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REVIEW 4 major objections 5 minor 1 cited by

The ALMA Survey of Gas Evolution of PROtoplanetary Disks (AGE-PRO): VII. Testing accretion mechanisms from disk population synthesis

T0 review · 4 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

Pith's one-line read The ALMA gas census favors MHD disk winds over turbulence as the driver of disk evolution.

desk verdict Sharp new M_D/Mdot diagnostic, but the wind-vs-turbulence conclusion rests on a gas-mass scale whose uncertainty is about the size of the discrepancy. read the letter →

arxiv 2506.10742 v1 pith:SFMMHMDZ submitted 2025-06-12 astro-ph.EP astro-ph.SR

classification astro-ph.EPastro-ph.SR
keywords diskpopulationsynthesisprotoplanetarydisksaccretionmechanismsMHDwindsturbulence-drivengasmassesdispersalAGE-PROsurvey
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper argues that the ALMA AGE-PRO survey's gas masses and CO sizes, combined with accretion rates and disk fractions, can discriminate between the two main mechanisms thought to drain planet-forming disks. Population synthesis models of turbulence-driven accretion with a constant $\alpha$ and internal photoevaporation can match the disk fraction and disk sizes, but then overproduce the median disk gas mass by a factor of 5-10 and predict apparent disk lifetimes $M_D/\dot{M}_*$ far longer than observed. MHD wind-driven accretion, with initially compact disks ($R_0\simeq10$ au), an initial magnetization $\beta\simeq10^5$, and a magnetic field that declines with time, reproduces the evolution from Ophiuchus to Upper Sco. A sympathetic reading is that the data favor wind-driven accretion, conditional on the low gas masses of compact disks being real.

What carries the argument

The central object is a population synthesis pipeline that evolves thousands of 1D disk models with randomly drawn initial parameters and compares the surviving, still-disk-bearing members at each age with survey data. Two scenarios share a common parameterization: turbulence-driven evolution with $\alpha_{\rm SS}$, viscous timescale $t_{\nu,0}$, and the photoevaporative mass-loss profile adopted from published hydrodynamical calculations; and MHD wind-driven evolution built on an analytical MHD wind solution with wind-torque parameter $\alpha_{\rm DW}$, magnetic lever arm $\lambda$, and exponent $\omega$ controlling the secular decay of the magnetic field. A four-stage fit sequentially constrains the median initial mass, initial size, accretion/viscous timescale, and wind mass-loss rate using the disk fraction, the Lupus median accretion rate, the CO size, and the gas mass. The decisive diagnostic is the apparent disk lifetime $M_D/\dot{M}_*$, which turbulence-driven models with constant $\alpha$ cannot make as short as AGE-PRO reports; the wind model produces short lifetimes through rapid draining just before dispersal.

What would settle it

A campaign of deep ALMA observations targeting the most compact disks (CO radii below about 60 au) to measure their CO isotopologue fluxes, N2H+ emission, and, where possible, pressure-broadened line profiles could settle whether the low gas masses are real. If the true masses of compact disks are a factor of 5-10 higher than AGE-PRO reports, the observed $M_D/\dot{M}_*$ distribution would move above 1 Myr and the central tension with turbulence-driven models would vanish; conversely, confirming the low masses would leave turbulence-driven models without a constant-$\alpha$ explanation.

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Extended reading notes

Core claim

The paper's central claim is that no turbulence-driven model with a constant Shakura-Sunyaev $\alpha_{\rm SS}$ and a fixed photoevaporative mass-loss profile can simultaneously reproduce the observed disk fraction, median accretion rate, median CO gas size, and median gas mass of the Lupus population. The joint fit pins the viscous timescale to $t_{\nu,0}\simeq0.4-3$ Myr ($\alpha_{\rm SS}\simeq2-4\times10^{-4}$) and compact initial radii $R_0\simeq5-20$ au, but the predicted median disk mass at 2 Myr is $5\times10^{-3}\,M_\odot$, a factor 5-10 above the AGE-PRO estimate, and the predicted $M_D/\dot{M}_*$ distribution is too long by the same token. In contrast, the MHD wind-driven scenario with $\alpha_{\rm DW}\simeq5\times10^{-4}-10^{-3}$, $R_0\simeq10$ au, $\omega\simeq0.5$, and ejection-to-accretion ratio $f_M\lesssim1$ reproduces the declining gas mass from Ophiuchus to Lupus, the roughly constant mass from Lupus to Upper Sco, and the short apparent disk lifetimes seen in the data. The paper concludes that the observed populations tend to favor MHD wind-driven accretion, with the caveat that the mass estimates for compact disks need independent confirmation.

Load-bearing premise

The argument stands on the AGE-PRO gas mass estimates being accurate, especially for compact disks; if those masses were systematically underestimated by a factor of five to ten, turbulence-driven models would become compatible with the data and the preference for wind-driven accretion would largely disappear.

Editorial extensions

If this is right

  • If MHD wind-driven accretion is the main mechanism, disks lose mass without spreading, so gas surfaces stay compact; the observed modest growth of CO size with age is a survivorship bias, not viscous expansion.
  • The failure of constant-$\alpha$ turbulence models points to a need for disk evolution models with radially or temporally varying viscosity or other physics before invoking turbulence as the driver.
  • The best-fit wind parameters ($\beta\simeq10^5$, $\omega\simeq0.5$) give concrete targets for numerical simulations of magnetized disks on secular timescales.
  • The synthetic populations, matching gas masses and sizes, can be fed into planet formation models to make statistical predictions for exoplanet systems.
  • The short apparent disk lifetimes of middle-aged disks imply a population of low-mass, compact, still-accreting disks about to disperse, which should be visible in surveys.

