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REVIEW 4 major objections 6 minor 1 cited by

Peculiar Dust Emission within the Orion Molecular Cloud

T0 review · 4 major / 6 minor · reviewed 2026-08-12 · deepseek-v4-flash

Pith's one-line read Millimeter observations of six Orion protostellar cores confirm that the 3 mm dust emission is too bright for a single opacity power law.

desk verdict Solid new data confirm flattened long-wavelength dust opacity in Orion cores; the NOEMA slope calibration needs scrutiny, but the result holds up. read the letter →

arxiv 2411.12693 v2 pith:JC3UV5UT submitted 2024-11-19 astro-ph.GA astro-ph.SR

classification astro-ph.GAastro-ph.SR
keywords dustopacityindexspectralenergydistributionOrionMolecularCloudprotostellarcoresmillimeterinterferometrydiskcontaminationgraingrowth
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 targets a puzzle in the Orion Molecular Cloud: dust emission at wavelengths beyond 2 mm is brighter than a single power-law opacity law predicts from shorter wavelengths. Using interferometric measurements of six protostellar cores from 1.7 to 3.6 mm, matched to the same spatial scales of about 0.02-0.08 pc, it confirms that the opacity index beta between 2.9 and 3.6 mm is flat (beta approximately -0.16 to 1.45), well below the beta > 1.3 inferred from single-dish data on 0.08 pc scales. If right, a single dust-opacity power law cannot describe these cores across 1.6-3.6 mm, so masses and dust properties derived from extrapolating one band would be biased. The paper argues that in four cores the long-wavelength excess may come largely from large grains in embedded disks, while two cores show different behavior.

What carries the argument

The load-bearing object is the spectral index $\alpha$ defined by S_nu proportional to nu^$\alpha$ on the Rayleigh-Jeans tail, with opacity index $\beta$ = $\alpha$ - 2. The argument works by measuring $\alpha$ separately from interferometric data at 83-102 GHz (2.9-3.6 mm) and 137-177 GHz (1.6-2.2 mm), after cutting visibilities at uv > 5 kilolambda and smoothing beams so that both datasets trace 0.02-0.08 pc scales, then comparing with modified-blackbody fits to single-dish data from 0.16 to 2 mm.

What would settle it

A matched-resolution, matched-uv-coverage comparison of single-dish and interferometric data at 2.9-3.6 mm that included all short spacings and recovered beta > 1.3 would falsify the flattening claim; alternatively, resolving the embedded disks in FIR6B and MMS7 at 3 mm and finding their flux below the extrapolated disk contribution would falsify the proposed disk-contamination explanation.

Watch

Extended reading notes

Core claim

On the paper's own terms, the discovery is that the 2.9-3.6 mm continuum of six OMC 2/3 protostellar cores is systematically elevated relative to a modified blackbody fitted to single-dish data from 0.16 to 2 mm, giving power-law opacity indices beta between approximately -0.16 and 1.45. Four of the six sources have interferometric spectral slopes consistent within one sigma across the two wavelength regimes, indicating a common emission mechanism from 1.7 to 3.6 mm; the other two (FIR2 and MMS6) have slopes differing by more than two sigma. The paper proposes that embedded disks with large grains can bias longer-wavelength fluxes for the consistent sources, while free-free emission and anomalous microwave emission are insufficient to explain the flattening. The conclusion is that combining multi-scale observations or extrapolating single-band observations requires care.

Load-bearing premise

The analysis assumes that, after matching spatial filtering and resolution, the interferometric and single-dish measurements trace the same dust emission components and that a single power law describes the spectrum across 1.7-3.6 mm.

Editorial extensions

If this is right

  • If the flattened slopes are real, dust opacity cannot be a single power law across 1.6-3.6 mm for these cores.
  • Four of the six cores have matching interferometric slopes, so their long-wavelength excess can be explained by a common emission component, likely embedded disks with large grains.
  • Disk contamination can account for up to roughly 70 percent of the 3 mm flux in FIR6B and MMS7, meaning protostellar disk mass can bias core-scale measurements.
  • Free-free emission and anomalous microwave emission cannot explain the flattening.
  • Extrapolating single-band observations to other wavelengths is unsafe at these scales.

