Pith. sign in

REVIEW 4 major objections 5 minor 118 references

Nascent Embedded-protostar Survey in Taurus (NEST) II: Measuring Dust Mass, Disk Size, and Gas Mass

T0 review · 4 major / 5 minor · reviewed 2026-08-11 · deepseek-v4-flash

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

Pith's one-line read The first region-complete census of Taurus's 26 embedded disks reports median dust masses of 5.5 Earth masses at 345 GHz and 39 Earth masses at 33 GHz, with CO-based gas-to-dust ratios centered near 26.

desk verdict Useful, honest census of Taurus Class 0/I disks, but the two continuum-derived dust mass scales disagree by ~5.7 and the paper leaves the central medians model-dependent. read the letter →

arxiv 2608.09896 v1 pith:TYMTVVEX submitted 2026-08-10 astro-ph.SR astro-ph.EP

Noshin Yesmin , Patrick Sheehan , John Tobin , Aislinn Coleman-Plante , Nicholas P. Ballering , Tyler L. Bourke , Josh Eisner , Hauyu Baobab Liu
show 1 more author
Zhi-Yun Li
This is my paper · ORCID
classification astro-ph.SRastro-ph.EP
keywords protostarsprotoplanetarydisksClass0/Idustmassgas-to-dustratioTaurusmolecularcloudmillimeterinterferometrydiskradii
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 sets out the first region-complete census of the earliest, envelope-embedded disks in Taurus: 26 Class 0/I protostellar systems observed with high-resolution 345 GHz and 33 GHz continuum imaging plus carbon monoxide isotopologue lines. Its central claim is that these nascent disks have median 345 GHz flux 71 mJy, dust mass 5.5 Earth masses, and radius 28 AU, and median 33 GHz flux 0.43 mJy, dust mass 39 Earth masses, and radius 32 AU, with a CO-inferred median gas mass of $6.7\times10^{-4}$ solar masses. That gas mass translates into a median gas-to-dust ratio of 26 with a 16th-84th percentile range of 8-147, so many embedded disks hold far less gas per unit dust than the canonical interstellar ratio of 100. If correct, this census would mean that Taurus starts its disk lifetimes with dust reservoirs comparable to its older Class II disks at 0.87 mm, and it would place the region squarely between the larger, more massive disks of Orion and the smaller, less massive disks of Ophiuchus. The stakes are concrete: these are the initial solid and gas budgets from which planets must assemble.

What carries the argument

The argument runs on three linked machines. The first is a pair of interferometric continuum images, ALMA at 345 GHz and the VLA at 33 GHz, whose sub-arcsecond beams isolate a compact disk component from the surrounding envelope; every flux and size in the paper comes from two-dimensional Gaussian fits to those images. The second is the standard optically thin, isothermal dust-mass conversion, $M_{\rm dust}=F_\nu d^2/[\kappa_\nu B_\nu(T_{\rm dust})]$, with a luminosity-scaled dust temperature and a single power-law opacity at both frequencies; this is what turns raw flux into the headline Earth masses. The third is a Keplerian-masking plus radiative-transfer pipeline: $^{13}$CO and C$^{18}$O line cubes are masked to the velocity pattern expected from a rotating disk, and the masked line luminosities are matched against a disk-plus-envelope model grid to assign a gas mass. The radii come from deconvolved Gaussian major axes, and the censored medians are computed with a Kaplan-Meier estimator that carries upper limits.

What would settle it

Fit each target's 345 GHz and 33 GHz continuum together with a longer-wavelength 1-3 cm measurement in a source-by-source radiative-transfer model that includes finite optical depth and free-free emission; if the corrected median dust masses fall outside the quoted 68% ranges (3.9-9.4 Earth masses at 345 GHz, 34-52 Earth masses at 33 GHz), or a C$^{17}$O-based gas census shifts the median gas-to-dust ratio far from 26, the headline numbers of this paper would need revision.

Watch

Extended reading notes

Core claim

On the paper's own terms, the discovery is a set of population medians for the youngest disks in a single cloud, measured the same way for every source. At 345 GHz the sample gives a median flux density of 71 mJy (54-107 mJy at 68%), a median dust mass of 5.5 Earth masses (3.9-9.4), and a median radius of 28 AU (25-39); at 33 GHz the corresponding medians are 0.43 mJy (0.41-0.80), 39 Earth masses (34-52), and 32 AU (29-33). The CO-based gas masses have a median of $6.7\times10^{-4}$ solar masses, giving gas-to-dust ratios with a mean of 147, a median of 26, and a 16th-84th percentile range of 8-147. The paper also claims that Taurus Class I disks are fainter and less massive than Orion Class 0/I disks, broadly comparable to Perseus Class I disks, and brighter and more massive than Ophiuchus Class I disks, while Taurus Class 0/I disks are brighter than Taurus Class II disks at both frequencies but not more massive at 345 GHz.

Load-bearing premise

The whole mass census rests on assuming that a single opacity value, a luminosity-only temperature, and optically thin emission can convert each measured continuum flux into a dust mass, even though the paper itself notes that optical depths near 1-2 would raise the true masses by factors of 1.6-2.3, opacity choices vary by an order of magnitude, and the two frequencies disagree by a factor of about 5.7.

Editorial extensions

If this is right

  • If the 345 GHz median dust mass of 5.5 Earth masses is right, Taurus embedded disks start with about the same solid reservoir as the region's older Class II disks, so the steep Class 0/I-to-Class II dust-mass decline reported in cross-region studies is not universal.
  • If the CO-inferred gas masses are right, applying the canonical interstellar gas-to-dust ratio of 100 to Taurus embedded disks would overestimate their total gas by roughly a factor of four at the median.
  • If the 33 GHz dust masses are the more reliable tracer, the census implies roughly seven times more dust than the 345 GHz estimate, which changes the total-mass budget available for planet formation and pushes the inferred gas-to-dust ratios downward.
  • If the region ordering is real, disk assembly models must produce larger, more massive disks in Orion, intermediate ones in Taurus, and compact, low-mass disks in Ophiuchus from environmental differences alone, without invoking different stellar initial mass functions.