Reading between the lines

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

  • If deeper observations confirm the low masses of compact disks, turbulence-driven accretion would need either a strongly time-varying $\alpha$ or an inner mass reservoir invisible to CO lines to survive.
  • A population with such short $M_D/\dot{M}_*$ implies a rapid final dispersal phase; planet formation and migration must finish early, possibly within the first 1-2 Myr, in wind-driven disks.
  • The approach could be extended to other star-forming regions and to older clusters to test whether the decline in median accretion rate with cluster age is universal, as the Upper Sco comparison assumes.
  • Correlating initial disk size and mass in the synthetic populations is a testable next step: a positive correlation would steepen predicted trends and can be constrained by Class I disk surveys.
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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 / 5 minor

Summary. This manuscript develops a disk population synthesis framework to interpret the AGE-PRO survey's measurements of disk gas masses and CO gas sizes, together with stellar accretion rates and disk fractions, in order to discriminate between turbulence-driven accretion (with internal photoevaporation) and MHD wind-driven accretion. The authors fit the population parameters in a stepwise manner, first to the observed disk fraction, then to the median Lupus accretion rate, CO size, and gas mass, and finally compare the best-fit tracks to Ophiuchus and Upper Sco. They find that turbulence-driven models with constant alpha can reproduce the disk fraction, accretion rate, and CO size but overproduce the median disk mass by a factor of 5-10 and severely overproduce the apparent disk lifetime M_D/Mdot. The MHD wind-driven model, with initially compact disks (R0 about 10 au), alpha_DW about 5e-4 to 1e-3, and a decaying magnetic field parameterized by omega about 0.5, simultaneously reproduces the median mass, size, accretion rate, and disk fraction from Ophiuchus to Upper Sco. The paper concludes that the AGE-PRO data favor MHD wind-driven accretion, while explicitly cautioning that systematic uncertainties in the disk mass estimates, especially for compact disks, could change this conclusion.

Significance. If the disk mass calibration is correct, this paper provides a novel and potentially decisive population-level test between two leading disk evolution paradigms, and it carefully accounts for survivorship bias, which is often neglected. The stepwise fitting strategy is transparent and computationally efficient, and the use of the public Diskpop code is a strength. The paper also makes a falsifiable prediction: the distribution of M_D/Mdot should be short, with a tail of compact, low-mass, actively accreting disks, and it identifies compact disks as the key targets for future chemical and kinematic mass measurements. However, the central discriminating observable, the disk mass scale, carries a quoted systematic uncertainty of about 0.7 dex, which is comparable to the 5-10x discrepancy that excludes turbulence; the manuscript explicitly acknowledges this in Sec. 4.2.2. The conclusion is therefore conditional on an external calibration that is not yet demonstrated.

major comments (4)
  1. [Sec. 4.2.2 and Fig. 12] The paper's core claim is that turbulence-driven models overproduce M_D/Mdot by a factor of 5-10, but the quoted systematic uncertainty on the AGE-PRO disk masses is sigma=0.7 dex, i.e., about a factor of 5. The manuscript itself states in Sec. 4.2.2 that a systematic underestimate of disk mass by a factor of 5-10 would make turbulence-driven models compatible with the data. Since the short apparent lifetimes are dominated by the lowest-mass compact disks, the conclusion rests on an external mass calibration at approximately the level of the quoted systematic uncertainty. Please add a quantitative propagation of a mass-scale bias, for example by recomputing the step 2-4 fits and Fig. 13 with global M_D scaling factors of 2, 5, and 10, or by adding an inner-disk mass floor, and state explicitly whether the wind preference survives.
  2. [Sec. 3.2 and Fig. 10] The stepwise fitting procedure fixes all lognormal spreads and the independence of parameters a priori (Table 1) and fits only the medians. The predicted median M_D and the M_D/Mdot distribution are sensitive to these choices because survivorship bias preferentially removes light and small disks; for example, a larger spread in M0 or a correlation between M0 and R0 changes the median of the surviving population. The conclusion that turbulence overpredicts M_D by a factor of 5-10 should be tested against plausible alternative spread and correlation values, or the spreads should be fit jointly with the medians; otherwise the discrepancy could be an artifact of the adopted fixed spreads.
  3. [Sec. 3.1.4 and Figs. 5-6] The MHD wind best fit is degenerate in the (omega, f_M, <M0>) plane: the Lupus median disk mass can be reproduced for omega=0.25 with f_M<1 and for omega=0.5 with f_M<0.5, while higher masses would be accommodated by f_M=1-10. The preference for omega=0.5 rests mainly on the Ophiuchus initial mass and the Oph-to-Lupus mass drop, which are the least secure mass estimates (CO-only retrieval in the presence of envelopes). Please quantify the joint allowed parameter region including observational uncertainties, or provide a formal model comparison metric over all three regions, rather than selecting two representative models by eye.
  4. [Sec. 4.2.1 and Fig. 7] The Upper Sco comparison is weaker than the text suggests: the AGE-PRO Upper Sco sample is selected to be among the youngest sources in the region (adopted median age 4 Myr versus 7 Myr for the cluster), the Fang et al. accretion rates include upper limits for about half the sources, and the sample size is small. The evolutionary track from Lupus to Upper Sco is therefore not a strong falsifier of the turbulence-driven model. The grey quartile bands in Fig. 7 should be supplemented with the actual number of sources and a statistical treatment of upper limits, and the strength of the claim that the MHD wind model 'reproduces the bulk properties from Ophiuchus to Upper Sco' should be tempered accordingly.
minor comments (5)
  1. [Sec. 2.1] The text 'which is futher studied in the case of turbulence-driven accretion' contains a typo; 'futher' should be 'further'.
  2. [Sec. 2.2.1] The phrase 'thought using only Halpha line flux as a proxy' should read 'though using only Halpha line flux'.
  3. [Fig. 11 caption] The caption lists 't_nu,0=3.0 Myr (left)' for the third model; this should be '(right)' to match the panel layout.
  4. [References] The in-press references to Anania (2025) and Zhang (2025) contain placeholder arXiv identifiers; these should be updated before final publication.
  5. [Eq. (16)] The approximate power-law for the dispersal time is useful, but the text should state explicitly over what range of parameters it was calibrated and what typical fractional error it carries, so that readers do not use it outside its regime of validity.

Circularity Check

2 steps flagged · score 4.0 of 10

MHD wind 'reproduction' is partly in-sample because f_M is fit to Lupus and omega is selected using Ophiuchus mass; the turbulence-model tension and Upper Sco tracks provide independent content.

  1. fitted input called prediction [Sec. 3.1.4 (best-fit MHD disk-wind model), Figs. 6-7]
    "Putting all the constraints stemming from the properties of the Lupus population and disk fraction, we find best-fit models with an omega=0.25-0.5, low mass ejection-to-accretion f_M<~1, initially compact disks <R_0>=10 au, and alpha_DW~5e-4-1e-3. Reproducing the essential features of the Lupus population constitutes the first success of the MHD disk-wind models. ... By construction, the two synthetic populations reproduce the Lupus population at 2 Myr."