Reading between the lines

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

  • Inference: if disk contamination is as large as suggested for FIR6B and MMS7, envelope masses and column densities estimated from 3 mm continuum in similar protostars may be systematically overestimated.
  • Inference: the broken-power-law interpretation predicts that higher-resolution observations that resolve out the disks would recover steeper envelope slopes; this is testable at roughly 0.01 pc resolution.
  • Inference: the same flat-slope signature seen elsewhere in Orion and Serpens suggests the disk-contamination bias may affect cloud-wide surveys, not just individual cores.
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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

4 major / 6 minor

Summary. The paper presents NOEMA 2.9-3.6 mm and ALMA-ACA Band 4/5 (1.6-2.2 mm) continuum observations of six protostellar cores in the OMC 2/3 filament. The authors fit power-law SEDs separately to the NOEMA and ALMA data, derive dust opacity indices beta = alpha - 2, and compare them with single-dish modified-blackbody beta values from Sadavoy et al. (2016). They report flattened beta values between 2.9 and 3.6 mm (beta approximately -0.16 to 1.45), agreement between ALMA and NOEMA slopes for four sources, and disagreement for FIR2 and MMS6. They discuss free-free emission, anomalous microwave emission, disk contamination, and unusual dust properties as possible explanations, and conclude that disk contamination may be significant for some sources and that multi-scale SED analyses require caution.

Significance. If the flattened opacity indices are real, the result is significant: it would confirm that the dust SED in OMC 2/3 cores cannot be described by a single power law from 0.16 to 3.6 mm, with implications for mass estimates and dust grain models. The paper's strengths include the use of independent NOEMA and ALMA-ACA datasets, explicit line-channel flagging, a uv-cut to isolate comparable spatial scales, source flux extraction with background fitting, a Monte Carlo treatment of the ALMA 10% calibration uncertainty, and a direct comparison with GBT/MUSTANG data to test line contamination and missing short-spacing flux. These are appropriate steps that go beyond earlier single-dish studies. However, the central claim rests on the NOEMA-only slopes, and two methodological issues - differing resolution across the NOEMA basebands and unquantified frequency-dependent calibration errors - need to be addressed before the flattened beta values can be considered secure.

major comments (4)
  1. [Section 3.1, Table 2] The four NOEMA basebands are smoothed to different final beams rather than to a common resolution. Table 2 gives final beam sizes of 14.2x8.8 arcsec at 82.7 GHz, 13.2x8.4 arcsec at 86.8 GHz, 11.4x7.9 arcsec at 98.2 GHz, and 10.7x7.6 arcsec at 102.3 GHz. Because several targets show extended emission (e.g., MMS9 and FIR2, Section 4 and Figures 1-2), the lower-frequency points may include more extended flux than the higher-frequency points, which would flatten the NOEMA-only slope in exactly the direction claimed. The paper should smooth all NOEMA basebands to a common beam (e.g., the largest synthesized beam) and re-fit the slopes.
  2. [Section 2.1, Section 3.2] The NOEMA calibration uncertainties are not propagated into the slope errors. Section 2.1 quotes up to 21.6% amplitude loss, <30% pointing error, and <30% focus error, and states that a spectral index of -0.38 was adopted for the RF calibrator. Section 3.2 claims that because the NOEMA data were taken simultaneously with the same flux calibration, the flux calibration errors will not affect the slope; this holds only for a constant gain error across the band. Any frequency dependence in the amplitude loss or an error in the adopted calibrator spectral index changes the relative flux between the 82.7 and 102.3 GHz basebands. A 10% relative amplitude error changes alpha by about 0.45, which is comparable to the reported 1-sigma uncertainties in Table 4. The authors should quantify this effect, for example with a Monte Carlo that draws per-baseband amplitude gains and by testing the sensitivity to the RF calibrator spectral index, before claiming the flattened beta values are robust.
  3. [Section 4, Table 4] The comparison between ALMA and NOEMA slopes uses heterogeneous error bars. The ALMA slopes in Table 4 include the Monte Carlo calibration uncertainty, while the NOEMA slopes are fit-only errors from emcee (Section 3.2). Therefore, the 'consistent within 1-sigma' classification for FIR6B, MMS7, MMS9, and NW167 does not include NOEMA calibration systematics. For MMS7 the slopes differ by only 0.41 with quoted errors of 0.39 and 0.42; adding a plausible calibration uncertainty of order 0.45 to the NOEMA slope would make the agreement test inconclusive. Similarly, the two 'discrepant' sources (FIR2 and MMS6) could change classification. The paper should report a single error budget for each slope that includes both fit and calibration terms, or explicitly state which error bars are used in the comparison.
  4. [Section 3.1] The statement that the ALMA and NOEMA data 'should be consistently tracing emission from the envelope and core over the same spatial scales' is not demonstrated. The uv>5 klambda cut and beam smoothing are necessary, but the two datasets have different baseline distributions and the paper does not show the overlapping uv coverage. A quantitative test, such as fitting the ALMA visibilities at the same uv range as NOEMA or re-imaging with different uv cuts, would show whether residual spatial-filtering differences can explain the ALMA/NOEMA slope discrepancies. Without this, the conclusion that FIR2 and MMS6 trace different emission components is not fully supported.
minor comments (6)
  1. [Section 2.1] The phrase 'and < in 30% focus error' should read 'and <30% in focus error'.
  2. [Section 3.2] The phrase 'we used a random selector to generate two sets of 5000 samples' should say 'a random number generator' or similar.
  3. [Section 6.4] The sentence 'We find that only for FIR2 (α = 2− 3) and MMS6 (α = 3, disk contamination is likely minimal' is missing a closing parenthesis after the α = 3 and should be rephrased for clarity.
  4. [Table 5] The table note refers to 'β-21 values' but should be 'β-B21 values' to match the citation to Bouvier et al. (2021).
  5. [Section 6.1] The phrase 'This result is not unsurprising' is a double negative and should be revised.
  6. [Section 5.3] The source is sometimes abbreviated 'MM6' instead of 'MMS6'; please use the same abbreviation throughout.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the reported slopes are direct fits to independent NOEMA and ALMA data, not constructed from the prior single-dish values.

