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Dust Scattering Albedo at Millimeter-Wavelengths in the TW Hya Disk

T0 review · 2 major / 6 minor · reviewed 2026-08-11 · deepseek-v4-flash

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Pith's one-line read Pressure-broadened CO wings measure the dust albedo in TW Hya's inner disk without an opacity model.

desk verdict Genuinely new method paper, but the quoted albedo values rest on a RADMC-3D geometry that the paper's own settling calculation contradicts, so the 0.5–0.8 range is provisional. read the letter →

arxiv 2412.10731 v1 pith:UAMUSAGO submitted 2024-12-14 astro-ph.EP astro-ph.GA

Tomohiro C. Yoshida , Hideko Nomura , Takashi Tsukagoshi , Kiyoaki Doi , Kenji Furuya , Akimasa Kataoka This is my paper · ORCID
classification astro-ph.EPastro-ph.GA
keywords protoplanetarydisksdustscatteringalbedoTWHyamillimetercontinuumpressure-broadenedCOlinesgraingrowthALMAplanetformation
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 claims that the dust scattering albedo — the fraction of radiation a dust grain scatters rather than absorbs — in the inner 6 au of the TW Hya protoplanetary disk is high, about 0.5–0.8 at wavelengths from 0.9 to 3 mm, and that this is the first measurement of the albedo spectrum that does not assume a dust opacity model. The key move is to use the pressure-broadened wings of the CO $J=2-1$ and $J=3-2$ lines as an optically thin thermometer of the disk midplane, breaking the usual degeneracy between albedo and temperature in thermal dust emission. If the claim holds, scattering removes a substantial fraction of the millimeter continuum intensity in this disk, so dust masses estimated under optically thin or scattering-free assumptions are too low. The same data also imply a maximum grain size near $340\,\mu\mathrm{m}$, a grain-size distribution power-law index above $-4.1$, and porosity below $0.96$.

What carries the argument

The load-bearing object is the scattering intensity-reduction factor $\chi_\nu$ that relates an optically thick dust slab's emergent intensity to the Planck function, $I_\nu = \chi_\nu B_\nu(T)$, with $\chi$ decreasing as the effective albedo $\omega_{\mathrm{eff}}$ increases. The paper obtains the temperature without a dust model by solving Equation (15), which equates the ratio of the two CO line optical depths, derived from observed line and continuum intensities, to a temperature-only function $C(T)$; the pressure-broadened CO line wings supply the optically thin, high-signal-to-noise midplane thermometer. With the temperature in hand, each continuum band gives $\chi_\nu$, and a Monte Carlo radiative transfer calculation of the $\chi$\u2013$\omega_{\mathrm{eff}}$ relation converts those factors into albedos. The albedo spectrum is then compared with and fit to grain models through the effective scattering opacity $\kappa_s^{\mathrm{eff}} = (1-g)\kappa_s$.

What would settle it

Measure the continuum optical depth of the inner $r<6$ au at 3.2 mm with a method that does not assume the SED shape, such as resolved imaging that isolates the optically thick core; if the Band 3 continuum is not optically thick, the inferred intensity-reduction factors and albedos would be biased.

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Extended reading notes

Core claim

On the paper's own terms, the discovery is that the observed inner-disk continuum at 0.87–3.2 mm can be written as $I_\nu = \chi_\nu B_\nu(T)$ with an intensity reduction factor that implies an effective scattering albedo between roughly 0.5 and 0.8, independent of any assumed dust opacity law. The albedo is inferred after solving for the midplane temperature from the ratio of pressure-broadened CO line wings, which are optically thin and trace the midplane inside the CO snowline. The resulting albedo spectrum is broadly consistent with the Ricci default, DIANA, and DSHARP default grain models but excludes the Ricci compact and DSHARP Zubko compositions; freeing composition parameters leaves the grain size, grain-size-distribution slope, and porosity constrained at $a_{\max}\sim340\,\mu\mathrm{m}$, $q_{\mathrm{pow}}>-4.1$, and $p<0.96$. The high albedo is presented as direct evidence that scattering-induced intensity reduction operates in this disk.