Reading between the lines

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

  • A natural extension the authors do not push: the factor-of-about-5.7 offset between the ALMA and VLA dust-mass scales is most simply explained by 345 GHz emission that is not perfectly optically thin, in which case the true dust masses lie between the two medians and the gas-to-dust ratios computed against 345 GHz masses are upper limits on the true ratios.
  • The same Keplerian-masking plus radiative-transfer pipeline could be run on the existing 345 GHz and 33 GHz data for Orion and Ophiuchus, giving a three-region census analyzed with identical assumptions; that would test whether the reported inter-region ordering survives a fully matched analysis.
  • A testable prediction follows from the low end of the gas-to-dust distribution: if ratios near 8 are real, those disks have already lost or sequestered most of their gas or grown their solids enough to lower the apparent dust opacity, and they should show accompanying spectral-index or CO-depletion signatures.
  • Because the Class II comparison adopts a cooler fixed dust temperature (25 K versus 43 K for Class 0/I), part of the 'comparable dust masses' result is sensitive to that temperature choice; recomputing both populations with a common luminosity-scaled temperature law is a cheap check.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 5 minor

Summary. This paper presents ALMA Band 7 (345 GHz) and VLA Ka-band (33 GHz) continuum observations, together with 13CO and C18O J=3–2 line data, for 26 Taurus Class 0/I protostellar systems (35 individual disks). The authors measure dust masses and radii from the continuum using the standard optically thin formula (Eq. 1), report median values of 5.5 M⊕ and 28 AU at 345 GHz and 39 M⊕ and 32 AU at 33 GHz, and infer gas masses by matching Keplerian-masked CO isotopologue luminosities to a radiative-transfer model grid, yielding a median gas mass of 6.7e-4 M⊙ and a median gas-to-dust ratio of 26. They compare the Taurus Class I disks with samples in Orion, Perseus, and Ophiuchus, and with Taurus Class II disks, concluding that Taurus occupies an intermediate position in flux and mass and that Class 0/I disks are brighter but not more massive than Class II at 345 GHz.

Significance. If the quantitative results hold, this would be the first region-complete census of dust masses, sizes, and gas masses for embedded disks in Taurus, providing important constraints on early disk evolution and on the gas-to-dust ratio at the Class 0/I stage. The paper's strengths include a uniformly selected sample, joint ALMA/VLA analysis, careful Kaplan–Meier treatment of upper limits, and explicit sensitivity tests for CO abundance and freeze-out temperature. However, the central numerical claims are weakened by an unresolved factor ~5.7 discrepancy between the two continuum-derived mass scales and by gas-mass estimates that inherit the adopted Keplerian-mask and stellar-mass assumptions. These issues must be addressed before the reported medians can be accepted as robust census values.

major comments (4)
  1. [§3.1, Eq. (1), and the discussion following Table 4] The paper reports median dust masses of 5.5 M⊕ at 345 GHz and 39 M⊕ at 33 GHz for the same sources, using the same opacity law and the same optically thin formula (Eq. 1), and notes that the ALMA-based masses would need to be multiplied by about 5.7 to match the VLA-based distribution. Under the adopted κν ∝ ν scaling, the two bands should yield the same physical mass, so this offset implies that at least one of the two mass scales is biased. The paper's own estimates of the optical-depth bias (factors 1.6–2.3 for τ ~ 1–2) and free-free contamination at 33 GHz (median 10–15%, up to ~100%) are of comparable magnitude. Because both medians are quoted in the Abstract and used in the cross-region and Class II comparisons, the central quantitative claims are not robust until this discrepancy is resolved, either by applying corrections or by propagating the systematics into the reported medians and confidence intervals.
  2. [§3.2 and §3.3] The stellar masses adopted for the Keplerian masks are tuned by eye to match the observed 13CO line extents (Section 3.2), and the model grid used to derive gas masses sets its stellar-mass range from these same Keplerian-mask estimates (Section 3.3). The measured line fluxes, and hence the inferred gas masses, are therefore not statistically independent of the assumed stellar masses and mask geometry. The reported gas-mass uncertainties in Table 5 are 16th–84th percentiles of the match-weighted model distribution and do not include uncertainties in the adopted M*, inclination, position angle, z/r, or rout values. The consistency check with radiative-transfer stellar masses for a subset is encouraging, but a quantitative sensitivity analysis of the inferred gas masses to plausible variations in the mask parameters is needed to support the median gas mass of 6.7e-4 M⊙ and the resulting gas-to-dust ratios.
  3. [§3.3 and Figure 9] The gas-to-dust ratios are computed using the 345 GHz dust masses from Eq. (1), which the paper itself notes are biased low by optically thick emission (Section 3.1, factors 1.6–2.3 for τ~1–2 and more for higher τ). Because the CO-inferred gas masses are not corrected for this bias, the reported median gas-to-dust ratio of 26 and the 16th–84th percentile range of 8–147 are systematically too high. This propagation should be either quantified and corrected, or the gas-to-dust ratio distribution should be presented with this caveat as the dominant uncertainty rather than as a measured range.
  4. [§4.2 and Abstract] The statement that Taurus Class 0/I disks are comparable in 345 GHz dust mass to Taurus Class II disks (medians 5.5 vs 5.6 M⊕) is used to argue that embedded disks are not more massive than Class II disks. If the Class 0/I disks are partially optically thick while the Class II sample is not, this equality could be an artifact of the bias discussed in Section 3.1. The paper discusses this possibility in Section 4.2, but the Abstract and Section 5 present the conclusion without that caveat. A quantitative test (e.g., comparing spectral indices or applying an optical-depth correction) is needed before this conclusion can be stated as a primary result.
minor comments (5)
  1. [§2.2] The sentence 'our ALMA datasets includ both 12 m and ACA 7 m coverage' contains a typo; 'includ' should be 'include'.
  2. [§3.1] Please verify the opacity power-law exponent in the formula κν = 10 (ν/1000 GHz) cm2 g−1; the stated values κ345 = 3.45 and κ33 = 0.33 correspond to κν = 10(ν/1000 GHz) cm2/g with exponent unity, so the printed formula should be checked for a missing or misplaced exponent.
  3. [Figure 4 caption] The phrase 'outliers fall below 10^3 in luminosity' is unclear; if the intended threshold is 10^-3, as the surrounding text suggests, the exponent should be corrected.
  4. [Table 5] The entry for 04264+2433AB lists two systemic velocities and two stellar masses; please add an explanatory note clarifying which value applies to which component or stating that the mask was constructed for the combined system.
  5. [§4.1] The description of the VANDAM–Perseus 9 mm flux as 'averaging the two bands' could introduce a bias if the spectral index varies across the sample; a short justification or a consistency check using the measured spectral indices would improve clarity.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the dust and gas mass derivations are not equivalent to their inputs by construction.