full rationale

The paper's central quantities, alpha and beta, are obtained by fitting a power-law S_nu = A nu^alpha (Equation 2) directly to flux densities extracted from independent NOEMA and ALMA-ACA observations. The relation beta = alpha - 2 is a standard definitional conversion on the Rayleigh-Jeans tail, not a derivation of the target result from its own inputs. The comparison values beta-SD come from prior single-dish work by Sadavoy et al. (2016) and Mason et al. (2020), some of whose authors overlap with the present paper, but those values are used as external benchmarks rather than as fitted parameters: the new data are not forced to reproduce them, and the measured NOEMA/ALMA slopes are not residuals from those fits. The selection of six sources with previously known elevated 3 mm emission introduces a possible selection bias when the paper says it 'confirms' flattened indices, but this is a sampling and interpretation issue, not a circular derivation: the slopes themselves are still fresh measurements. The paper's own caveats about calibration uncertainties, the 25 K temperature check, and matching uv coverage are correctness risks, not evidence that the conclusion is equivalent to its inputs. No self-citation is load-bearing, no uniqueness theorem is imported, and no known result is merely renamed. The derivation chain from observed fluxes to spectral indices is self-contained, so no circular step can be exhibited.

Assumptions & free parameters 2 free parameters · 4 assumptions · 0 invented entities

The paper introduces no new physical entities. Its central measurement depends on standard dust emission models, a Rayleigh-Jeans approximation, the spatial-scale matching of two interferometers, and assumed disk spectral indices for the contamination estimate. The only fitted quantities are the spectral indices themselves, which are the measured result rather than ad hoc parameters.

free parameters (2)
  • Assumed disk spectral index (alpha=2 upper, alpha=3 lower) = alpha = 2 and alpha = 3
    Used in Equation 3 to extrapolate 0.87 mm disk fluxes from Tobin et al. (2020) to NOEMA and ALMA frequencies. These adopted values, not fitted to the new data, determine the disk contamination fractions in Table 6.
  • Dust temperature for modified-blackbody check = 25 K
    Used in Section 4 to estimate how much the Rayleigh-Jeans power-law fit underestimates beta relative to a modified blackbody; the authors note the true core temperatures on these scales are not constrained and may be higher.
assumptions (4)
  • domain assumption Thermal dust emission follows a modified blackbody with power-law opacity kappa_nu proportional to nu^beta (Equation 1)
    Standard model for dust continuum emission; the central flattening claim depends on interpreting the measured fluxes as thermal dust emission.
  • domain assumption The Rayleigh-Jeans tail approximation I_nu proportional to nu^(2+beta) holds at 83-177 GHz (Equation 2)
    Used to convert fluxes to spectral indices without knowing dust temperatures; the authors estimate a 10-15% beta bias for a 25 K temperature.
  • domain assumption A uv>5 klambda cut and beam smoothing make the ALMA and NOEMA datasets comparable in spatial scale (Section 2.2, Table 2)
    The slope comparison between the two instruments, and hence the split into consistent and inconsistent sources, relies on this matching being sufficient.
  • domain assumption Source fluxes extracted with imfit Gaussian plus background are unbiased (Section 3.1)
    Any residual extended emission or background mismatch would affect the per-band fluxes and therefore the fitted slopes; the background is treated as a free parameter in the fits.