    In the MHD wind solution (Eq. 8), M_D/Mdot is set by t_acc,0, f_M, and omega alone (it is independent of M_0). The staged fit sets t_acc,0 via the disk fraction (Eq. 15), R_0 via the Lupus CO size, M_0 via the Lupus accretion rate, and f_M via the Lupus disk mass. Therefore the short apparent disk lifetimes M_D/Mdot in Lupus are a consequence of parameters fitted to Lupus data, not an out-of-sample prediction. The paper itself acknowledges this: 'By construction, the two synthetic populations reproduce the Lupus population at 2 Myr.' The independent content is the Upper Sco evolution and the turbulence-model discrepancy.

  2. fitted input called prediction [Sec. 3.1.2 and Sec. 3.1.4, Figs. 5 and 7]
    "The median gas mass of <M_D>~7+4-2e-3 M_sun obtained by AGE-PRO in Ophiuchus ... favors low ejection-to-accretion ratios f_M<~1 and relatively high values of omega. ... AGE-PRO finds a decrease in median disk mass of about 10 from Ophiuchus to Lupus which is well reproduced by omega=0.5."

    The Ophiuchus median gas mass is used to select the omega value (and f_M), breaking the degeneracy in Fig. 5, and the omega=0.5 model is then presented as 'well reproducing' the Ophiuchus-to-Lupus mass decline. Because the Ophiuchus point was an input to the parameter selection, this anchor is partly in-sample rather than a clean out-of-sample test. The Upper Scorpius comparison and the failure of the turbulence-driven model remain external checks that do not reduce to the fitted values.

full rationale

Most of the paper is a genuine, self-contained population-synthesis comparison. The turbulence-driven model is fitted to the disk fraction, Lupus accretion rate, and Lupus CO size, and then independently predicts an overestimate of the Lupus/Upper Sco disk masses and apparent disk lifetimes by a factor of 5-10; that failure is an independent result, not a circular one. The MHD wind model, however, is fit to Lupus (t_acc,0 via disk fraction, M_0 via accretion rate, R_0 via CO size, f_M via disk mass) and additionally uses the Ophiuchus median mass to select omega=0.5. The paper states 'By construction, the two synthetic populations reproduce the Lupus population at 2 Myr,' and the short M_D/Mdot values in Lupus follow directly from the fitted parameters via Eq. (8). Thus the MHD model's reproduction of the Lupus apparent-lifetime distribution and the Ophiuchus-to-Lupus mass decline is partly in-sample. The Upper Sco evolutionary tracks and the turbulence-model discrepancy are not fitted and provide independent content, so this is partial circularity rather than full circularity. No uniqueness theorem, ansatz smuggling through self-citation, or renaming of a known result was found; the Tabone et al. (2022a) self-citation supplies the model equations but is not used as a substitute for the data comparison. The disk-mass calibration caveat (0.7 dex uncertainty versus the needed factor 5-10) is a data-quality risk, not a circularity.

Assumptions & free parameters 11 free parameters · 12 assumptions · 0 invented entities

The population synthesis requires fitting several medians to the same Lupus data and disk fraction; the model comparison then tests whether the fitted models can also explain Ophiuchus and Upper Sco. No new physical entities are introduced; the main external load-bearing inputs are the AGE-PRO mass and size estimates and the published evolution models.

free parameters (11)
  • Median initial disk mass <M0> (MHD wind) = 7.5e-3 Msun
    Adjusted so the synthetic median accretion rate at 2 Myr matches the Lupus value of 1e-9 Msun/yr (Sec 3.1.2).
  • Median initial disk mass <M0> (turbulent) = 1.2e-2 Msun
    Adjusted to match the Lupus median accretion rate at 2 Myr (Sec 3.2.2).
  • Median initial disk radius <R0> = 10 au (both scenarios)
    Fitted to the Lupus median CO gas size (Sec 3.1.3 and 3.2.3).
  • MHD accretion timescale / alpha_DW = t_acc,0 = 0.75 Myr, alpha_DW = 5e-4 to 1e-3
    Set by fitting the median disk lifetime of 3 Myr (Eq 15).
  • Turbulent viscous timescale <t_nu,0> = 1.0 Myr, alpha_SS = 3.4e-4, range 0.4-3 Myr
    Grid parameter constrained by disk fraction, Lupus accretion rate, and CO size (Sec 3.2.3).
  • Photoevaporative mass-loss rate <Mdot_PEW> (turbulent) = 4.4e-9 Msun/yr
    Fitted to disk fraction for each combination of M0, R0, and t_nu,0 (Sec 3.2.1).
  • Ejection-to-accretion ratio <f_M> (MHD wind) = <0.5, lambda > 8
    Constrained by the Lupus median disk mass (Sec 3.1.3).
  • omega (magnetic field decay index) = 0.25 and 0.5 explored
    Two values are explored, not fit; omega=0.5 matches the Oph-to-Lupus mass drop better (Sec 3.1.4).
  • CO depletion factor delta_C = 0.2
    Hand-chosen scale for the CO size column threshold (Eq 12), adopted from the AGE-PRO thermochemical analysis.
  • Spreads of lognormal parameter distributions = sigma_R0=0.3, sigma_M0=0.6, sigma_alpha=0.2, sigma_Mdot=0.3 dex
    Fixed to reproduce the decline of disk fraction and spread in accretion rates; not varied in the fit (Table 1).
  • Median disk lifetime and spread from disk fraction = 3 Myr, spread 0.3 dex
    Obtained by fitting an error function to the disk fraction data (Fedele et al. 2010) and used as the target for model disk dispersal (Sec 2.2.1).
assumptions (12)
  • standard math Shakura-Sunyaev alpha prescription for viscous angular momentum transport
    Used in Eq (1); standard in disk evolution models.
  • domain assumption MHD disk-wind analytical solution of Tabone et al. (2022a) with alpha_SS=0 and constant lambda
    Adopted as the wind-driven evolution model; assumes no radial angular momentum transport (Sec 2.1.2).
  • domain assumption Ophiuchus, Lupus, and Upper Sco samples are draws from a single evolving population at ages 0, 2, and 4 Myr
    Required for the population synthesis comparison (Sec 2.2.1 and Sec 4.2.1).
  • domain assumption Disks are isolated after the Class I phase, with no envelope accretion or streamer infall
    Assumed at the start of Sec 2.1; sets t=0.
  • domain assumption External photoevaporation and close-binary effects are negligible; disk fraction is corrected by factor 1.2 for binaries
    Stated in Sec 2.2.1; external FUV in Upper Sco is briefly discussed in Sec 4.2.1.
  • ad hoc to paper Individual disk parameters follow independent lognormal distributions with fixed spreads
    Needed to build synthetic populations; spreads are fixed by hand (Table 1).
  • domain assumption Disk dispersal occurs when the accretion rate drops below 1e-12 Msun/yr
    Definition used in Sec 2.1.1 and 2.1.2.
  • domain assumption CO gas size is given by the radius where the hydrogen column density equals N_gas = 3.7e21 delta_C^-1 (M_D/Msun)^0.34 with delta_C=0.2
    Analytical conversion from Trapman et al. (2023) and Toci et al. (2023), used in Eq (12).
  • domain assumption Photoevaporation profile follows Picogna et al. (2021) for a 0.5 Msun star, scaled by a free total rate constant in time
    Adopted in Sec 2.1.1; ignores attenuation by an inner wind and time-varying stellar flux.
  • ad hoc to paper The alpha parameter is constant in time and radius for the turbulent model
    Simplification stated in Sec 2.1.1; step-function alpha profiles are not explored in detail.
  • domain assumption Temperature profile T ~ R^-1/2 with aspect ratio 0.0333 at 1 au and stellar mass 0.5 Msun for the evolution equations
    Used to convert alpha to timescales (Eqs 4 and 10).
  • domain assumption Median ages of 2 Myr for Lupus and 4 Myr for the Upper Sco AGE-PRO subsample
    Stated in Sec 2.2.1; Upper Sco sample is younger than the cluster median of 7 Myr.