full rationale

The central quantitative claims rest on two independent measurement chains. The dust masses follow from the standard formula Mdust = Fnu d^2 / (kappa_nu B_nu(Tdust)) applied to measured ALMA and VLA fluxes, with adopted opacities and luminosity-scaled temperatures; no parameter is fit to the headline medians. The factor-of-~5.7 offset between the 345 GHz and 33 GHz mass scales is explicitly discussed by the paper as a systematic uncertainty (opacity prescription, optical depth, free-free contamination), not as a derivation that reduces one mass to the other. The gas masses are obtained by comparing observed 13CO and C18O luminosities to a RADMC-3D model grid with fixed ISM abundances; although the grid's stellar-mass range is informed by the Keplerian-mask estimates and the observed line kinematics, the inferred gas mass is selected by luminosity matching and is not set equal to the adopted stellar mass, mask size, or dust mass. The paper transparently labels the adopted stellar masses as practical mask-construction choices rather than precise measurements. Self-citations to Sheehan et al. (2022), Tobin et al. (2020), and Plante et al. (2026) supply external modeling, calibration, and sample characterization, but the central results are not forced by those citations, and no uniqueness theorem or ansatz is smuggled in. The acknowledged limitations (optical depth, CO abundance, model dependence) are correctness risks, not circularity.

Assumptions & free parameters 6 free parameters · 9 assumptions · 0 invented entities

All quantitative results are grounded in standard observational calibrations and model choices rather than new physics. The central gas masses are effectively grid fits to line luminosities under assumed abundances. No new physical entities are introduced.

free parameters (6)
  • Dust opacity normalization kappa_nu = 10 (nu/1000 GHz)^2 cm2/g = kappa_345 = 3.45 cm2/g, kappa_33 = 0.33 cm2/g
    Adopted from Beckwith & Sargent (1991) in Eq. 1. The paper notes opacity prescriptions can vary by an order of magnitude, so this choice sets the absolute dust mass scale.
  • Dust temperature normalization T0 = 43 K for Class 0/I, 25 K for Class II
    Used in Tdust = T0 (Lbol/Lsun)^0.25 in Eq. 2, following Tobin et al. (2020). The choice affects inferred dust masses and the Class 0/I versus Class II comparison.
  • CO abundance x_CO = 1e-4 relative to H2
    Assumed ISM abundance in the radiative-transfer grid (Section 3.3). Sensitivity tests show x_CO = 1e-5 or 1e-3 changes inferred gas masses by factors of roughly 1.4-10.
  • CO isotopologue ratios = [CO]/[13CO] = 70, [CO]/[C18O] = 550
    Fixed ISM ratios from Wilson & Rood (1994) used to compute isotopologue abundances; isotope-selective photodissociation is not included (Section 3.3).
  • CO freeze-out temperature = 20 K
    Below 20 K, gas-phase CO is multiplied by 1e-8 in the models (Section 3.3). A 5 K change alters line luminosities by 1-31% and inferred gas masses by roughly 25-50%.
  • Per-source stellar masses and mask geometry = M* 0.1-1.8 Msun, z/r 0.1-0.5, r_out 0.5-3.0 R_dust (Table 5)
    M*, z/r, and r_out are adjusted by eye to match observed line emission when constructing Keplerian masks (Section 3.2). These are fitting choices, not independent measurements, and they influence the measured line fluxes.
assumptions (9)
  • standard math Planck function and radiative transfer equations
    Used for dust mass conversion (Eq. 1) and line luminosity modeling (Section 3.3).
  • domain assumption Keplerian rotation model for disk gas
    The Keplerian mask assumes line emission follows Keplerian rotation around the central protostar (Section 3.2), which is the basis for separating disk from envelope.
  • domain assumption Compact continuum emission is dominated by disk dust
    Section 3.1 assumes the compact 345/33 GHz emission is circumstellar disk, citing Sheehan et al. (2022) radiative-transfer models.
  • domain assumption Dust emission is optically thin and isothermal
    Eq. 1 uses the optically thin relation; the paper notes optical depths of order 1-2 would bias masses low by factors of 1.6-2.3 (Section 3.1).
  • domain assumption CO isotopologue emission traces total disk gas with ISM abundances
    Section 3.3 fixes x_CO = 1e-4 and isotopologue ratios, with freeze-out only, and no chemical conversion or selective photodissociation; if CO is depleted, gas masses are underestimated.
  • domain assumption Bolometric luminosity is a proxy for stellar luminosity
    Used for the Tdust scaling in Eq. 2 for embedded Class 0/I sources (Section 3.1).
  • domain assumption Taurus and Orion protostellar populations share the same IMF
    Section 4.1 interprets Orion's higher disk masses as due to more massive protostars under a common IMF; if false, the environmental interpretation is invalid.
  • domain assumption Free-free emission at 33 GHz is small on average
    No free-free correction is applied; empirical luminosity relations suggest median contributions of 10-15% but up to 100% in some sources (Section 3.1).
  • ad hoc to paper Per-source mask parameters tuned by eye are adequate
    Section 3.2 and Table 5 footnotes: M*, z/r, and r_out are adjusted per source based on the observed emission to make the masks fit, which can bias flux measurements and gas masses.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Nascent Embedded-protostar Survey in Taurus (NEST) II: Measuring Dust Mass, Disk Size, and Gas Mass." pith.science (2026). https://pith.science/paper/TYMTVVEX

@misc{pith2026260809896,
  author       = {Pith},
  title        = {Pith review of: Nascent Embedded-protostar Survey in Taurus (NEST) II: Measuring Dust Mass, Disk Size, and Gas Mass},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/TYMTVVEX}},
  note         = {Machine review of arXiv:2608.09896}
}
read the original abstract