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Cite this review

Pith. "Pith review of Peculiar Dust Emission within the Orion Molecular Cloud." pith.science (2026). https://pith.science/paper/JC3UV5UT

@misc{pith2026241112693,
  author       = {Pith},
  title        = {Pith review of: Peculiar Dust Emission within the Orion Molecular Cloud},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/JC3UV5UT}},
  note         = {Machine review of arXiv:2411.12693}
}
abstract

It is widely assumed that dust opacities in molecular clouds follow a power-law profile with an index, $\beta$. Recent studies of the Orion Molecular Cloud (OMC) 2/3 complex, however, show a flattening in the spectral energy distribution (SED) at $ \lambda > 2$ mm implying non-constant indices on scales $\gtrsim$ 0.08 pc. The origin of this flattening is not yet known but it may be due to the intrinsic properties of the dust grains or contamination from other sources of emission. We investigate the SED slopes in OMC 2/3 further using observations of six protostellar cores with NOEMA from 2.9 mm to 3.6 mm and ALMA-ACA in Band 4 (1.9 -- 2.1 mm) and Band 5 (1.6 -- 1.8 mm) on core and envelope scales of $\sim 0.02 - 0.08$ pc. We confirm flattened opacity indices between 2.9 mm and 3.6 mm for the six cores with $\beta \approx -0.16 - 1.45$, which are notably lower than the $\beta$ values of $> 1.3$ measured for these sources on $0.08$ pc scales from single-dish data. Four sources have consistent SED slopes between the ALMA data and the NOEMA data. We propose that these sources may have a significant fraction of emission coming from large dust grains in embedded disks, which biases the emission more at longer wavelengths. Two sources, however, had inconsistent slopes between the ALMA and NOEMA data, indicating different origins of emission. These results highlight how care is needed when combining multi-scale observations or extrapolating single-band observations to other wavelengths.

Figures

Figures reproduced from arXiv: 2411.12693 by the authors.

Figure 1
Figure 1. Cleaned NOEMA images of all six protostellar cores in OMC 2/3 for the LSB-I baseband at a central frequency of 86.78157 GHz. Contours represent a 5σ level. The synthesized beam is plotted in the bottom left corner. These maps represent the unsmoothed NOEMA observations [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Cleaned continuum emission maps of OMC 2 (left) and OMC 3 (right) at Band 4-High (150.9918 GHz) from ALMA/ACA obser￾vations as an example. These maps correspond to the unsmoothed mosaics with a uv-cut of 5 kλ. A 5σ contour is overlaid on the maps. The six target sources are labeled and the synthesized beam is shown in the lower-left corner. The red boxes represent the regions used for flux extraction with imfit in C… view at source ↗
Figure 3
Figure 3. SEDs for the six sources with best-fit power-law slopes for the ALMA data (dashed) and NOEMA data (dotted). The yellow areas show the uncertainty on the ALMA slope from 10% flux calibration errors. Solid lines show the modified blackbody functions from single-dish data (Herschel at 0.16 – 0.5 mm and IRAM+GISMO at 2 mm) from Sadavoy et al. (2016) [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: SEDs for the six sources with best-fit power-law slopes for the NOEMA data (dotted). The 3 mm GBT MUSTANG (Mason et al. 2020) are included for comparison but were not used in the fitting. To facilitate a robust comparison, the NOEMA data were smoothed to match the 10.8…

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Works this paper leans on

86 extracted references · 19 canonical work pages · cited by 1 Pith paper

  1. [1]

    M., & Dickinson, C

    Ali-Ha¨ımoud, Y ., Hirata, C. M., & Dickinson, C. 2009, MNRAS, 395, 1055, doi: 10.1111/j.1365-2966.2009.14599.x

  2. [2]

    G., Lazarian, A., & Vaillancourt, J

    Andersson, B. G., Lazarian, A., & Vaillancourt, J. E. 2015, ARA&A, 53, 501, doi: 10.1146/annurev-astro-082214-122414 Peculiar Dust Emission in OMC 2/3 17

  3. [3]

    M., Terrell, M., Tripathi, A., et al

    Andrews, S. M., Terrell, M., Tripathi, A., et al. 2018, ApJ, 865, 157, doi: 10.3847/1538-4357/aadd9f

  4. [4]

    1995, in Revista Mexicana de Astronomia y Astrofisica Conference Series, V ol

    Anglada, G. 1995, in Revista Mexicana de Astronomia y Astrofisica Conference Series, V ol. 1, Revista Mexicana de Astronomia y Astrofisica Conference Series, ed. S. Lizano & J. M. Torrelles, 67

  5. [5]

    1998, AJ, 116, 2953, doi: 10.1086/300637

    Anglada, G., Villuendas, E., Estalella, R., et al. 1998, AJ, 116, 2953, doi: 10.1086/300637

  6. [6]

    2000, ApJS, 131, 465, doi: 10.1086/317378

    Aso, Y ., Tatematsu, K., Sekimoto, Y ., et al. 2000, ApJS, 131, 465, doi: 10.1086/317378

  7. [7]