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Cite this review

Pith. "Pith review of The ALMA Survey of Gas Evolution of PROtoplanetary Disks (AGE-PRO): VII. Testing accretion mechanisms from disk population synthesis." pith.science (2026). https://pith.science/paper/SFMMHMDZ

@misc{pith2026250610742,
  author       = {Pith},
  title        = {Pith review of: The ALMA Survey of Gas Evolution of PROtoplanetary Disks (AGE-PRO): VII. Testing accretion mechanisms from disk population synthesis},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/SFMMHMDZ}},
  note         = {Machine review of arXiv:2506.10742}
}
abstract

The architecture of planetary systems depends on the evolution of the disks in which they form. In this work, we develop a population synthesis approach to interpret the AGE-PRO measurements of disk gas mass and size considering two scenarios: turbulence-driven evolution with photoevaporative winds and MHD disk-wind-driven evolution. A systematic method is proposed to constrain the distribution of disk parameters from the disk fractions, accretion rates, disk gas masses, and CO gas sizes. We find that turbulence-driven accretion with initially compact disks ($R_0 \simeq 5-20~$au), low mass-loss rates, and relatively long viscous timescales ($t_{\nu,0} \simeq 0.4-3~$Myr or $\alpha_{SS} \simeq 2-4 \times 10^{-4}$) can reproduce the disk fraction and gas sizes. However, the distribution of apparent disk lifetime defined as the $M_D/\dot{M}_*$ ratio is severely overestimated by turbulence-driven models. On the other hand, MHD wind-driven accretion can reproduce the bulk properties of the disk populations from Ophiuchus to Upper Sco assuming compact disks with an initial magnetization of about $\beta \simeq 10^5$ ($\alpha_{DW} \simeq 0.5-1 \times 10^{-3}$) and a magnetic field that declines with time. More studies are needed to confirm the low masses found by AGE-PRO, notably for compact disks that question turbulence-driven accretion. The constrained synthetic disk populations can now be used for realistic planet population models to interpret the properties of planetary systems on a statistical basis.

Figures

Figures reproduced from arXiv: 2506.10742 by the authors.

Figure 1
Figure 1. Example of turbulence-driven evolution for a set of parameters illustrating two different pathways of dispersal. Left: surface density profiles from initial time (blue) to dispersal (red). Right: evolution of the disk mass and accretion rate. The first solution is an example of the popular inside-out dispersal pathway with gap opening occurring for large disks and leading to relic disks. The second solution exhibits… view at source ↗
Figure 2
Figure 2. Example of MHD wind-driven evolution for a set of parameters illustrating the impact of time evolution of the disk magnetization as parameterized by ω. The left panels show the surface density profile from initial time (blue) to dispersal (red). The right panels show the evolution of the disk mass and accretion rate. The two solutions share the same value of λ and initial mass and size but differ by the value of ω. … view at source ↗
Figure 3
Figure 3. Summary of the observational data to be reproduced by our population synthesis model. Top left: disk fraction probed by the mid- and near-infrared excess of several star-forming regions. The disk fractions compiled by Fedele et al. (2010) are rescaled by a factor of 1.2 to account for the short-lived disks around binaries. Top right: stellar accretion rates from the nearly complete surveys of the Lupus and Upper Sco… view at source ↗
Figures from the paper (12 more)
Figure 4
Figure 4. Figure 4: Schematic view of the fitting stages for the turbulent (left) and the MHD disk-wind (right) models. This step-by-step approach allows us to build synthetic populations consistent with the obser￾vations in a rationalized approach. median CO gas size in Lupus) constrains…
Figure 5
Figure 5. Figure 5: Constraints on the initial median disk mass < M0 > ob￾tained by reproducing the median accretion rate of Lupus (M˙ ∗ ≃ 10−9M⊙/yr). The grey area indicates the median disk mass derived by AGE-PRO in Ophiuchus. Each dot corresponds to a synthetic population with a medial…
Figure 6
Figure 6. Figure 6: Predicted median CO gas size and disk mass at the age of Lupus for synthetic populations matching disk fraction (see Eq. (15)) and the Lupus median accretion rate (see [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]
Figure 7
Figure 7. Figure 7: Best fit MHD-DW model for ω = 0.25 (left) and ω = 0.5 (right) compared with the observations. The top panels show the total disk gas mass, the middle panels the accretion rates, and the bottom panels the CO disk size. Individual sources are represented by dots and the …
Figure 8
Figure 8. Figure 8: Illustration of the method used to constrain the median mass-loss rate < M˙ PEW > from the disk fraction, assuming a fixed value of R0, < M0 > , and < tν,0 > . The predicted disk fraction as defined by non-accreting disks is shown in solid line for various values of th…
Figure 9
Figure 9. Figure 9: Constraints on < M˙ PEW > obtained by fitting a median disk dispersal time of tdisp = 3 Myr and the resulting median ac￾cretion rate at initial time and after 2 Myr for a median initial disk size of < R0 > = 10 au. The method used to find the value of < M˙ PEW > that f…
Figure 10
Figure 10. Figure 10: Summary of the constraints on turbulence-driven disk evolution obtained from disk dispersal time and median accretion rate measured in Lupus (namely, after 2). The fitted values of < M0 > (panel a) and < M˙ PEW > (panel b) parameters are plotted as a function of < tν,…
Figure 11
Figure 11. Figure 11: Best fit viscous model for tν,0 = 0.4 Myr (left), tν,0 = 1.0 Myr (middle) and tν,0 = 3.0 Myr (left) compared with the observations. The figure follows the same convention as [PITH_FULL_IMAGE:figures/full_fig_p015_11.png]
Figure 12
Figure 12. Figure 12: Comparison in the disk mass-accretion rate plane between the Lupus sources and our best-fit population models for the turbulence￾driven and MHD wind-driven case. The AGE-PRO sources with accretion rates from Manara et al. (2020) are shown in red. The simulated disks a…
Figure 13
Figure 13. Figure 13: Cumulative distribution of the accretion rate, the disk mass, and the disk lifetime for the best fit MHD disk-wind (red) and turbulence-driven model (blue) versus the AGE-PRO sample focusing on 1-3 Myr disks (black). The MHD wind model repro￾duces well the distributio…
Figure 14
Figure 14. Figure 14: The survivorship bias illustrated by the initial median value of the disk mass (left) and size (right) calculated over the sur￾viving disks. The blue and red lines correspond to the best-fit MHD wind-driven and turbulence-driven populations (see [PITH_FULL_IMAGE:figu…
Figure 15
Figure 15. Figure 15: Summary of the constraints on turbulence-driven disk evolution obtained from disk dispersal time. The fitted values of < M˙ PEW > are plotted as a function of < tν,0 > for various values of R0 (top row). The median accretion rate at t = 0 and t = 2 Myr are shown in th…