Load-bearing premise

The result assumes the dust continuum at $r<6$ au is optically thick at every wavelength from 0.87 to 3.2 mm, so $I = \chi B(T)$ holds; the paper takes this from earlier modeling rather than verifying it at the longest wavelengths.

Editorial extensions

If this is right

  • Dust masses for the TW Hya inner disk computed from millimeter continua under optically thin or scattering-free assumptions are too low, because scattering reduces the emergent intensity.
  • The Ricci default, DIANA, and DSHARP default dust models survive the albedo comparison, while Ricci compact and DSHARP Zubko models are ruled out for this region.
  • The constraint $a_{\max}\sim340\,\mu\mathrm{m}$, combined with the adopted disk parameters, implies fragmentation-limited grain growth at a threshold velocity near $0.08\,\mathrm{m\,s^{-1}}$.
  • Absolute flux uncertainties of roughly 10% ($1\sigma$) on ALMA image-plane fluxes, about twice the usually assumed value, are needed to reproduce the scatter among archival observations.
  • The same CO-wing thermometer method can be applied to other disks with pressure-broadened CO emission to build a sample of model-independent albedo spectra.

Reading between the lines

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

  • If the high albedo found here is common in inner disks, survey dust masses derived from optically thin millimeter fluxes would be systematically low, which would shift disk mass distributions upward.
  • A direct test of the layered-dust assumption is to measure the vertical dust scale height in the same region, since well-mixed dust would suppress the line-wing emission that the method relies on.
  • Future far-infrared and submillimeter photometry with better absolute flux accuracy could separate the surviving models through the short-wavelength slope of the albedo spectrum, where they differ most.
  • The fragmentation-velocity estimate depends on the adopted turbulence parameter $\alpha$; independent measurements of $\alpha$ in the same region would test whether the small grains are genuinely fragile.
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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

2 major / 6 minor

Summary. The paper proposes a method to measure the millimeter dust scattering albedo in a protoplanetary disk without assuming a dust opacity model. The key idea is to use optically thin, pressure-broadened CO J=2-1 and J=3-2 line wings as a midplane thermometer, combined with the two-line LTE relation in Equations (10)-(15), to break the usual degeneracy between dust temperature and albedo. The method is applied to ALMA observations of the TW Hya disk at r<6 au: a forward model with MCMC gives a midplane temperature T0 ~ 45 K and intensity reduction factors chi ~ 0.8 at Bands 6 and 7; combining with continuum at Bands 3, 4, 6, and 7 yields chi_nu ~ 0.7-1.0. A RADMC-3D calculation converts chi to effective albedo, giving omega ~ 0.5-0.8 at 0.87-3.2 mm. The albedo spectrum is compared with Ricci, DIANA, and DSHARP dust models, and MCMC fits of the DSHARP material parameters give amax ~ 340 um, qpow > -4.1, and p < 0.96. Appendix A uses many archival ALMA images to estimate absolute flux uncertainties of roughly 10%, which is larger than the nominal values.

Significance. If correct, this is a significant result: it would be the first millimeter albedo measurement that does not adopt a particular dust opacity model, and it would demonstrate that scattering-induced intensity reduction is important in an optically thick inner disk, implying that dust masses derived under optically thin or scattering-free assumptions are underestimated. The paper has genuine strengths: the formal derivation in Section 2 is clean and self-contained; the MCMC fitting is described with sufficient detail (walkers, steps, priors in Table 1); the treatment of absolute flux uncertainty in Appendix A is careful and empirically grounded; and the authors are explicit about non-constraints such as Band 8 and the composition degeneracy. The concern is that the headline albedo values rest on two load-bearing assumptions that are not sufficiently stress-tested: the optically thick continuum assumption at all bands and the fixed vertical geometry assumed in the RADMC-3D chi-omega conversion.