    D., Stark, A

    Bally, J., Langer, W. D., Stark, A. A., & Wilson, R. W. 1987, ApJL, 312, L45, doi: 10.1086/184817

  8. [8]

    2012, A&A, 539, A148, doi: 10.1051/0004-6361/201118136

    Birnstiel, T., Klahr, H., & Ercolano, B. 2012, A&A, 539, A148, doi: 10.1051/0004-6361/201118136

Show all 86 references
  1. [9]

    D., & Payne, D

    Blandford, R. D., & Payne, D. G. 1982, MNRAS, 199, 883, doi: 10.1093/mnras/199.4.883

  2. [10]

    2005, ApJ, 633, 272, doi: 10.1086/432966

    Boudet, N., Mutschke, H., Nayral, C., et al. 2005, ApJ, 633, 272, doi: 10.1086/432966

  3. [11]

    2021, A&A, 653, A117, doi: 10.1051/0004-6361/202141157

    Bouvier, M., L´opez-Sepulcre, A., Ceccarelli, C., et al. 2021, A&A, 653, A117, doi: 10.1051/0004-6361/202141157

  4. [12]

    Briggs, D. S. 1995, PhD thesis, New Mexico Institute of Mining and Technology

  5. [13]

    S., Schwab, F

    Briggs, D. S., Schwab, F. R., & Sramek, R. A. 1999, in Astronomical Society of the Pacific Conference Series, V ol. 180, Synthesis Imaging in Radio Astronomy II, ed. G. B. Taylor, C. L. Carilli, & R. A. Perley, 127

  6. [14]

    J., et al

    Cacciapuoti, L., Macias, E., Maury, A. J., et al. 2023, A&A, 676, A4, doi: 10.1051/0004-6361/202346204 Carrasco-Gonz´alez, C., Sierra, A., Flock, M., et al. 2019, ApJ, 883, 71, doi: 10.3847/1538-4357/ab3d33

  7. [15]

    J., Myers, P

    Caselli, P., Benson, P. J., Myers, P. C., & Tafalla, M. 2002, ApJ, 572, 238, doi: 10.1086/340195

  8. [16]

    2007, in Protostars and Planets V , ed

    Caux, E. 2007, in Protostars and Planets V , ed. B. Reipurth, D. Jewitt, & K. Keil, 47, doi: 10.48550/arXiv.astro-ph/0603018

  9. [17]

    1997, ApJL, 474, L135, doi: 10.1086/310436

    Chini, R., Reipurth, B., Ward-Thompson, D., et al. 1997, ApJL, 474, L135, doi: 10.1086/310436

  10. [18]

    2011, A&A, 535, A124, doi: 10.1051/0004-6361/201116945

    Coupeaud, A., Demyk, K., Meny, C., et al. 2011, A&A, 535, A124, doi: 10.1051/0004-6361/201116945

  11. [19]

    M., et al

    Crapsi, A., Caselli, P., Walmsley, C. M., et al. 2005, ApJ, 619, 379, doi: 10.1086/426472 D’Alessio, P., Calvet, N., & Hartmann, L. 2001, ApJ, 553, 321, doi: 10.1086/320655 de Oliveira-Costa, A., Kogut, A., Devlin, M. J., et al. 1997, ApJL, 482, L17, doi: 10.1086/310684

  12. [20]

    2020, A&A, 642, A177, doi: 10.1051/0004-6361/202038849

    Dib, S., Bontemps, S., Schneider, N., et al. 2020, A&A, 642, A177, doi: 10.1051/0004-6361/202038849

  13. [21]

    R., Mason, B

    Dicker, S. R., Mason, B. S., Korngut, P. M., et al. 2009, ApJ, 705, 226, doi: 10.1088/0004-637X/705/1/226

  14. [22]

    2012, MNRAS, 426, 23, doi: 10.1111/j.1365-2966.2012.21140.x

    Drabek, E., Hatchell, J., Friberg, P., et al. 2012, MNRAS, 426, 23, doi: 10.1111/j.1365-2966.2012.21140.x

  15. [23]

    Draine, B. T. 2011, Physics of the Interstellar and Intergalactic Medium

  16. [24]

    T., & Lazarian, A

    Draine, B. T., & Lazarian, A. 1998, ApJ, 508, 157, doi: 10.1086/306387

  17. [25]

    T., & Li, A

    Draine, B. T., & Li, A. 1999, in American Astronomical Society Meeting Abstracts, V ol. 195, American Astronomical Society Meeting Abstracts, 74.03

  18. [26]

    R., Arce, H

    Feddersen, J. R., Arce, H. G., Kong, S., et al. 2020, ApJ, 896, 11, doi: 10.3847/1538-4357/ab86a9

  19. [27]