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Works this paper leans on

131 extracted references · 12 canonical work pages · cited by 1 Pith paper

  1. [1]

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  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]

    q #H# @ )T @ @ x^ S> pߞ! g,SLg @ @ Hq 4 9r>⎛&ϟ , A /h=B q ;v 3|p8(_ @ @ ^kt𕸾^ @ @ [ lY؈@ x Q= @ 8<

    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...

  4. [4]

    M., Sierra , A., et al

    Agurto-Gangas , C., P \'e rez , L. M., Sierra , A., et al. 2025, in press,

  5. [5]

    M., Natta , A., Manara , C

    Alcal \'a , J. M., Natta , A., Manara , C. F., et al. 2014, , 561, A2, 10.1051/0004-6361/201322254

  6. [7]

    2017 b , , 600, A20, 10.1051/0004-6361/201629929

    ---. 2017 b , , 600, A20, 10.1051/0004-6361/201629929

  7. [8]

    2008, , 52, 60, 10.1016/j.newar.2008.04.004

    Alexander , R. 2008, , 52, 60, 10.1016/j.newar.2008.04.004

  8. [9]

    2014, in Protostars and Planets VI, ed

    Alexander , R., Pascucci , I., Andrews , S., Armitage , P., & Cieza , L. 2014, in Protostars and Planets VI, ed. H. Beuther , R. S. Klessen , C. P. Dullemond , & T. Henning , 475, 10.2458/azu\_uapress\_9780816531240-ch021

Show all 131 references
  1. [10]

    J., et al

    Alexander , R., Rosotti , G., Armitage , P. J., et al. 2023, , 524, 3948, 10.1093/mnras/stad1983

  2. [11]

    D., & Armitage , P

    Alexander , R. D., & Armitage , P. J. 2009, , 704, 989, 10.1088/0004-637X/704/2/989

  3. [12]

    D., Clarke , C

    Alexander , R. D., Clarke , C. J., & Pringle , J. E. 2006, , 369, 229, 10.1111/j.1365-2966.2006.10294.x

  4. [13]

    Anania , R. 2025, . xxxx.xxxx

  5. [14]

    E., Blake , G

    Anderson , D. E., Blake , G. A., Bergin , E. A., et al. 2019, , 881, 127, 10.3847/1538-4357/ab2cb5

  6. [15]

    M., Rosenfeld , K

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

  7. [16]

    M., & Williams , J

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

  8. [17]

    P., Manara , C

    Ansdell , M., Williams , J. P., Manara , C. F., et al. 2017, , 153, 240, 10.3847/1538-3881/aa69c0

  9. [18]

    J., Simon , J

    Armitage , P. J., Simon , J. B., & Martin , R. G. 2013, , 778, L14, 10.1088/2041-8205/778/1/L14

  10. [19]

    M., Sip o cz , B

    Astropy Collaboration , Price-Whelan , A. M., Sip o cz , B. M., et al. 2018, , 156, 123, 10.3847/1538-3881/aabc4f

  11. [20]

    2016, , 821, 80, 10.3847/0004-637X/821/2/80

    Bai , X.-N. 2016, , 821, 80, 10.3847/0004-637X/821/2/80

  12. [21]

    Bai , X.-N., & Stone , J. M. 2011, , 736, 144, 10.1088/0004-637X/736/2/144

  13. [22]

    2013, , 769, 76, 10.1088/0004-637X/769/1/76

    ---. 2013, , 769, 76, 10.1088/0004-637X/769/1/76

  14. [23]

    A., Carpenter , J

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

  15. [24]

    2017, , 600, A75, 10.1051/0004-6361/201630056

    B \'e thune , W., Lesur , G., & Ferreira , J. 2017, , 600, A75, 10.1051/0004-6361/201630056

  16. [25]

    D., & Payne , D

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

  17. [26]

    S., Tabone , B., Ilee , J

    Booth , A. S., Tabone , B., Ilee , J. D., et al. 2021, , 257, 16, 10.3847/1538-4365/ac1ad4

  18. [27]

    2000, , 361, 1178

    Casse , F., & Ferreira , J. 2000, , 361, 1178. astro-ph/0008244

  19. [28]

    F., Liu , H

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

  20. [29]

    Clarke , C. J. 2007, , 376, 1350, 10.1111/j.1365-2966.2007.11547.x

  21. [30]

    J., Gendrin , A., & Sotomayor , M

    Clarke , C. J., Gendrin , A., & Sotomayor , M. 2001, , 328, 485, 10.1046/j.1365-8711.2001.04891.x

  22. [31]

    Coleman , G. A. L., & Haworth , T. J. 2022, , 514, 2315, 10.1093/mnras/stac1513

  23. [32]