major comments (2)
  1. [Section 4.2 and Section 6.1, Eqs. (26)-(27)] The RADMC-3D chi-omega relation used to convert the observed intensity reduction factors into albedos is computed for a dust slab with vertical scale height h_d = 0.05 H_g. However, the paper's own settling calculation in Section 6.1, using the best-fit a_max = 340 um, rho = 2 g cm^-3, Sigma_g = 1200 g cm^-2, and alpha ~ 10^-4, gives f_H ~ 0.7. This is a factor of roughly 14 larger than the slab height used in the chi-omega conversion. Since the chi-omega relation depends on disk geometry, as acknowledged in Section 4.2, the inferred omega values at Bands 3-7 and all subsequent dust-property constraints in Section 5 could shift. The manuscript does not acknowledge or test this internal inconsistency; the statement in Section 6.1 that f_H ~ 0.7 is 'still consistent with the settling scenario' addresses only the visibility of the pressure-broadened wings, not the validity of the chi-omega conversion. I request either a physical justification for h_d = 0.05 H_g for the mm-emitting grains or a recomputed chi-omega relation for f_H = 0.7, with the resulting uncertainty propagated through Figures 9-13.
  2. [Section 4.1, Eq. (17)] The derivation of chi_nu assumes the dust continuum is optically thick at every band, including Band 3 at 3.2 mm, based on Macias et al. (2021). This is a load-bearing assumption: if the Band 3 continuum is not optically thick, Equation (17) should include an additional (1 - exp(-tau_nu)) factor, and the inferred chi_3 and omega_3 would be biased. Because Band 3 anchors the long-wavelength end of the claimed 0.5-0.8 albedo spectrum, this assumption deserves direct testing. The paper provides no explicit verification of tau_nu > 1 for the r < 6 au region in the data analyzed here. Please either verify the optical-thickness assumption at each band, for example with resolved radial profiles or by including tau_nu as a free parameter, or quantify how the derived albedo spectrum changes if one or more bands are only moderately optically thick.
minor comments (6)
  1. [Abstract and Section 5.3] The phrase 'even without assuming dust composition' overstates the analysis: the composition fitting frees the volume fractions of five pre-selected materials (water ice, silicates, troilite, organics, Zubko carbon) but still assumes the DSHARP optical-constant library. Please rephrase to something like 'without fixing the relative abundances of the adopted dust components.'
  2. [Appendix A] The project ID list contains duplicates (2016.1.00440.S and 2018.A.00021.S appear twice) and a missing comma after 2016.1.01375.S; please clean up the list.
  3. [Section 4.2] The statement that the RADMC-3D results 'do not depend on the choice of wavelength' should be justified in one sentence, for example by noting that the slab is made optically thick and that the chi-omega relation is expressed in terms of albedo. As written, it could be misread as claiming that dust opacities themselves are wavelength-independent.
  4. [Section 4.1, Eq. (18)] The text says 'the power law index of 0.5,' but Equation (18) has Sigma_g proportional to r^{-0.5}; the sign convention should be stated explicitly to avoid confusion.
  5. [Figure 3] The gray model curves in the bottom zoom-in panels are nearly indistinguishable from the data; plotting a credible-interval band or using different line styles would improve readability.
  6. [Section 6.1] The sentence 'This value is not very small but still consistent with the settling scenario' is vague; please quantify the comparison, especially because f_H ~ 0.7 is the same quantity used to assess the layered geometry assumed in the RADMC-3D conversion.

Circularity Check

0 steps flagged · score 2.0 of 10

The albedo measurement is not circular: the CO-line temperature cancels the albedo factors, and the χ–ω geometry inconsistency is a robustness issue, not a circular reduction.

full rationale

The central derivation is non-circular. The midplane temperature is obtained from the ratio of two optically thin CO line wings: in Equation (15) the intensity-reduction factors χ cancel identically, so Td is determined by line ratios and known spectroscopic constants, not by the dust albedo. The χν values then follow from the observed continuum divided by the Planck function at that T (Equations 12 and 17), which is a measurement rather than a fit to a dust-opacity model. The subsequent conversion χ→ωeff uses a RADMC-3D grid with an assumed vertical geometry (dust scale height 0.05 × Hg and dust surface density 0.01 × Σg, Section 4.2). This is a genuine modeling assumption, and the paper's own settling estimate (Section 6.1, Equation 26, with a = 340 μm, α ~ 1e-4) gives fH ~ 0.7, roughly 14 times the adopted value; if the χ–ω relation is sensitive to fH, the quoted albedo 0.5–0.8 could shift. That is an unverified-geometry and self-consistency concern, not a circular reduction: the assumption does not define the albedo in terms of itself, and no equation equates an input to the output by construction. Self-citations are present and the Yoshida et al. (2022) pressure-broadened CO-wing identification is load-bearing for the method, but it is an empirical result based on the same ALMA data and is re-examined here (Figure 3), so it constitutes independent support rather than a self-referential chain. The dust-property constraints in Section 5 are explicitly fits to the derived albedo spectrum, not predictions from it; no fitted parameter is renamed as a prediction. Therefore no significant circularity is found; the score of 2 reflects the reliance on prior-group work for the line-wing identification and the unacknowledged geometry inconsistency, not a circular derivation.