Envelope-embedded protostellar disks represent the earliest stage of protoplanetary disk evolution, but their masses and sizes are difficult to measure because disk emission is entangled with the envelope. We analyze 26 protostellar disk systems in Taurus using ALMA Band 7 (345 GHz; ~0.3'') and VLA Ka-band (33 GHz; ~0.2'') continuum observations, together with molecular-line data to constrain disk gas masses. At 345 GHz, the median flux density, dust mass, and radius are 71 mJy, 5.5 M_Mearth, and 28 AU, with 68% ranges of 54-107 mJy, 3.9-9.4 M_Mearth, and 25-39 AU. At 33 GHz, the corresponding medians are 0.43 mJy, 39 M_Mearth, and 32 AU, with ranges of 0.41-0.80 mJy, 34-52 M_Mearth, and 29-33 AU. Taurus Class I disks are fainter and less massive than those in Orion, comparable to Perseus Class I disks but fainter than Perseus Class 0 disks, and brighter and more massive than those in Ophiuchus. Within Taurus, Class 0/I disks are brighter than Class II disks at both frequencies, although their inferred dust masses are comparable at 345 GHz and slightly higher at 33 GHz. Radiative-transfer modeling of CO isotopologue emission yields a median gas mass of 6.7 x 10^-4 M_Msun. The resulting CO-inferred gas-to-dust ratios span a broad range, with a mean of 147 +/- 75, a median of 26, and a 16th-84th percentile range of 8-147. This distribution overlaps the Taurus Class II population at the low end and ISM-like or higher values, including the AGE-PRO Ophiuchus Class 0/I population, at the high end.

Figures

Figures reproduced from arXiv: 2608.09896 by the authors.

Figure 1
Figure 1. Representative continuum maps. ALMA 345 GHz (12 m + 7 m arrays) and VLA 33 GHz images are primary–beam corrected; restoring beams are shown at lower left and 100 AU scale bars at lower right. Source 04166+2706 illustrates a compact, marginally resolved disk, while 04288+1802 shows a binary system with extended circumbinary emission. Continuum maps for the full sample are provided in Appendix A. fixed. Because Mdust … view at source ↗
Figure 2
Figure 2. Cumulative distribution functions (CDFs) of ALMA and VLA continuum properties for the Taurus Class 0/I sample: (a) flux densities, (b) dust masses, and (c) dust radii. Shaded regions show 68% confidence intervals from Kaplan–Meier survival analysis (i.e., statistical uncertainty from finite sample size and censoring), and do not include measurement uncertainties in the individual fluxes/masses/radii. We computed cum… view at source ↗
Figure 3
Figure 3. Example channel maps illustrating the Keplerian mask used in our analysis. Shown here are 13CO (J=3-2) channel maps for IRAS 04016+2610 at velocities reported relative to the systemic velocity (vsys ≈ 7 km s−1 ). The black contour shows the Keplerian mask computed for the best-fit stellar mass (1.45M⊙) and an outer radius rout = 1.0 × Rdust. At each velocity channel, the mask isolates emission consistent with Kepler… view at source ↗
Figures from the paper (8 more)
Figure 4
Figure 4. Figure 4: Comparison of model grid luminosities and observed CO isotopologue luminosities. The colored points show the modeled L(C18O) versus L( 13CO) values for a range of gas masses, based on a grid of 29,160 paired 13CO and C18O models. The black points with error bars repres…
Figure 5
Figure 5. Figure 5: Cumulative distribution functions (CDFs) of continuum flux densities for Class 0/I disks across different star-forming regions. Panels (a) and (b) show 345 GHz and 33 GHz flux densities, respectively. All flux densities are scaled to a common distance of 140 pc for dir…
Figure 6
Figure 6. Figure 6: Cumulative distribution functions (CDFs) of dust masses inferred from continuum emission for Class 0/I disks across different star-forming regions. Panels (a) and (b) show dust masses derived from 345 GHz and 33 GHz data, respectively. Shaded regions show 68% confidenc…
Figure 7
Figure 7. Figure 7: Cumulative distribution functions (CDFs) of dust disk radii at 345 GHz for Class 0/I disks in Taurus, Orion, and Ophiuchus. Shaded regions show 68% confidence intervals from Kaplan–Meier survival analysis, which incorporates upper limits. For the Taurus sample, only th…
Figure 8
Figure 8. Figure 8: Cumulative distribution functions (CDFs) of continuum flux densities and corresponding dust masses for Taurus Class 0/I and Class II disks at 345 and 33 GHz. The 345 GHz Class II comparison sample is taken from Andrews et al. (2013), while the 33 GHz Class II compariso…
Figure 9
Figure 9. Figure 9: Gas masses (top) and gas-to-dust mass ratios (bottom) for our Taurus Class 0/I sample. The dust masses used to compute these gas-to-dust ratios are derived from the ALMA 345 GHz continuum data (Section 3.1). In the top panel, error bars show the asymmetric 16th–84th pe…
Figure 10
Figure 10. Figure 10: Continuum images of 04016+2610 observed with ALMA at 345 GHz (left) and the VLA at 33 GHz (right). The complete figure set containing continuum images of all sources is available in the online journal. the brighter component, whereas for the wider binary 04191+1523AB,…
Figure 11
Figure 11. Figure 11: Representative 13CO channel maps for 04016+2610. Each panel is labeled by the channel velocity relative to the systemic velocity, and the black contours show the Keplerian mask used in the analysis. The full figure set, which includes both 13CO and C18O channel maps f…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

118 extracted references · 6 canonical work pages

  1. [1]

    L., P´ erez, L

    ALMA Partnership, Brogan, C. L., P´ erez, L. M., et al. 2015, ApJL, 808, L3, doi: 10.1088/2041-8205/808/1/L3 AMI Consortium, Scaife, A. M. M., Buckle, J. V., et al. 2012, MNRAS, 420, 3334, doi: 10.1111/j.1365-2966.2011.20254.x

    arXiv 2015

  2. [2]

    C., Stephens, I

    Andersen, B. C., Stephens, I. W., Dunham, M. M., et al. 2019, ApJ, 873, 54, doi: 10.3847/1538-4357/ab05c7

    doi:10.3847/1538-4357/ab05c7 2019

  3. [3]

    R., Williams, J

    Anderson, A. R., Williams, J. P., van der Marel, N., et al. 2022, ApJ, 938, 55, doi: 10.3847/1538-4357/ac8ff0

    doi:10.3847/1538-4357/ac8ff0 2022

  4. [4]

    Andrews, S. M. 2020, ARA&A, 58, 483, doi: 10.1146/annurev-astro-031220-010302

    doi:10.1146/annurev-astro-031220-010302 2020

  5. [5]

    M., Rosenfeld, K

    Andrews, S. M., Rosenfeld, K. A., Kraus, A. L., & Wilner, D. J. 2013, ApJ, 771, 129, doi: 10.1088/0004-637X/771/2/129

    doi:10.1088/0004-637x/771/2/129 2013

  6. [6]