    2020, , 634, L12, 10.1051/0004-6361/201936950

    de Valon , A., Dougados , C., Cabrit , S., et al. 2020, , 634, L12, 10.1051/0004-6361/201936950

  24. [33]

    N., Okuzumi , S., Flock , M., Pinilla , P., & Dzyurkevich , N

    Delage , T. N., Okuzumi , S., Flock , M., Pinilla , P., & Dzyurkevich , N. 2022, , 658, A97, 10.1051/0004-6361/202141689

  25. [34]

    2025, in press,

    Deng , D., Vioque , M., Pascucci , I., et al. 2025, in press,

  26. [35]

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

    Drazkowska , J., Bitsch , B., Lambrechts , 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 , 717, 10.48550/arXiv.2203.09759

  27. [36]

    2023, , 673, A78, 10.1051/0004-6361/202244767

    Emsenhuber , A., Burn , R., Weder , J., et al. 2023, , 673, A78, 10.1051/0004-6361/202244767

  28. [37]

    2023, , 945, 112, 10.3847/1538-4357/acb2c9

    Fang , M., Pascucci , I., Edwards , S., et al. 2023, , 945, 112, 10.3847/1538-4357/acb2c9

  29. [38]

    2018, , 868, 28, 10.3847/1538-4357/aae780

    ---. 2018, , 868, 28, 10.3847/1538-4357/aae780

  30. [39]

    I., Bergin , E

    Favre , C., Cleeves , L. I., Bergin , E. A., Qi , C., & Blake , G. A. 2013, , 776, L38, 10.1088/2041-8205/776/2/L38

  31. [40]

    E., Henning , T., Jayawardhana , R., & Oliveira , J

    Fedele , D., van den Ancker , M. E., Henning , T., Jayawardhana , R., & Oliveira , J. M. 2010, , 510, A72, 10.1051/0004-6361/200912810

  32. [41]

    B., Mulders , G

    Fernandes , R. B., Mulders , G. D., Pascucci , I., Mordasini , C., & Emsenhuber , A. 2019, , 874, 81, 10.3847/1538-4357/ab0300

  33. [42]

    1997, , 319, 340

    Ferreira , J. 1997, , 319, 340. astro-ph/9607057

  34. [43]

    2006, , 453, 785, 10.1051/0004-6361:20054231

    Ferreira , J., Dougados , C., & Cabrit , S. 2006, , 453, 785, 10.1051/0004-6361:20054231

  35. [44]

    F., & Ercolano , B

    Flaischlen , S., Preibisch , T., Manara , C. F., & Ercolano , B. 2021, , 648, A121, 10.1051/0004-6361/202039746

  36. [45]

    Gammie , C. F. 1996, , 457, 355, 10.1086/176735

  37. [46]

    J., & Facchini , S

    G \'a rate , M., Pinilla , P., Haworth , T. J., & Facchini , S. 2024, , 681, A84, 10.1051/0004-6361/202347850

  38. [47]

    N., Stadler , J., et al

    G \'a rate , M., Delage , T. N., Stadler , J., et al. 2021, , 655, A18, 10.1051/0004-6361/202141444

  39. [48]

    2009, , 690, 1539, 10.1088/0004-637X/690/2/1539

    Gorti , U., & Hollenbach , D. 2009, , 690, 1539, 10.1088/0004-637X/690/2/1539

  40. [49]

    2006, , 648, 484, 10.1086/505788

    Hartmann , L., D'Alessio , P., Calvet , N., & Muzerolle , J. 2006, , 648, 484, 10.1086/505788

  41. [50]

    2016, , 54, 135, 10.1146/annurev-astro-081915-023347

    Hartmann , L., Herczeg , G., & Calvet , N. 2016, , 54, 135, 10.1146/annurev-astro-081915-023347

  42. [51]

    1994, , 428, 654, 10.1086/174276

    Hollenbach , D., Johnstone , D., Lizano , S., & Shu , F. 1994, , 428, 654, 10.1086/174276

  43. [52]

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

  44. [54]

    N., Dullemond , C

    Kimmig , C. N., Dullemond , C. P., & Kley , W. 2020, , 633, A4, 10.1051/0004-6361/201936412

  45. [55]

    2021, , 910, 51, 10.3847/1538-4357/abe2af

    Komaki , A., Nakatani , R., & Yoshida , N. 2021, , 910, 51, 10.3847/1538-4357/abe2af

  46. [56]

    2016, , 54, 271, 10.1146/annurev-astro-081915-023307

    Kratter , K., & Lodato , G. 2016, , 54, 271, 10.1146/annurev-astro-081915-023307

  47. [57]

    L., Ireland , M

    Kraus , A. L., Ireland , M. J., Hillenbrand , L. A., & Martinache , F. 2012, , 745, 19, 10.1088/0004-637X/745/1/19

  48. [58]

    K., & Inutsuka , S.-i

    Kunitomo , M., Suzuki , T. K., & Inutsuka , S.-i. 2020, , 492, 3849, 10.1093/mnras/staa087

  49. [59]

    P., Kuchner , M

    Laos , S., Wisniewski , J. P., Kuchner , M. J., et al. 2022, , 935, 111, 10.3847/1538-4357/ac8156

  50. [60]

    P., et al

    Lega , E., Morbidelli , A., Nelson , R. P., et al. 2022, , 658, A32, 10.1051/0004-6361/202141675

  51. [61]

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

    Lesur , G., Flock , M., Ercolano , B., et al. 2023 a , 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 , 465, 10.48550/arXiv.2203.09821

  52. [62]

    Lesur , G. R. J., Baghdadi , S., Wafflard-Fernandez , G., et al. 2023 b , , 677, A9, 10.1051/0004-6361/202346005

  53. [63]

    E., Manara , C

    Lodato , G., Scardoni , C. E., Manara , C. F., & Testi , L. 2017, , 472, 4700, 10.1093/mnras/stx2273

  54. [64]

    2018, , 618, A120, 10.1051/0004-6361/201731733

    Louvet , F., Dougados , C., Cabrit , S., et al. 2018, , 618, A120, 10.1051/0004-6361/201731733

  55. [65]

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

  56. [66]

    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, 10.48550/arXiv.2203.09930

  57. [67]

    F., Rosotti , G., Testi , L., et al

    Manara , C. F., Rosotti , G., Testi , L., et al. 2016, , 591, L3, 10.1051/0004-6361/201628549