    P., Langston, G

    Finkbeiner, D. P., Langston, G. I., & Minter, A. H. 2004, ApJ, 617, 350, doi: 10.1086/425165

  20. [28]

    W., Lang, D., & Goodman, J

    Foreman-Mackey, D., Hogg, D. W., Lang, D., & Goodman, J. 2013, PASP, 125, 306, doi: 10.1086/670067

  21. [29]

    K., Pineda, J

    Friesen, R. K., Pineda, J. E., co-PIs, et al. 2017, ApJ, 843, 63, doi: 10.3847/1538-4357/aa6d58

  22. [30]

    J., Ali, B., et al

    Furlan, E., Fischer, W. J., Ali, B., et al. 2016, VizieR Online Data

  23. [31]

    Catalog, J/ApJS/224/5, doi: 10.26093/cds/vizier.22240005

  24. [32]

    J., Valdivia, V ., et al

    Galametz, M., Maury, A. J., Valdivia, V ., et al. 2019, A&A, 632, A5, doi: 10.1051/0004-6361/201936342

  25. [33]

    2018, ApJ, 853, 171, doi: 10.3847/1538-4357/aaa6d4

    Ginsburg, A., Bally, J., Barnes, A., et al. 2018, ApJ, 853, 171, doi: 10.3847/1538-4357/aaa6d4

  26. [34]

    F., Bergin, E

    Goldsmith, P. F., Bergin, E. A., & Lis, D. C. 1997, ApJ, 491, 615, doi: 10.1086/304986

  27. [35]

    S., Scaife, A

    Greaves, J. S., Scaife, A. M. M., Frayer, D. T., et al. 2018, Nature Astronomy, 2, 662, doi: 10.1038/s41550-018-0495-z

  28. [36]

    M., Maury, A

    Guillet, V ., Girart, J. M., Maury, A. J., & Alves, F. O. 2020, A&A, 634, L15, doi: 10.1051/0004-6361/201937314

  29. [37]

    2018, A&A, 610, A77, doi: 10.1051/0004-6361/201731894

    Hacar, A., Tafalla, M., Forbrich, J., et al. 2018, A&A, 610, A77, doi: 10.1051/0004-6361/201731894

  30. [38]

    2020, ApJ, 895, 126, doi: 10.3847/1538-4357/ab70ba

    Hendler, N., Pascucci, I., Pinilla, P., et al. 2020, ApJ, 895, 126, doi: 10.3847/1538-4357/ab70ba

  31. [39]

    2016, ApJ, 824, 18, doi: 10.3847/0004-637X/824/1/18 H¨ogbom, J

    Hoang, T., Vinh, N.-A., & Quynh Lan, N. 2016, ApJ, 824, 18, doi: 10.3847/0004-637X/824/1/18 H¨ogbom, J. A. 1974, A&AS, 15, 417

  32. [40]

    2018, A&A, 612, A71, doi: 10.1051/0004-6361/201731921

    Juvela, M., He, J., Pattle, K., et al. 2018, A&A, 612, A71, doi: 10.1051/0004-6361/201731921

  33. [41]

    J., Bennett, C

    Kogut, A., Banday, A. J., Bennett, C. L., et al. 1996, The Astrophysical Journal, 464, L5

  34. [42]

    M., Readhead, A

    Leitch, E. M., Readhead, A. C. S., Pearson, T. J., & Myers, S. T. 1997, ApJL, 486, L23, doi: 10.1086/310823

  35. [43]

    I.-H., Liu, H

    Li, J. I.-H., Liu, H. B., Hasegawa, Y ., & Hirano, N. 2017, ApJ, 840, 72, doi: 10.3847/1538-4357/aa6f04

  36. [44]

    2024, ApJ, 963, 104, doi: 10.3847/1538-4357/ad182d

    Liu, Y ., Takahashi, S., Machida, M., et al. 2024, ApJ, 963, 104, doi: 10.3847/1538-4357/ad182d

  37. [45]

    J., et al

    Long, F., Pinilla, P., Herczeg, G. J., et al. 2020, ApJ, 898, 36, doi: 10.3847/1538-4357/ab9a54

  38. [46]

    2022, ApJ, 929, 102, doi: 10.3847/1538-4357/ac5d4f 18 N ozari et al

    Lowe, I., Mason, B., Bhandarkar, T., et al. 2022, ApJ, 929, 102, doi: 10.3847/1538-4357/ac5d4f 18 N ozari et al

  39. [47]

    2020, ApJ, 893, 13, doi: 10.3847/1538-4357/ab734a

    Mason, B., Dicker, S., Sadavoy, S., et al. 2020, ApJ, 893, 13, doi: 10.3847/1538-4357/ab734a