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

The central measurement rests on the optically thick continuum assumption, the optically thin and layered line-wing assumption, and the RADMC-3D conversion from intensity reduction to effective albedo. These are domain assumptions from prior literature rather than standard mathematics. The MCMC fitting introduces several free parameters: T0, Sigma_g,0, XCO, chi6, and chi7. The dust-property constraints later fit amax, qpow, p, and volume fractions to the measured albedo, so they are not independent of the dust models. No new physical entities are introduced.

free parameters (9)
  • T0 (midplane temperature at r0 = 3.2 au) = 44.5 (+3, -2) K
    Free parameter in the MCMC fit to the two CO spectra; sets the whole radial temperature profile.
  • log10 Sigma_g,0 (gas surface density at cavity radius) = 3.04 (+0.48, -0.38)
    Free parameter; poorly constrained because it is degenerate with XCO in the optically thin line wings.
  • log10 XCO (CO/H2 abundance) = 5.10 (+0.76, -0.99)
    Free parameter; degenerate with Sigma_g,0 in the line-wing fitting.
  • chi6 (intensity reduction factor at 1.3 mm, CO J=2-1) = 0.80 (+0.01, -0.02)
    Free parameter in MCMC; central to the albedo measurement.
  • chi7 (intensity reduction factor at 0.87 mm, CO J=3-2) = 0.81 (+0.01, -0.02)
    Free parameter in MCMC; central to the albedo measurement.
  • amax (maximum grain size) = 340 (+180, -120) um
    Fitted to the measured albedo spectrum using the DSHARP model in Sections 5.2 and 5.3.
  • qpow (grain size power-law index) = > -4.1 (weak peak near -4.2)
    Fitted to the albedo spectrum with DSHARP model; only a lower limit is well constrained.
  • p (porosity) = < 0.96 (volume filling factor > 2-4%)
    Fitted to the albedo spectrum; upper limit only.
  • Volume fractions of five materials (water ice, silicates, troilite, organics, Zubko carbon) = Unconstrained, upper limits about 50% each
    Free parameters in the composition-independent fit of Section 5.3.
assumptions (6)
  • domain assumption Dust continuum at r<6 au is optically thick at all observed bands, so I = chi_nu B_nu(T) holds (Equation 17).
    Adopted from Macias et al. 2021; the whole decomposition of continuum into temperature and scattering reduction depends on it.
  • domain assumption The pressure-broadened CO line wings are optically thin, in LTE, and emerge from the same midplane layer as the dust, with Tg = Td.
    Used to derive Equations (10)-(14) and the T0 measurement; partially discussed in Section 6.1.
  • domain assumption The midplane temperature profile is T = T0 (r/r0)^-0.5.
    The power-law index is fixed from Macias et al. 2021; only T0 is fitted.
  • domain assumption The RADMC-3D chi-omega_eff relation computed with isotropic scattering and a fixed dust vertical distribution applies to the real disk.
    The albedo values in Figure 9 are obtained through this conversion, whose systematic uncertainty is not propagated.
  • domain assumption Dust grains are vertically settled so dust and gas form a layered structure.
    The toy model and the forward model assume a dust layer below the gas layer; Section 6.1 estimates fH ~ 0.7 to support this.
  • standard math The LTE optical-depth ratio of two CO transitions depends only on temperature and known spectroscopic constants.
    Foundational to Equation (15); standard radiative transfer under LTE.