  58. [68]

    F., Testi , L., Herczeg , G

    Manara , C. F., Testi , L., Herczeg , G. J., et al. 2017, , 604, A127, 10.1051/0004-6361/201630147

  59. [69]

    F., Tazzari , M., Long , F., et al

    Manara , C. F., Tazzari , M., Long , F., et al. 2019, , 628, A95, 10.1051/0004-6361/201935964

  60. [70]

    F., Natta , A., Rosotti , G

    Manara , C. F., Natta , A., Rosotti , G. P., et al. 2020, , 639, A58, 10.1051/0004-6361/202037949

  61. [71]

    2022, , 667, A17, 10.1051/0004-6361/202142946

    Martel , \'E ., & Lesur , G. 2022, , 667, A17, 10.1051/0004-6361/202142946

  62. [72]

    2024, , 686, A9, 10.1051/0004-6361/202348546

    Martire , P., Longarini , C., Lodato , G., et al. 2024, , 686, A9, 10.1051/0004-6361/202348546

  63. [73]

    F., Ansdell , M., et al

    Mauc \'o , K., Manara , C. F., Ansdell , M., et al. 2023, , 679, A82, 10.1051/0004-6361/202347627

  64. [74]

    C., & Kataoka , A

    Miotello , A., Kamp , I., Birnstiel , T., Cleeves , L. C., & Kataoka , A. 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 , 501, 10.48550/arXiv.2203.09818

  65. [75]

    Miret-Roig , N., Galli , P. A. B., Olivares , J., et al. 2022, , 667, A163, 10.1051/0004-6361/202244709

  66. [76]

    Morbidelli , A., & Raymond , S. N. 2016, Journal of Geophysical Research (Planets), 121, 1962, 10.1002/2016JE005088

  67. [78]

    D., Pascucci , I., Manara , C

    Mulders , G. D., Pascucci , I., Manara , C. F., et al. 2017, , 847, 31, 10.3847/1538-4357/aa8906

  68. [79]

    2018, , 857, 57, 10.3847/1538-4357/aab70b

    Nakatani , R., Hosokawa , T., Yoshida , N., Nomura , H., & Kuiper , R. 2018, , 857, 57, 10.3847/1538-4357/aab70b

  69. [80]

    2024, , 686, A201, 10.1051/0004-6361/202348676

    Nazari , P., Tabone , B., Ahmadi , A., et al. 2024, , 686, A201, 10.1051/0004-6361/202348676

  70. [81]

    K., & Morbidelli , A

    Ogihara , M., Kokubo , E., Suzuki , T. K., & Morbidelli , A. 2018, , 615, A63, 10.1051/0004-6361/201832720

  71. [82]

    2015, , 584, L1, 10.1051/0004-6361/201527117

    Ogihara , M., Morbidelli , A., & Guillot , T. 2015, , 584, L1, 10.1051/0004-6361/201527117

  72. [83]

    E., Clarke , C

    Owen , J. E., Clarke , C. J., & Ercolano , B. 2012, , 422, 1880, 10.1111/j.1365-2966.2011.20337.x

  73. [84]

    E., Ercolano , B., Clarke , C

    Owen , J. E., Ercolano , B., Clarke , C. J., & Alexander , R. D. 2010, , 401, 1415, 10.1111/j.1365-2966.2009.15771.x

  74. [85]

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

    Pascucci , I., Cabrit , S., Edwards , S., 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 , 567, 10.48550/arXiv.2203.10068

  75. [86]

    2020, , 903, 78, 10.3847/1538-4357/abba3c

    Pascucci , I., Banzatti , A., Gorti , U., et al. 2020, , 903, 78, 10.3847/1538-4357/abba3c

  76. [87]

    L., Cabrit , S., et al

    Pascucci , I., Beck , T. L., Cabrit , S., et al. 2025, Nature Astronomy, 9, 81, 10.1038/s41550-024-02385-7

  77. [88]

    Picogna , G., Ercolano , B., & Espaillat , C. C. 2021, , 508, 3611, 10.1093/mnras/stab2883

  78. [89]

    2005, , 160, 401, 10.1086/432891

    Preibisch , T., Kim , Y.-C., Favata , F., et al. 2005, , 160, 401, 10.1086/432891

  79. [90]

    E., Alves , J., et al

    Ratzenb \"o ck , S., Gro schedl , J. E., Alves , J., et al. 2023, , 678, A71, 10.1051/0004-6361/202346901

  80. [91]

    2015, , 576, A52, 10.1051/0004-6361/201424846

    Ribas , \'A ., Bouy , H., & Mer \' n , B. 2015, , 576, A52, 10.1051/0004-6361/201424846

  81. [92]

    Ribas , \'A ., Mer \' n , B., Bouy , H., & Maud , L. T. 2014, , 561, A54, 10.1051/0004-6361/201322597

  82. [93]

    2010, , 512, A15, 10.1051/0004-6361/200913403

    Ricci , L., Testi , L., Natta , A., et al. 2010, , 512, A15, 10.1051/0004-6361/200913403

  83. [94]

    2020, , 639, A95, 10.1051/0004-6361/201937418

    Riols , A., Lesur , G., & Menard , F. 2020, , 639, A95, 10.1051/0004-6361/201937418

  84. [95]

    J., Klahr , H., Fendt , C., & Dullemond , C

    Rodenkirch , P. J., Klahr , H., Fendt , C., & Dullemond , C. P. 2020, , 633, A21, 10.1051/0004-6361/201834945

  85. [96]

    P., Clarke , C

    Rosotti , G. P., Clarke , C. J., Manara , C. F., & Facchini , S. 2017, , 468, 1631, 10.1093/mnras/stx595

  86. [97]

    Ruaud , M., Gorti , U., & Hollenbach , D. J. 2022, , 925, 49, 10.3847/1538-4357/ac3826

  87. [98]

    A., Gonz\'alez-Ruilova , C., Cieza , L

    Ruiz-Rodriguez , D. A., Gonz\'alez-Ruilova , C., Cieza , L. A., et al. 2025, in press,

  88. [99]

    D., Booth , R

    Sellek , A. D., Booth , R. A., & Clarke , C. J. 2020, , 498, 2845, 10.1093/mnras/staa2519

  89. [100]

    D., Grassi , T., Picogna , G., et al

    Sellek , A. D., Grassi , T., Picogna , G., et al. 2024, arXiv e-prints, arXiv:2408.00848, 10.48550/arXiv.2408.00848