    M., & Williams, J

    Andrews, S. M., & Williams, J. P. 2005, ApJ, 631, 1134, doi: 10.1086/432712

    doi:10.1086/432712 2005

  7. [7]

    M., Huang, J., P´ erez, L

    Andrews, S. M., Huang, J., P´ erez, L. M., et al. 2018, ApJL, 869, L41, doi: 10.3847/2041-8213/aaf741 28 Figure 11.Representative 13CO channel maps for 04016+2610. Each panel is labeled by the channel velocity relative to the systemic velocity, and the black contours show the Keplerian mask used in the analysis. The full figure set, which includes both 13...

    doi:10.3847/2041-8213/aaf741 2018

  8. [8]

    P., van der Marel, N., et al

    Ansdell, M., Williams, J. P., van der Marel, N., et al. 2016, ApJ, 828, 46, doi: 10.3847/0004-637X/828/1/46 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f Astropy Col...

    doi:10.3847/0004-637x/828/1/46 2016

Show all 118 references
  1. [9]

    P., & Eisner, J

    Ballering, N. P., & Eisner, J. A. 2019, AJ, 157, 144, doi: 10.3847/1538-3881/ab0a56

    2019 doi

  2. [10]

    A., Carpenter, J

    Barenfeld, S. A., Carpenter, J. M., Ricci, L., & Isella, A. 2016, ApJ, 827, 142, doi: 10.3847/0004-637X/827/2/142

    2016 doi

  3. [11]

    Beckwith, S. V. W., & Sargent, A. I. 1991, ApJ, 381, 250, doi: 10.1086/170646

    1991 doi

  4. [12]

    2014, in Protostars and Planets VI, ed

    Benz, W., Ida, S., Alibert, Y., Lin, D., & Mordasini, C. 2014, in Protostars and Planets VI, ed. H. Beuther, R. S

    2014

  5. [14]

    C., Savage, B

    Bohlin, R. C., Savage, B. D., & Drake, J. F. 1978, ApJ, 224, 132, doi: 10.1086/156357

    1978 doi

  6. [15]

    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

    2021 doi

  7. [16]

    K., Bergin, E., Zhang, K., et al

    Calahan, J. K., Bergin, E., Zhang, K., et al. 2021, ApJ, 908, 8, doi: 10.3847/1538-4357/abd255

    2021 doi

  8. [17]

    F., Liu, H

    Cazzoletti, P., Manara, C. F., Liu, H. B., et al. 2019, A&A, 626, A11, doi: 10.1051/0004-6361/201935273

    2019 doi

  9. [18]

    M., Gurwell, M

    Chung, C.-Y., Andrews, S. M., Gurwell, M. A., et al. 2024, ApJS, 273, 29, doi: 10.3847/1538-4365/ad528b

    2024 doi

  10. [19]

    2025, ApJS, 277, 45, doi: 10.3847/1538-4365/adb717 D’Alessio, P., Calvet, N., Hartmann, L., Franco-Hern´ andez, R., & Serv ´ ın, H

    Chung, C.-Y., Tsai, A.-L., Wright, M., et al. 2025, ApJS, 277, 45, doi: 10.3847/1538-4365/adb717 D’Alessio, P., Calvet, N., Hartmann, L., Franco-Hern´ andez, R., & Serv ´ ın, H. 2006, ApJ, 638, 314, doi: 10.1086/498861

    2025 doi

  11. [20]

    2019, Journal of Open Source Software, 4, 1317, doi: 10.21105/joss.01317

    Davidson-Pilon, C. 2019, Journal of Open Source Software, 4, 1317, doi: 10.21105/joss.01317

    2019 doi

  12. [21]

    2015, ApJ, 809, 93, doi: 10.1088/0004-637X/809/1/93

    Dong, R., Zhu, Z., & Whitney, B. 2015, ApJ, 809, 93, doi: 10.1088/0004-637X/809/1/93

    2015 doi

  13. [22]

    P., Juhasz, A., Pohl, A., et al

    Dullemond, C. P., Juhasz, A., Pohl, A., et al. 2012, RADMC-3D: A multi-purpose radiative transfer tool, Astrophysics Source Code Library, record ascl:1202.015

    2012

  14. [23]

    1996, A&A, 309, 493

    Dutrey, A., Guilloteau, S., Duvert, G., et al. 1996, A&A, 309, 493

    1996

  15. [24]

    Eisner, J. A. 2012, ApJ, 755, 23, doi: 10.1088/0004-637X/755/1/23

    2012 doi

  16. [25]

    A., Arce, H

    Eisner, J. A., Arce, H. G., Ballering, N. P., et al. 2018, ApJ, 860, 77, doi: 10.3847/1538-4357/aac3e2

    2018 doi

  17. [26]

    J., Looney, L

    Encalada, F. J., Looney, L. W., Tobin, J. J., et al. 2021, ApJ, 913, 149, doi: 10.3847/1538-4357/abf4fd

    2021 doi

  18. [27]

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

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

    2013 doi

  19. [28]

    2008, ApJS, 176, 184, doi: 10.1086/527301

    Furlan, E., McClure, M., Calvet, N., et al. 2008, ApJS, 176, 184, doi: 10.1086/527301

    2008 doi

  20. [29]

    J., Ali, B., et al

    Furlan, E., Fischer, W. J., Ali, B., et al. 2016, ApJS, 224, 5, doi: 10.3847/0067-0049/224/1/5

    2016 doi

  21. [30]

    Galli, P. A. B., Loinard, L., Ortiz-L´ eon, G. N., et al. 2018, ApJ, 859, 33, doi: 10.3847/1538-4357/aabf91

    2018 doi

  22. [31]

    G., et al

    Garufi, A., Ginski, C., van Holstein, R. G., et al. 2024, A&A, 685, A53, doi: 10.1051/0004-6361/202347586

    2024 doi

  23. [32]

    2025, A&A, 694, A290, doi: 10.1051/0004-6361/202452496

    Garufi, A., Carrasco-Gonz´ alez, C., Mac ´ ıas, E., et al. 2025, A&A, 694, A290, doi: 10.1051/0004-6361/202452496

    2025 doi

  24. [33]

    F., Bergin, E

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

    1997 doi

  25. [34]

    S., & Rice, W

    Greaves, J. S., & Rice, W. K. M. 2010, MNRAS, 407, 1981, doi: 10.1111/j.1365-2966.2010.17043.x

