-astro-081710-102602

    Duch \^e ne , G., & Kraus , A. 2013, , 51, 269, 10.1146/annurev-astro-081710-102602

    2013 doi

  14. [24]

    2020, , 251, 20, 10.3847/1538-4365/abba26

    Dutta , S., Lee , C.-F., Liu , T., et al. 2020, , 251, 20, 10.3847/1538-4365/abba26

    2020 doi

  15. [25]

    2018, , 615, A94, 10.1051/0004-6361/201832672

    Fontani , F., Commer c on , B., Giannetti , A., et al. 2018, , 615, A94, 10.1051/0004-6361/201832672

    2018 doi

  16. [26]

    F., Lin , Y.-T., Stone , J

    Gammie , C. F., Lin , Y.-T., Stone , J. M., & Ostriker , E. C. 2003, , 592, 203, 10.1086/375635

    2003 doi

  17. [27]

    2018, , 480, 3511, 10.1093/mnras/sty2016

    Girichidis , P., Seifried , D., Naab , T., et al. 2018, , 480, 3511, 10.1093/mnras/sty2016

    2018 doi

  18. [28]

    P., Kroupa , P., Goodman , A., & Burkert , A

    Goodwin , S. P., Kroupa , P., Goodman , A., & Burkert , A. 2007, in Protostars and Planets V, ed. B. Reipurth , D. Jewitt , & K. Keil , 133, 10.48550/arXiv.astro-ph/0603233

    2007 doi arXiv

  19. [29]

    P., Whitworth , A

    Goodwin , S. P., Whitworth , A. P., & Ward-Thompson , D. 2004 a , , 414, 633, 10.1051/0004-6361:20031594

    2004 doi

  20. [30]

    2004 b , , 423, 169, 10.1051/0004-6361:20040285

    ---. 2004 b , , 423, 169, 10.1051/0004-6361:20040285

    2004 doi

  21. [31]

    2012, , 20, 55, 10.1007/s00159-012-0055-y

    Hennebelle , P., & Falgarone , E. 2012, , 20, 55, 10.1007/s00159-012-0055-y

    2012 doi

  22. [32]

    2019, Frontiers in Astronomy and Space Sciences, 6, 5, 10.3389/fspas.2019.00005

    Hennebelle , P., & Inutsuka , S.-i. 2019, Frontiers in Astronomy and Space Sciences, 6, 5, 10.3389/fspas.2019.00005

    2019

  23. [33]

    Hildebrand , R. H. 1983, , 24, 267

    1983

  24. [34]

    G., & Whitworth , A

    Hosking , J. G., & Whitworth , A. P. 2004, , 347, 1001, 10.1111/j.1365-2966.2004.07274.x

    2004

  25. [35]

    2017, , 836, 132, 10.3847/1538-4357/aa5b95

    Johnstone , D., Ciccone , S., Kirk , H., et al. 2017, , 836, 132, 10.3847/1538-4357/aa5b95

    2017 doi

  26. [36]

    2016, , 817, 167, 10.3847/0004-637X/817/2/167

    Kirk , H., Di Francesco , J., Johnstone , D., et al. 2016, , 817, 167, 10.3847/0004-637X/817/2/167

    2016 doi

  27. [37]

    T., Poteet , C

    Kounkel , M., Megeath , S. T., Poteet , C. A., Fischer , W. J., & Hartmann , L. 2016, , 821, 52, 10.3847/0004-637X/821/1/52

    2016 doi

  28. [38]

    Lee , Y.-N., Offner , S. S. R., Hennebelle , P., et al. 2020, , 216, 70, 10.1007/s11214-020-00699-2

    2020 doi

  29. [39]

    S., Norman , M

    Li , P. S., Norman , M. L., Mac Low , M.-M., & Heitsch , F. 2004, , 605, 800, 10.1086/382652

    2004 doi

  30. [40]

    2022, , 931, 158, 10.3847/1538-4357/ac66d9

    Luo , Q.-y., Liu , T., Tatematsu , K., et al. 2022, , 931, 158, 10.3847/1538-4357/ac66d9

    2022 doi

  31. [41]

    N., Tomisaka , K., Matsumoto , T., & Inutsuka , S.-i

    Machida , M. N., Tomisaka , K., Matsumoto , T., & Inutsuka , S.-i. 2008, , 677, 327, 10.1086/529133

    2008 doi

  32. [42]

    Maury , A., Hennebelle , P., & Girart , J. M. 2022, Frontiers in Astronomy and Space Sciences, 9, 949223, 10.3389/fspas.2022.949223

    2022

  33. [43]

    F., & Ostriker , E

    McKee , C. F., & Ostriker , E. C. 2007, , 45, 565, 10.1146/annurev.astro.45.051806.110602

    2007 arXiv

  34. [44]

    T., McKee , C

    Myers , A. T., McKee , C. F., Cunningham , A. J., Klein , R. I., & Krumholz , M. R. 2013, , 766, 97, 10.1088/0004-637X/766/2/97

    2013 doi

  35. [45]

    Offner , S. S. R., Kratter , K. M., Matzner , C. D., Krumholz , M. R., & Klein , R. I. 2010, , 725, 1485, 10.1088/0004-637X/725/2/1485

    2010 doi

  36. [46]