  40. [48]

    2021, ApJ, 916, 23, doi: 10.3847/1538-4357/ac069f

    Matsushita, Y ., Takahashi, S., Ishii, S., et al. 2021, ApJ, 916, 23, doi: 10.3847/1538-4357/ac069f

  41. [49]

    P., Waters, B., Schiebel, D., Young, W., & Golap, K

    McMullin, J. P., Waters, B., Schiebel, D., Young, W., & Golap, K. 2007, in Astronomical Society of the Pacific Conference Series, V ol. 376, Astronomical Data Analysis Software and Systems XVI, ed. R. A. Shaw, F. Hill, & D. J. Bell, 127

  42. [50]

    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

  43. [51]

    2007, A&A, 468, 171, doi: 10.1051/0004-6361:20065771

    Meny, C., Gromov, V ., Boudet, N., et al. 2007, A&A, 468, 171, doi: 10.1051/0004-6361:20065771

  44. [52]

    G., Wink, J

    Mezger, P. G., Wink, J. E., & Zylka, R. 1990, A&A, 228, 95

  45. [53]

    K., & Juvela, M

    Miettinen, Harju, J., Haikala, L. K., & Juvela, M. 2012, A&A, 538, A137, doi: 10.1051/0004-6361/201117849

  46. [54]

    C., & Kataoka, A

    Miotello, A., Kamp, I., Birnstiel, T., Cleeves, L. C., & Kataoka, A. 2023, in Astronomical Society of the Pacific Conference Series, V ol. 534, Protostars and Planets VII, ed. S. Inutsuka, Y . Aikawa, T. Muto, K. Tomida, & M. Tamura, 501, doi: 10.48550/arXiv.2203.09818

  47. [55]

    2014, A&A, 567, A32, doi: 10.1051/0004-6361/201322945

    Miotello, A., Testi, L., Lodato, G., et al. 2014, A&A, 567, A32, doi: 10.1051/0004-6361/201322945

  48. [56]

    Nielbock, M., Chini, R., & M¨uller, S. A. H. 2003, A&A, 408, 245, doi: 10.1051/0004-6361:20030961

  49. [57]

    2011, A&A, 532, A43, doi: 10.1051/0004-6361/201117058

    Paszun, D. 2011, A&A, 532, A43, doi: 10.1051/0004-6361/201117058

  50. [58]

    1994, A&A, 291, 943

    Ossenkopf, V ., & Henning, T. 1994, A&A, 291, 943

  51. [59]

    2011, in EAS Publications Series, V ol

    Pagani, L., Bacmann, A., Steinacker, J., Stutz, A., & Henning, T. 2011, in EAS Publications Series, V ol. 52, EAS Publications Series, ed. M. R¨ollig, R. Simon, V . Ossenkopf, & J. Stutzki, 225–228, doi: 10.1051/eas/1152036

  52. [60]

    P., M´eny, C., & Gromov, V

    Paradis, D., Bernard, J. P., M´eny, C., & Gromov, V . 2011, A&A, 534, A118, doi: 10.1051/0004-6361/201116862

  53. [61]

    Peterson, D. E. 2005, PhD thesis, University of Rochester, New York

  54. [62]

    E., & Megeath, S

    Peterson, D. E., & Megeath, S. T. 2008, in Handbook of Star Forming Regions, V olume I, ed. B. Reipurth, V ol. 4, 590, doi: 10.48550/arXiv.0809.4006

  55. [63]

    2005, in SF2A-2005: Semaine de l’Astrophysique Francaise, ed

    Pety, J. 2005, in SF2A-2005: Semaine de l’Astrophysique Francaise, ed. F. Casoli, T. Contini, J. M. Hameury, & L. Pagani, 721 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2011, A&A, 536, A20, doi: 10.1051/0004-6361/201116470 Planck Collaboration, Ade, P. A. R., Alv...

  56. [64]

    A., Megeath, S

    Poteet, C. A., Megeath, S. T., Watson, D. M., et al. 2011, ApJL, 733, L32, doi: 10.1088/2041-8205/733/2/L32

  57. [65]

    F., & Chini, R

    Reipurth, B., Rodr´ıguez, L. F., & Chini, R. 1999, AJ, 118, 983, doi: 10.1086/300958

  58. [66]

    I., Stutz, A

    Sadavoy, S. I., Stutz, A. M., Schnee, S., et al. 2016, A&A, 588, A30, doi: 10.1051/0004-6361/201527364

  59. [67]

    I., Di Francesco, J., Bontemps, S., et al

    Sadavoy, S. I., Di Francesco, J., Bontemps, S., et al. 2010, ApJ, 710, 1247, doi: 10.1088/0004-637X/710/2/1247