    2010

  26. [35]

    Y., Bohn, A

    Haffert, S. Y., Bohn, A. J., de Boer, J., et al. 2019, Nature Astronomy, 3, 749, doi: 10.1038/s41550-019-0780-5

    2019 doi

  27. [36]

    2025, MNRAS, 541, 4025, doi: 10.1093/mnras/staf1220

    Zhao, C. 2025, MNRAS, 541, 4025, doi: 10.1093/mnras/staf1220

    2025 doi

  28. [37]

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

    1983

  29. [38]

    G., Maureira, M

    Hsieh, C.-H., Arce, H. G., Maureira, M. J., et al. 2024, ApJ, 973, 138, doi: 10.3847/1538-4357/ad6152 —. 2025, A&A, 700, A235, doi: 10.1051/0004-6361/202555174

    2024 doi

  30. [39]

    2013, ApJ, 764, 114, doi: 10.1088/0004-637X/764/2/114

    Hsu, W.-H., Hartmann, L., Allen, L., et al. 2013, ApJ, 764, 114, doi: 10.1088/0004-637X/764/2/114

    2013 doi

  31. [40]

    Hunter, J. D. 2007, Computing in Science and Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

    2007 doi

  32. [41]

    R., Indebetouw, R., Brogan, C

    Hunter, T. R., Indebetouw, R., Brogan, C. L., et al. 2023, PASP, 135, 074501, doi: 10.1088/1538-3873/ace216

    2023 doi

  33. [42]

    2004, ApJL, 611, L45, doi: 10.1086/423737

    Johnstone, D., Di Francesco, J., & Kirk, H. 2004, ApJL, 611, L45, doi: 10.1086/423737

    2004 doi

  34. [43]

    Kamp, I., & Dullemond, C. P. 2004, ApJ, 615, 991, doi: 10.1086/424703

    2004 doi

  35. [44]

    J., G´ omez, M., & Whitney, B

    Kenyon, S. J., G´ omez, M., & Whitney, B. A. 2008, in Handbook of Star Forming Regions, Volume I, ed. B. Reipurth, Vol. 4, 405, doi: 10.48550/arXiv.0810.1298

    2008 doi arXiv

  36. [45]

    2018, A&A, 617, A44, doi: 10.1051/0004-6361/201832957

    Keppler, M., Benisty, M., M¨ uller, A., et al. 2018, A&A, 617, A44, doi: 10.1051/0004-6361/201832957

    2018 doi

  37. [46]

    B., Lai, S.-P., et al

    Ko, C.-L., Liu, H. B., Lai, S.-P., et al. 2020, ApJ, 889, 172, doi: 10.3847/1538-4357/ab5e79

    2020 doi

  38. [47]

    R., Bergin, E

    Krijt, S., Schwarz, K. R., Bergin, E. A., & Ciesla, F. J. 2018, ApJ, 864, 78, doi: 10.3847/1538-4357/aad69b

    2018 doi

  39. [48]

    J., Alves, J., & Lada, E

    Lada, C. J., Alves, J., & Lada, E. A. 1996, AJ, 111, 1964, doi: 10.1086/117933

    1996 doi

  40. [49]

    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

    2017 doi

  41. [50]

    N., & Simon, J

    Li, R., Youdin, A. N., & Simon, J. B. 2019, ApJ, 885, 69, doi: 10.3847/1538-4357/ab480d 30

    2019 doi

  42. [51]

    Liu, H. B. 2019, ApJL, 877, L22, doi: 10.3847/2041-8213/ab1f8e —. 2021, ApJ, 914, 25, doi: 10.3847/1538-4357/abf8b6

    2019 doi

  43. [52]

    J., Pascucci, I., et al

    Long, F., Herczeg, G. J., Pascucci, I., et al. 2017, ApJ, 844, 99, doi: 10.3847/1538-4357/aa78fc

    2017 doi

  44. [53]

    J., et al

    Long, F., Pinilla, P., Herczeg, G. J., et al. 2018, The Astrophysical Journal, 869, 17, doi: 10.3847/1538-4357/aae8e1

    2018 doi

  45. [54]

    Lynden-Bell, D., & Pringle, J. E. 1974, MNRAS, 168, 603, doi: 10.1093/mnras/168.3.603

    1974 doi

  46. [55]

    F., Ansdell, M., Rosotti, G

    Manara, C. F., Ansdell, M., Rosotti, G. P., 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, 539, doi: 10.48550/arXiv.2203.09930

    2023 doi arXiv

  47. [56]

    F., Morbidelli, A., & Guillot, T

    Manara, C. F., Morbidelli, A., & Guillot, T. 2018, A&A, 618, L3, doi: 10.1051/0004-6361/201834076

    2018 doi

  48. [57]

    2010, ApJ, 714, 680, doi: 10.1088/0004-637X/714/1/680

    Kitamura, Y. 2010, ApJ, 714, 680, doi: 10.1088/0004-637X/714/1/680

    2010 doi

  49. [58]

    J., Pineda, J

    Maureira, M. J., Pineda, J. E., Liu, H. B., et al. 2024, A&A, 689, L5, doi: 10.1051/0004-6361/202451166

    2024 doi

  50. [59]

    K., Furlan, E., Manoj, P., et al

    McClure, M. K., Furlan, E., Manoj, P., et al. 2010, ApJS, 188, 75, doi: 10.1088/0067-0049/188/1/75

    2010 doi

  51. [60]

    K., Bergin, E

    McClure, M. K., Bergin, E. A., Cleeves, L. I., et al. 2016, ApJ, 831, 167, doi: 10.3847/0004-637X/831/2/167 CASA Team, Bean, B., Bhatnagar, S., et al. 2022, PASP, 134, 114501, doi: 10.1088/1538-3873/ac9642

    2016 doi

  52. [61]

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

    Megeath, S. T., Gutermuth, R., Muzerolle, J., et al. 2012, AJ, 144, 192, doi: 10.1088/0004-6256/144/6/192

    2012 doi

  53. [62]

    2018, A&A, 614, A65, doi: 10.1051/0004-6361/201731396

    Meingast, S., Alves, J., & Lombardi, M. 2018, A&A, 614, A65, doi: 10.1051/0004-6361/201731396

    2018 doi

  54. [63]