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Cite this review

Pith. "Pith review of Dust Scattering Albedo at Millimeter-Wavelengths in the TW Hya Disk." pith.science (2026). https://pith.science/paper/UAMUSAGO

@misc{pith2026241210731,
  author       = {Pith},
  title        = {Pith review of: Dust Scattering Albedo at Millimeter-Wavelengths in the TW Hya Disk},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/UAMUSAGO}},
  note         = {Machine review of arXiv:2412.10731}
}
abstract

Planetary bodies are formed by coagulation of solid dust grains in protoplanetary disks. Therefore, it is crucial to constrain the physical and chemical properties of the dust grains. In this study, we measure the dust albedo at mm-wavelength, which depends on dust properties at the disk midplane. Since the albedo and dust temperature are generally degenerate in observed thermal dust emission, it is challenging to determine them simultaneously. We propose to break this degeneracy by using multiple optically-thin molecular lines as a dust-albedo independent thermometer. In practice, we employ pressure-broadened CO line wings that provide an exceptionally high signal-to-noise ratio as an optically thin line. We model the CO $J=2-1$ and $3-2$ spectra observed by the Atacama Large Millimeter/sub-millimeter Array (ALMA) at the inner region ($r<6\ {\rm au}$) of the TW Hya disk and successfully derived the midplane temperature. Combining multi-band continuum observations, we constrain the albedo spectrum at $0.9-3$ mm for the first time without assuming a dust opacity model. The albedo at these wavelengths is high, $\sim0.5-0.8$, and broadly consistent with the Ricci et al. (2010), DIANA, and DSHARP dust models. Even without assuming dust composition, we estimate the maximum grain size to be $\sim 340\ \mu m$, the power law index of the grain size distribution to be $>-4.1$, and porosity to be $<0.96$. The derived dust size may suggest efficient fragmentation with the threshold velocity of $\sim 0.08\ {\rm m\ s^{-1}}$. We also note that the absolute flux uncertainty of $\sim10\%$ ($1\sigma$) is measured and used in the analysis, which is approximately twice the usually assumed value.

Figures

Figures reproduced from arXiv: 2412.10731 by the authors.