    Offner , S. S. R., Moe , M., Kratter , K. M., et al. 2023, in Astronomical Society of the Pacific Conference Series, Vol. 534, Protostars and Planets VII, ed. S. Inutsuka , Y. Aikawa , T. Muto , K. Tomida , & M. Tamura , 275, 10.48550/arXiv.2203.10066

    2023 doi arXiv

  37. [47]

    C., Stone , J

    Ostriker , E. C., Stone , J. M., & Gammie , C. F. 2001, , 546, 980, 10.1086/318290

    2001 doi

  38. [48]

    2015, , 453, 3785, 10.1093/mnras/stv1834

    Palau , A., Ballesteros-Paredes , J., V \'a zquez-Semadeni , E., et al. 2015, , 453, 3785, 10.1093/mnras/stv1834

    2015 doi

  39. [49]

    M., et al

    Palau , A., Zhang , Q., Girart , J. M., et al. 2021, , 912, 159, 10.3847/1538-4357/abee1e

    2021 doi

  40. [50]

    2023, in Astronomical Society of the Pacific Conference Series, Vol

    Pattle , K., Fissel , L., Tahani , M., Liu , T., & Ntormousi , E. 2023, in Astronomical Society of the Pacific Conference Series, Vol. 534, Protostars and Planets VII, ed. S. Inutsuka , Y. Aikawa , T. Muto , K. Tomida , & M. Tamura , 193, 10.48550/arXiv.2203.11179

    2023 doi arXiv

  41. [51]

    2017, , 846, 122, 10.3847/1538-4357/aa80e5

    Pattle , K., Ward-Thompson , D., Berry , D., et al. 2017, , 846, 122, 10.3847/1538-4357/aa80e5

    2017 doi

  42. [52]

    S., & Mac Low , M.-M

    Peters , T., Banerjee , R., Klessen , R. S., & Mac Low , M.-M. 2011, , 729, 72, 10.1088/0004-637X/729/1/72

    2011 doi

  43. [53]

    2013, , 777, L33, 10.1088/2041-8205/777/2/L33

    Polychroni , D., Schisano , E., Elia , D., et al. 2013, , 777, L33, 10.1088/2041-8205/777/2/L33

    2013 doi

  44. [54]

    J., & Bate , M

    Price , D. J., & Bate , M. R. 2007, , 377, 77, 10.1111/j.1365-2966.2007.11621.x

    2007

  45. [55]

    R., Eswaraiah , C., et al

    Rawat , V., Samal , M. R., Eswaraiah , C., et al. 2024, , 528, 1460, 10.1093/mnras/stae053

    2024 doi

  46. [56]

    2020, , 644, A29, 10.1051/0004-6361/202039303

    Redaelli , E., Bizzocchi , L., & Caselli , P. 2020, , 644, A29, 10.1051/0004-6361/202039303

    2020 doi

  47. [57]

    2006, , 118, 590, 10.1086/502982

    Rosolowsky , E., & Leroy , A. 2006, , 118, 590, 10.1086/502982

    2006 doi

  48. [58]

    G., Polychroni , D., et al

    Roy , A., Martin , P. G., Polychroni , D., et al. 2013, , 763, 55, 10.1088/0004-637X/763/1/55

    2013 doi

  49. [59]

    M., Zhang , Q., et al

    Sanhueza , P., Jackson , J. M., Zhang , Q., et al. 2017, , 841, 97, 10.3847/1538-4357/aa6ff8

    2017 doi

  50. [60]

    M., Peretto , N., et al

    Tang , Y.-W., Koch , P. M., Peretto , N., et al. 2019, , 878, 10, 10.3847/1538-4357/ab1484

    2019 doi

  51. [61]

    2008, , 60, 407, 10.1093/pasj/60.3.407

    Tatematsu , K., Kandori , R., Umemoto , T., & Sekimoto , Y. 2008, , 60, 407, 10.1093/pasj/60.3.407

    2008 doi

  52. [62]

    J., Looney , L

    Tobin , J. J., Looney , L. W., Li , Z.-Y., et al. 2016, , 818, 73, 10.3847/0004-637X/818/1/73

    2016 doi

  53. [63]

    J., Sheehan , P

    Tobin , J. J., Sheehan , P. D., Megeath , S. T., et al. 2020, , 890, 130, 10.3847/1538-4357/ab6f64

    2020 doi

  54. [64]

    J., Offner , S

    Tobin , J. J., Offner , S. S. R., Kratter , K. M., et al. 2022, , 925, 39, 10.3847/1538-4357/ac36d2

    2022 doi

  55. [65]

    2014, , 439, 3275, 10.1093/mnras/stu127

    Wang , K., Zhang , Q., Testi , L., et al. 2014, , 439, 3275, 10.1093/mnras/stu127

    2014 doi

  56. [66]

    2007, , 119, 855, 10.1086/521277

    Ward-Thompson , D., Di Francesco , J., Hatchell , J., et al. 2007, , 119, 855, 10.1086/521277

    2007 doi

  57. [67]

    M., & Wyckoff , S

    Womack , M., Ziurys , L. M., & Wyckoff , S. 1992, , 387, 417, 10.1086/171094

    1992 doi

  58. [68]

    2024, , 270, 9, 10.3847/1538-4365/acfee5

    Xu , F., Wang , K., Liu , T., et al. 2024, , 270, 9, 10.3847/1538-4365/acfee5

    2024 doi

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.