    F., Kama, M., & Bruderer, S

    Miotello, A., van Dishoeck, E. F., Kama, M., & Bruderer, S. 2016, A&A, 594, A85, doi: 10.1051/0004-6361/201628159

    2016 doi

  55. [64]

    F., Williams, J

    Miotello, A., van Dishoeck, E. F., Williams, J. P., et al. 2017, A&A, 599, A113, doi: 10.1051/0004-6361/201629556

    2017 doi

  56. [65]

    2012, A&A, 541, A97, doi: 10.1051/0004-6361/201117350

    Henning, T. 2012, A&A, 541, A97, doi: 10.1051/0004-6361/201117350

    2012 doi

  57. [66]

    2001, A&A, 372, L41, doi: 10.1051/0004-6361:20010543

    Motte, F., Andr´ e, P., Ward-Thompson, D., & Bontemps, S. 2001, A&A, 372, L41, doi: 10.1051/0004-6361:20010543

    2001 doi

  58. [67]

    A., Lada, C

    Muench, A. A., Lada, C. J., Luhman, K. L., Muzerolle, J., & Young, E. 2007, AJ, 134, 411, doi: 10.1086/518560

    2007 doi

  59. [68]

    D., Pascucci, I., Ciesla, F

    Mulders, G. D., Pascucci, I., Ciesla, F. J., & Fernandes, R. B. 2021, ApJ, 920, 66, doi: 10.3847/1538-4357/ac178e

    2021 doi

  60. [69]

    R., & Kenyon, S

    Najita, J. R., & Kenyon, S. J. 2014, MNRAS, 445, 3315, doi: 10.1093/mnras/stu1994

    2014 doi

  61. [70]

    2000, A&AS, 143, 23, doi: 10.1051/aas:2000169

    Ochsenbein, F., Bauer, P., & Marcout, J. 2000, A&AS, 143, 23, doi: 10.1051/aas:2000169

    2000 doi

  62. [71]

    J., Jørgensen, J

    Ohashi, N., Tobin, J. J., Jørgensen, J. K., et al. 2023, ApJ, 951, 8, doi: 10.3847/1538-4357/acd384

    2023 doi

  63. [72]

    1994, A&A, 291, 943

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

    1994

  64. [73]

    2022, PASP, 134, 094301, doi: 10.1088/1538-3873/ac8839

    Oya, Y., Kibukawa, H., Miyake, S., & Yamamoto, S. 2022, PASP, 134, 094301, doi: 10.1088/1538-3873/ac8839

    2022 doi

  65. [74]

    M., et al

    Pattle, K., Ward-Thompson, D., Kirk, J. M., et al. 2015, MNRAS, 450, 1094, doi: 10.1093/mnras/stv376

    2015 doi

  66. [75]

    B., Hubickyj, O., Bodenheimer, P., et al

    Pollack, J. B., Hubickyj, O., Bodenheimer, P., et al. 1996, Icarus, 124, 62, doi: 10.1006/icar.1996.0190 Portegies Zwart, S. F. 2016, MNRAS, 457, 313, doi: 10.1093/mnras/stv2831

    1996

  67. [76]

    A., Gonz´ alez-Ruilova, C., Cieza, L

    Ruiz-Rodriguez, D. A., Gonz´ alez-Ruilova, C., Cieza, L. A., et al. 2025, ApJ, 989, 2, doi: 10.3847/1538-4357/add2ec

    2025 doi

  68. [77]

    I., Stephens, I

    Sadavoy, S. I., Stephens, I. W., Myers, P. C., et al. 2019, ApJS, 245, 2, doi: 10.3847/1538-4365/ab4257

    2019 doi

  69. [78]

    2025, A&A, 693, A302, doi: 10.1051/0004-6361/202449847

    Savvidou, S., & Bitsch, B. 2025, A&A, 693, A302, doi: 10.1051/0004-6361/202449847

    2025 doi

  70. [79]

    2001, MNRAS, 325, 449, doi: 10.1046/j.1365-8711.2001.04274.x

    Scally, A., & Clarke, C. 2001, MNRAS, 325, 449, doi: 10.1046/j.1365-8711.2001.04274.x

    2001

  71. [80]

    2018, psheehan/pdspy: pdspy: A MCMC Tool for Continuum and Spectral Line Radiative Transfer Modeling, 1.0.0, Zenodo, doi: 10.5281/zenodo.2455079

    Sheehan, P. 2018, psheehan/pdspy: pdspy: A MCMC Tool for Continuum and Spectral Line Radiative Transfer Modeling, 1.0.0, Zenodo, doi: 10.5281/zenodo.2455079

    2018 doi

  72. [81]

    D., & Eisner, J

    Sheehan, P. D., & Eisner, J. A. 2017, ApJ, 851, 45, doi: 10.3847/1538-4357/aa9990

    2017 doi

  73. [82]

    D., Tobin, J

    Sheehan, P. D., Tobin, J. J., Looney, L. W., & Megeath, S. T. 2022, ApJ, 929, 76, doi: 10.3847/1538-4357/ac574d

    2022 doi

  74. [83]

    B., Armitage, P

    Simon, J. B., Armitage, P. J., Li, R., & Youdin, A. N. 2016, ApJ, 822, 55, doi: 10.3847/0004-637X/822/1/55

    2016 doi

  75. [84]

    Takeuchi, T., & Lin, D. N. C. 2005, ApJ, 623, 482, doi: 10.1086/428378

    2005 doi

  76. [85]

    2020, richteague/keplerian mask: Initial Release, 1.0, Zenodo, doi: 10.5281/zenodo.4321137

    Teague, R. 2020, richteague/keplerian mask: Initial Release, 1.0, Zenodo, doi: 10.5281/zenodo.4321137

    2020 doi

  77. [86]

    H., & Cassen, P

    Terebey, S., Shu, F. H., & Cassen, P. 1984, ApJ, 286, 529, doi: 10.1086/162628

    1984 doi

  78. [87]

    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

    2014 doi

  79. [88]

    J., Chandler, C

    Tobin, J. J., Chandler, C. J., Wilner, D. J., et al. 2013, ApJ, 779, 93, doi: 10.1088/0004-637X/779/2/93

    2013 doi

  80. [89]

    J., Looney, L

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

    2016 doi

  81. [90]

    J., Sheehan, P

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

    2020 doi

  82. [91]

    F., & Bruderer, S

    Dishoeck, E. F., & Bruderer, S. 2019, A&A, 629, A79, doi: 10.1051/0004-6361/201834723