  60. [68]

    I., Di Francesco, J., Johnstone, D., et al

    Sadavoy, S. I., Di Francesco, J., Johnstone, D., et al. 2013, ApJ, 767, 126, doi: 10.1088/0004-637X/767/2/126

  61. [69]

    J., Richer, J

    Salji, C. J., Richer, J. S., Buckle, J. V ., et al. 2015, MNRAS, 449, 1782, doi: 10.1093/mnras/stv369

  62. [70]

    2014, MNRAS, 444, 2303, doi: 10.1093/mnras/stu1596

    Schnee, S., Mason, B., Di Francesco, J., et al. 2014, MNRAS, 444, 2303, doi: 10.1093/mnras/stu1596

  63. [71]

    2004, ApJL, 612, L69, doi: 10.1086/424566

    Shang, H., Lizano, S., Glassgold, A., & Shu, F. 2004, ApJL, 612, L69, doi: 10.1086/424566

  64. [72]

    2009, ApJ, 696, 2234, doi: 10.1088/0004-637X/696/2/2234

    Ercolano, B. 2009, ApJ, 696, 2234, doi: 10.1088/0004-637X/696/2/2234

  65. [73]

    2009, PASJ, 61, 1055, doi: 10.1093/pasj/61.5.1055

    Shimajiri, Y ., Takahashi, S., Takakuwa, S., Saito, M., & Kawabe, R. 2009, PASJ, 61, 1055, doi: 10.1093/pasj/61.5.1055

  66. [74]

    Silsbee, K., Ali-Ha¨ımoud, Y ., & Hirata, C. M. 2011, MNRAS, 411, 2750, doi: 10.1111/j.1365-2966.2010.17882.x

  67. [75]

    M., & Kainulainen, J

    Stutz, A. M., & Kainulainen, J. 2015, A&A, 577, L6, doi: 10.1051/0004-6361/201526243

  68. [76]

    Takahashi, S., Ho, P. T. P., Tang, Y .-W., Kawabe, R., & Saito, M. 2009, ApJ, 704, 1459, doi: 10.1088/0004-637X/704/2/1459

  69. [77]

    2008a, ApJ, 688, 344, doi: 10.1086/592212

    Takahashi, S., Saito, M., Ohashi, N., et al. 2008a, ApJ, 688, 344, doi: 10.1086/592212

  70. [78]

    2008b, Ap&SS, 313, 165, doi: 10.1007/s10509-007-9638-x

    Takahashi, S., Saito, M., Takakuwa, S., & Kawabe, R. 2008b, Ap&SS, 313, 165, doi: 10.1007/s10509-007-9638-x

  71. [79]

    2019, PASJ, 71, S8, doi: 10.1093/pasj/psz100

    Tanabe, Y ., Nakamura, F., Tsukagoshi, T., et al. 2019, PASJ, 71, S8, doi: 10.1093/pasj/psz100

  72. [80]

    J., Testi, L., et al

    Tazzari, M., Clarke, C. J., Testi, L., et al. 2021, MNRAS, 506, 2804, doi: 10.1093/mnras/stab1808

  73. [81]

    2014, in Protostars and Planets VI, ed

    Testi, L., Birnstiel, T., Ricci, L., et al. 2014, in Protostars and Planets VI, ed. H. Beuther, R. S. Klessen, C. P. Dullemond, & T. Henning, 339–361, doi: 10.2458/azu uapress 9780816531240-ch015

  74. [82]

    J., Sheehan, P

    Tobin, J. J., Sheehan, P. D., Megeath, S. T., et al. 2020, ApJ, 890, 130, doi: 10.3847/1538-4357/ab6f64 Tychoniec, Ł., Manara, C. F., Rosotti, G. P., et al. 2020, A&A, 640, A19, doi: 10.1051/0004-6361/202037851

  75. [83]

    Villenave, M., M´enard, F., Dent, W. R. F., et al. 2020, A&A, 642, A164, doi: 10.1051/0004-6361/202038087

  76. [84]

    R., Duchˆene, G., et al

    Villenave, M., Stapelfeldt, K. R., Duchˆene, G., et al. 2022, ApJ, 930, 11, doi: 10.3847/1538-4357/ac5fae

  77. [85]

    2011, A&A, 535, A89, doi: 10.1051/0004-6361/201117394

    Ysard, N., Juvela, M., & Verstraete, L. 2011, A&A, 535, A89, doi: 10.1051/0004-6361/201117394

  78. [86]

    2012, A&A, 542, A21, doi: 10.1051/0004-6361/201118420

    Ysard, N., Juvela, M., Demyk, K., et al. 2012, A&A, 542, A21, doi: 10.1051/0004-6361/201118420

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