Figure 1
Figure 1. Flowchart of the procedure of this paper. tion 3 is summarized in [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Layered structure discussed as a toy model. The white arrow indicates the propagation direction of a ray toward the observer. layers are τg and τd, respectively. Similarly, the gas and dust temperatures are Tg and Td, respectively. Consid￾ering radiative transfer along the direction from dust to gas layers, the emerging intensity It can be expressed as It = χd(τd, ω)B(Td)(1 − e −τd )e −τg + B(Tg)(1 − e −τg ), (2) wh… view at source ↗
Figure 3
Figure 3. CO J = 2 − 1 (blue) and J = 3 − 2 (orange) spectra at the center (r < 6 au) of the TW Hya disk. The bottom panels are the zoom-in version of the top panel. The grey lines indicate the models created from parameters randomly sampled from the MCMC chain (Section 4.3). The gray-shaded regions (|v| < 4 km s−1 ) are not used for fitting. 10 0 6 × 10 1 2 × 10 0 3 × 10 0 wavelength [mm] 10 1 10 2 I [mJy b e a m 1 ] [PITH_… view at source ↗
Figures from the paper (12 more)
Figure 4
Figure 4. Figure 4: Continuum SED at the center (r < 6 au) of the disk. The uncertainty of Band 3 (λ = 3.2 mm), 4 (2.1 mm), 6 (1.2 mm), and 7 (0.87 mm) fluxes are estimated from archival images (Appendix A) while that of Band 8 (0.63 mm) is a nominal but conservative value, ∼ 20%. disk ce…
Figure 5
Figure 5. Figure 5: Intensity reduction factor as a function of the effective albedo. The blue line is the results from the nu￾merical simulation while the black dotted line indicates an approximated formula in Equation (3). K, and ∼ 0.8 for both Band 6 and Band 7. The gas surface density…
Figure 6
Figure 6. Figure 6: Corner plot of the MCMC fitting of the emission model to the CO spectra. The three vertical dashed lines in each histogram indicate the 16, 50, and 84 th percentiles. factors as long as the total continuum flux is conserved. Indeed, we re-ran the fitting with a power l…
Figure 7
Figure 7. Figure 7: Estimated temperature profile (Blue). The black dashed line is the best-fit temperature profile by Ueda et al. (2020) for comparison. 10 0 6 × 10 1 2 × 10 0 3 × 10 0 wavelength [mm] 0.0 0.2 0.4 0.6 0.8 1.0 1.2 [PITH_FULL_IMAGE:figures/full_fig_p009_7.png]
Figure 8
Figure 8. Figure 8: Intensity reduction factors at Band 3 (λ = 3.2 mm), 4 (2.1 mm), 6 (1.2 mm), 7 (0.87 mm), and 8 (0.63 mm) at the inner region (r < 6 au) of the TW Hya disk. The grey points and dashed lines are derived by taking into account the uncertainty in the temperature. 2020). Th…
Figure 10
Figure 10. Figure 10: Comparison of albedo spectra created from dust models on the literature for various maximum dust sizes (color lines) with ones derived from observations (grey area) [PITH_FULL_IMAGE:figures/full_fig_p011_10.png]
Figure 11
Figure 11. Figure 11: Corner plot of the MCMC fitting of dust model to the derived dust albedo spectrum. gradient. However, both the observed CO spectra are well fitted by the optically thin line wings with a con￾stant temperature ( [PITH_FULL_IMAGE:figures/full_fig_p012_11.png]
Figure 12
Figure 12. Figure 12: Dependencies of the albedo spectrum on amax, qpow and p in the case of the DSHARP default composition model (color lines). Grey area shows constraints from observations. the ballistic particle-cluster aggregation (BPCA; Mukai et al. 1992; Kozasa et al. 1992; Shen et a…
Figure 13
Figure 13. Figure 13: Corner plot of the MCMC fitting of dust model to the derived dust albedo spectrum. In this fitting, we kept the composition parameters free. 0.0 0.2 0.4 0.6 0.8 1.0 1.0 1.2 1.4 1.6 1.8 2.0 B(Tg)/ B(Td) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 fg [PITH_FULL_IMAGE:figures/full_fig_…
Figure 14
Figure 14. Figure 14: Line emerging factor fg as a function of ω and B(Tg)/B(Td). In this context, it is interesting to compare our re￾sults with Delussu et al. (2024). Delussu et al. (2024) found that the Ricci compact model matches observa￾tions better than the DSHARP default model, whil…
Figure 15
Figure 15. Figure 15: indicates the total flux versus frequency for all bands. We fitted these points by the fifth-degree polynomial 10 2 2 × 10 2 3 × 10 24 × 10 2 [GHz] 10 1 10 0 Flux density [Jy] [PITH_FULL_IMAGE:figures/full_fig_p016_15.png]
Figure 16
Figure 16. Figure 16: Deviation of measured fluxes against fitted flux densities. Star marks measured total flux on our self-calibrated images used in the analysis in the main sections. Squares indicates the product images which correspond to the data used for the self-calibrated images. T…

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Works this paper leans on

61 extracted references · 7 canonical work pages

  1. [1]

    M., Wilner, D

    Andrews, S. M., Wilner, D. J., Zhu, Z., et al. 2016, ApJL, 820, L40, doi: 10.3847/2041-8205/820/2/L40

    doi:10.3847/2041-8205/820/2/l40 2016

  2. [2]

    2021, ApJ, 910, 130, doi: 10.3847/1538-4357/abe61d

    Arakawa, S., & Krijt, S. 2021, ApJ, 910, 130, doi: 10.3847/1538-4357/abe61d

    doi:10.3847/1538-4357/abe61d 2021

  3. [3]

    Armitage, P. J. 2010, Astrophysics of Planet Formation Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068

    doi:10.1051/0004-6361/201322068 2010

  4. [4]

    P., Garufi, A., et al

    Avenhaus, H., Quanz, S. P., Garufi, A., et al. 2018, ApJ, 863, 44, doi: 10.3847/1538-4357/aab846 Barrado Y Navascu´ es, D. 2006, A&A, 459, 511, doi: 10.1051/0004-6361:20065717

    doi:10.3847/1538-4357/aab846 2018

  5. [5]

    A., Cleeves, L

    Bergin, E. A., Cleeves, L. I., Gorti, U., et al. 2013, Nature, 493, 644, doi: 10.1038/nature11805

    doi:10.1038/nature11805 2013

  6. [6]

    P., Zhu, Z., et al

    Birnstiel, T., Dullemond, C. P., Zhu, Z., et al. 2018, ApJL, 869, L45, doi: 10.3847/2041-8213/aaf743

    doi:10.3847/2041-8213/aaf743 2018

  7. [7]