  90. [101]

    I., & Sunyaev , R

    Shakura , N. I., & Sunyaev , R. A. 1973, , 500, 33

  91. [102]

    N., Pascucci , I., Edwards , S., et al

    Simon , M. N., Pascucci , I., Edwards , S., et al. 2016, , 831, 169, 10.3847/0004-637X/831/2/169

  92. [103]

    Somigliana , A., Toci , C., Lodato , G., Rosotti , G., & Manara , C. F. 2020, , 492, 1120, 10.1093/mnras/stz3481

  93. [104]

    2024, arXiv e-prints, arXiv:2407.21101, 10.48550/arXiv.2407.21101

    Somigliana , A., Testi , L., Rosotti , G., et al. 2024, arXiv e-prints, arXiv:2407.21101, 10.48550/arXiv.2407.21101

  94. [105]

    S., Li , Z.-Y., Krasnopolsky , R., & Shang , H

    Suriano , S. S., Li , Z.-Y., Krasnopolsky , R., & Shang , H. 2018, , 477, 1239, 10.1093/mnras/sty717

  95. [106]

    K., Ogihara , M., Morbidelli , A., Crida , A., & Guillot , T

    Suzuki , T. K., Ogihara , M., Morbidelli , A., Crida , A., & Guillot , T. 2016, , 596, A74, 10.1051/0004-6361/201628955

  96. [107]

    P., Cridland , A

    Tabone , B., Rosotti , G. P., Cridland , A. J., Armitage , P. J., & Lodato , G. 2022 a , , 512, 2290, 10.1093/mnras/stab3442

  97. [108]

    P., Lodato , G., et al

    Tabone , B., Rosotti , G. P., Lodato , G., et al. 2022 b , , 512, L74, 10.1093/mnrasl/slab124

  98. [109]

    2017, , 607, L6, 10.1051/0004-6361/201731691

    Tabone , B., Cabrit , S., Bianchi , E., et al. 2017, , 607, L6, 10.1051/0004-6361/201731691

  99. [110]

    2020, , 640, A82, 10.1051/0004-6361/201834377

    Tabone , B., Cabrit , S., Pineau des For \^e ts , G., et al. 2020, , 640, A82, 10.1051/0004-6361/201834377

  100. [111]

    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, 10.2458/azu_uapress_9780816531240-ch015

  101. [112]

    F., et al

    Testi , L., Natta , A., Manara , C. F., et al. 2022, , 663, A98, 10.1051/0004-6361/202141380

  102. [113]

    J., Sheehan , P

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

  103. [114]

    G., Rosotti , G., & Trapman , L

    Toci , C., Lodato , G., Livio , F. G., Rosotti , G., & Trapman , L. 2023, , 518, L69, 10.1093/mnrasl/slac137

  104. [115]

    2021, , 507, 818, 10.1093/mnras/stab2112

    Toci , C., Rosotti , G., Lodato , G., Testi , L., & Trapman , L. 2021, , 507, 818, 10.1093/mnras/stab2112

  105. [116]

    2024, , 533, 1211, 10.1093/mnras/stae1748

    Tong , S., Alexander , R., & Rosotti , G. 2024, , 533, 1211, 10.1093/mnras/stae1748

  106. [117]

    F., & Bruderer , S

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

  107. [118]

    D., Hogerheijde , M

    Trapman , L., Rosotti , G., Bosman , A. D., Hogerheijde , M. R., & van Dishoeck , E. F. 2020, , 640, A5, 10.1051/0004-6361/202037673

  108. [119]

    2023, , 954, 41, 10.3847/1538-4357/ace7d1

    Trapman , L., Rosotti , G., Zhang , K., & Tabone , B. 2023, , 954, 41, 10.3847/1538-4357/ace7d1

  109. [120]

    Trapman , L., Zhang , K., van't Hoff , M. L. R., Hogerheijde , M. R., & Bergin , E. A. 2022, , 926, L2, 10.3847/2041-8213/ac4f47

  110. [121]

    in press, 2025 a ,

    Trapman , L., Zhang , K., Rosotti , G., et al. in press, 2025 a ,

  111. [122]

    in press, 2025 b ,

    Trapman , L., Vioque , M., Kurtovic , N., et al. in press, 2025 b ,

  112. [123]

    E., Hacar , A., van Dishoeck , E

    van Terwisga , S. E., Hacar , A., van Dishoeck , E. F., Oonk , R., & Portegies Zwart , S. 2022, , 661, A53, 10.1051/0004-6361/202141913

  113. [124]

    2014, , 570, A82, 10.1051/0004-6361/201423776

    Venuti , L., Bouvier , J., Flaccomio , E., et al. 2014, , 570, A82, 10.1051/0004-6361/201423776

  114. [125]

    2023, , 677, A70, 10.1051/0004-6361/202245305

    Wafflard-Fernandez , G., & Lesur , G. 2023, , 677, A70, 10.1051/0004-6361/202245305

  115. [126]

    2019, , 874, 90, 10.3847/1538-4357/ab06fd

    Wang , L., Bai , X.-N., & Goodman , J. 2019, , 874, 90, 10.3847/1538-4357/ab06fd

  116. [127]

    2017, , 847, 11, 10.3847/1538-4357/aa8726

    Wang , L., & Goodman , J. 2017, , 847, 11, 10.3847/1538-4357/aa8726

  117. [128]

    2023, , 674, A165, 10.1051/0004-6361/202243453

    Weder , J., Mordasini , C., & Emsenhuber , A. 2023, , 674, A165, 10.1051/0004-6361/202243453

  118. [129]

    J., & Haworth , T

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

  119. [130]

    E., & Batygin , K

    Yap , T. E., & Batygin , K. 2024, , 417, 116085, 10.1016/j.icarus.2024.116085

  120. [131]

    C., Nomura , H., Tsukagoshi , T., Furuya , K., & Ueda , T

    Yoshida , T. C., Nomura , H., Tsukagoshi , T., Furuya , K., & Ueda , T. 2022, , 937, L14, 10.3847/2041-8213/ac903a

  121. [132]

    P., Clarke , C

    Zagaria , F., Rosotti , G. P., Clarke , C. J., & Tabone , B. 2022, , 514, 1088, 10.1093/mnras/stac1461

  122. [133]

    Zhang , K. 2025, . xxxx.xxxx

  123. [134]

    2025, in press,

    Zhang , K., P \'e rez , L., Pascucci , I., et al. 2025, in press,

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.