    2019 doi

  83. [92]

    F., & Bruderer, S

    Trapman, L., Miotello, A., Kama, M., van Dishoeck, E. F., & Bruderer, S. 2017, A&A, 605, A69, doi: 10.1051/0004-6361/201630308 31

    2017 doi

  84. [93]

    P., et al

    Trapman, L., Zhang, K., Rosotti, G. P., et al. 2025, ApJ, 989, 5, doi: 10.3847/1538-4357/adcd6e

    2025 doi

  85. [94]

    J., Karska, A., et al

    Tychoniec, L., Tobin, J. J., Karska, A., et al. 2018, ApJS, 238, 19, doi: 10.3847/1538-4365/aaceae

    2018 doi

  86. [95]

    F., Rosotti, G

    Tychoniec, L., Manara, C. F., Rosotti, G. P., et al. 2020, A&A, 640, A19, doi: 10.1051/0004-6361/202037851

    2020 doi

  87. [96]

    Ulrich, R. K. 1976, ApJ, 210, 377, doi: 10.1086/154840 van ’t Hoff, M. L. R., Tobin, J. J., Harsono, D., & van

    1976 doi

  88. [97]

    Dishoeck, E. F. 2018, A&A, 615, A83, doi: 10.1051/0004-6361/201732313 van Terwisga, S. E., & Hacar, A. 2023, A&A, 673, L2, doi: 10.1051/0004-6361/202346135 van Terwisga, S. E., Hacar, A., van Dishoeck, E. F., Oonk, R., & Portegies Zwart, S. 2022, A&A, 661, A53, doi: 10.1051/00...

    2018 doi

  89. [98]

    Blake, G. A. 2001, A&A, 377, 566, doi: 10.1051/0004-6361:20011137

    2001 doi

  90. [99]

    Vrba, F. J. 1977, AJ, 82, 198, doi: 10.1086/112031

    1977 doi

  91. [100]

    P., & Best, W

    Williams, J. P., & Best, W. M. J. 2014, ApJ, 788, 59, doi: 10.1088/0004-637X/788/1/59

    2014 doi

  92. [101]

    P., Cieza, L., Hales, A., et al

    Williams, J. P., Cieza, L., Hales, A., et al. 2019, ApJL, 875, L9, doi: 10.3847/2041-8213/ab1338

    2019 doi

  93. [102]

    P., & Cieza, L

    Williams, J. P., & Cieza, L. A. 2011, ARA&A, 49, 67, doi: 10.1146/annurev-astro-081710-102548

    2011 doi

  94. [103]

    L., & Rood, R

    Wilson, T. L., & Rood, R. 1994, ARA&A, 32, 191, doi: 10.1146/annurev.aa.32.090194.001203

    1994

  95. [104]

    J., & Haworth, T

    Winter, A. J., & Haworth, T. J. 2022, European Physical Journal Plus, 137, 1132, doi: 10.1140/epjp/s13360-022-03314-1

    2022 doi

  96. [105]

    2016, A&A, 586, A103, doi: 10.1051/0004-6361/201526538

    Woitke, P., Min, M., Pinte, C., et al. 2016, A&A, 586, A103, doi: 10.1051/0004-6361/201526538

    2016 doi

  97. [106]

    N., & Goodman, J

    Youdin, A. N., & Goodman, J. 2005, ApJ, 620, 459, doi: 10.1086/426895

    2005 doi

  98. [107]

    J., Dodson-Robinson, S

    Yu, M., Evans, II, N. J., Dodson-Robinson, S. E., Willacy, K., & Turner, N. J. 2017, ApJ, 841, 39, doi: 10.3847/1538-4357/aa6e4c

    2017 doi

  99. [108]

    J., Zhao, B., et al

    Zamponi, J., Maureira, M. J., Zhao, B., et al. 2021, MNRAS, 508, 2583, doi: 10.1093/mnras/stab2657

    2021 doi

  100. [109]

    A., Schwarz, K., Krijt, S., & Ciesla, F

    Zhang, K., Bergin, E. A., Schwarz, K., Krijt, S., & Ciesla, F. 2019, ApJ, 883, 98, doi: 10.3847/1538-4357/ab38b9

    2019 doi

  101. [110]

    R., & Bergin, E

    Zhang, K., Schwarz, K. R., & Bergin, E. A. 2020, ApJL, 891, L17, doi: 10.3847/2041-8213/ab7823

    2020 doi

  102. [111]

    M., Pascucci, I., et al

    Zhang, K., P´ erez, L. M., Pascucci, I., et al. 2025, ApJ, 989, 1, doi: 10.3847/1538-4357/addebe

    2025 doi

  103. [112]

    F., Speagle, J

    Zucker, C., Schlafly, E. F., Speagle, J. S., et al. 2018, ApJ, 869, 83, doi: 10.3847/1538-4357/aae97c

    2018 doi

  104. [113]

    S., Schlafly, E

    Zucker, C., Speagle, J. S., Schlafly, E. F., et al. 2020, A&A, 633, A51, doi: 10.1051/0004-6361/201936145

    2020 doi

  105. [114]

    A., Langer, W

    Frerking, M. A., Langer, W. D., & Wilson, R. W. 1982, ApJ, 262, 590, doi: 10.1086/160451

    1982 doi

  106. [115]

    Hogerheijde, M. R. 2008, ApJ, 681, 1396, doi: 10.1086/588516

    2008 doi

  107. [116]

    I., Wilner, D

    Qi, C., D’Alessio, P., ¨Oberg, K. I., Wilner, D. J., Hughes, A. M., Andrews, S. M., & Ayala, S. 2011, ApJ, 740, 84, doi: 10.1088/0004-637X/740/2/84

    2011 doi

  108. [117]

    A., Andrews, S

    Rosenfeld, K. A., Andrews, S. M., Hughes, A. M., Wilner, D. J., & Qi, C. 2013, ApJ, 774, 16, doi: 10.1088/0004-637X/774/1/16

    2013 doi

  109. [118]

    1972, Journal of the Royal Statistical Society: Series A, 135, 185–207, doi: 10.2307/2344317

    Peto, R., & Peto, J. 1972, Journal of the Royal Statistical Society: Series A, 135, 185–207, doi: 10.2307/2344317

    1972 doi

  110. [119]

    C., et al

    Plante, A. C., et al. 2026, ApJ, in press

    2026

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.