    F., & Huffman, D

    Bohren, C. F., & Huffman, D. R. 1998, Absorption and Scattering of Light by Small Particles

    work page 1998

  8. [8]

    D., & Banzatti, A

    Bosman, A. D., & Banzatti, A. 2019, A&A, 632, L10, doi: 10.1051/0004-6361/201936638

    doi:10.1051/0004-6361/201936638 2019

Show all 61 references
  1. [9]

    D., Bergin, E

    Bosman, A. D., Bergin, E. A., Loomis, R. A., et al. 2021, ApJS, 257, 15, doi: 10.3847/1538-4365/ac1433

    2021 doi

  2. [10]

    L., Hunter, T

    Brogan, C. L., Hunter, T. R., & Fomalont, E. B. 2018, arXiv e-prints, arXiv:1805.05266, doi: 10.48550/arXiv.1805.05266

    2018 doi arXiv

  3. [11]

    Canta, A., Teague, R., Le Gal, R., & ¨Oberg, K. I. 2021, ApJ, 922, 62, doi: 10.3847/1538-4357/ac23da Carrasco-Gonz´ alez, C., Sierra, A., Flock, M., et al. 2019, ApJ, 883, 71, doi: 10.3847/1538-4357/ab3d33

    2021 doi

  4. [12]

    2022, MNRAS, 513, 5790, doi: 10.1093/mnras/stac1285

    Casassus, S., & C´ arcamo, M. 2022, MNRAS, 513, 5790, doi: 10.1093/mnras/stac1285

    2022 doi

  5. [13]

    A., Teague, R., et al

    Czekala, I., Loomis, R. A., Teague, R., et al. 2021, ApJS, 257, 2, doi: 10.3847/1538-4365/ac1430

    2021 doi

  6. [14]

    2024, A&A, 688, A81, doi: 10.1051/0004-6361/202450328

    Delussu, L., Birnstiel, T., Miotello, A., et al. 2024, A&A, 688, A81, doi: 10.1051/0004-6361/202450328

    2024 doi

  7. [15]

    2023, ApJ, 957, 11, doi: 10.3847/1538-4357/acf5df

    Doi, K., & Kataoka, A. 2023, ApJ, 957, 11, doi: 10.3847/1538-4357/acf5df

    2023 doi

  8. [16]

    Dominik, C., & Dullemond, C. P. 2024, A&A, 682, A144, doi: 10.1051/0004-6361/202347716

    2024 doi

  9. [17]

    2021, OpTool: Command-line driven tool for creating complex dust opacities, Astrophysics Source Code Library, record ascl:2104.010

    Dominik, C., Min, M., & Tazaki, R. 2021, OpTool: Command-line driven tool for creating complex dust opacities, Astrophysics Source Code Library, record ascl:2104.010. http://ascl.net/2104.010

    2021

  10. [18]

    1995, A&A, 300, 503

    Mutschke, H. 1995, A&A, 300, 503

    1995

  11. [19]

    Draine, B. T. 2003, ARA&A, 41, 241, doi: 10.1146/annurev.astro.41.011802.094840

    2003 arXiv

  12. [20]

    1995, Icarus, 114, 237, doi: 10.1006/icar.1995.1058

    Dubrulle, B., Morfill, G., & Sterzik, M. 1995, Icarus, 114, 237, doi: 10.1006/icar.1995.1058

    1995

  13. [21]

    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. http://ascl.net/1202.015

    2012

  14. [22]

    P., van Zadelhoff, G

    Dullemond, C. P., van Zadelhoff, G. J., & Natta, A. 2002, A&A, 389, 464, doi: 10.1051/0004-6361:20020608

    2002 doi

  15. [23]

    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

  16. [24]

    2020, AJ, 160, 270, doi: 10.3847/1538-3881/abbe1a Gaia Collaboration, Prusti, T., de Bruijne, J

    Harsono, D. 2020, AJ, 160, 270, doi: 10.3847/1538-3881/abbe1a Gaia Collaboration, Prusti, T., de Bruijne, J. H. J., et al. 2016, A&A, 595, A1, doi: 10.1051/0004-6361/201629272 Gaia Collaboration, Brown, A. G. A., Vallenari, A., et al. 2021, A&A, 649, A1, doi: 10.1051/0004-6361...

    2020 doi

  17. [25]

    2022, Journal of Quantitative Spectroscopy and Radiative Transfer, 277, 107949, doi: https://doi.org/10.1016/j.jqsrt.2021.107949

    Gordon, I., Rothman, L., Hargreaves, R., et al. 2022, Journal of Quantitative Spectroscopy and Radiative Transfer, 277, 107949, doi: https://doi.org/10.1016/j.jqsrt.2021.107949

    2022

  18. [26]

    1996, A&A, 311, 291

    Henning, T., & Stognienko, R. 1996, A&A, 311, 291

    1996

  19. [27]

    K., Oka, A., & Nakamoto, T

    Inoue, A. K., Oka, A., & Nakamoto, T. 2009, MNRAS, 393, 1377, doi: 10.1111/j.1365-2966.2008.14316.x

    2009

  20. [28]

    1978, Wave propagation and scattering in random media

    Ishimaru, A. 1978, Wave propagation and scattering in random media. Volume 1 - Single scattering and transport theory, Vol. 1, doi: 10.1016/B978-0-12-374701-3.X5001-7

    1978 doi

  21. [29]

    Jorsater, S., & van Moorsel, G. A. 1995, AJ, 110, 2037, doi: 10.1086/117668

    1995 doi

  22. [30]

    1992, A&A, 263, 423

    Kozasa, T., Blum, J., & Mukai, T. 1992, A&A, 263, 423

    1992

  23. [31]

    D., Zhang, K., et al

    Krijt, S., Bosman, A. D., Zhang, K., et al. 2020, ApJ, 899, 134, doi: 10.3847/1538-4357/aba75d Mac ´ ıas, E., Guerra-Alvarado, O., Carrasco-Gonz´ alez, C., et al. 2021, A&A, 648, A33, doi: 10.1051/0004-6361/202039812

    2020 doi

  24. [32]

    S., Rumpl, W., & Nordsieck, K

    Mathis, J. S., Rumpl, W., & Nordsieck, K. H. 1977, ApJ, 217, 425, doi: 10.1086/155591

    1977 doi

  25. [33]

    2007, in Astronomical Society of the Pacific Conference Series, Vol

    Golap, K. 2007, in Astronomical Society of the Pacific Conference Series, Vol. 376, Astronomical Data Analysis Software and Systems XVI, ed. R. A. Shaw, F. Hill, & D. J. Bell, 127 19

    2007

  26. [34]

    1993, Icarus, 106, 20, doi: 10.1006/icar.1993.1156

    Miyake, K., & Nakagawa, Y. 1993, Icarus, 106, 20, doi: 10.1006/icar.1993.1156

    1993

  27. [35]

    Greenberg, J. M. 1992, A&A, 262, 315

    1992

  28. [36]

    2016, ApJ, 827, 63, doi: 10.3847/0004-637X/827/1/63 ¨Oberg, K

    Musiolik, G., Teiser, J., Jankowski, T., & Wurm, G. 2016, ApJ, 827, 63, doi: 10.3847/0004-637X/827/1/63 ¨Oberg, K. I., & Bergin, E. A. 2021, PhR, 893, 1, doi: 10.1016/j.physrep.2020.09.004

    2016 doi

  29. [37]

    2012, ApJ, 752, 106, doi: 10.1088/0004-637X/752/2/106

    Okuzumi, S., Tanaka, H., Kobayashi, H., & Wada, K. 2012, ApJ, 752, 106, doi: 10.1088/0004-637X/752/2/106

    2012 doi

  30. [38]

    2019, ApJ, 878, 132, doi: 10.3847/1538-4357/ab204d

    Okuzumi, S., & Tazaki, R. 2019, ApJ, 878, 132, doi: 10.3847/1538-4357/ab204d

    2019 doi

  31. [39]

    J., Min, M., et al

    Pinte, C., Harries, T. J., Min, M., et al. 2009, A&A, 498, 967, doi: 10.1051/0004-6361/200811555

    2009 doi

  32. [40]

    2010, A&A, 512, A15, doi: 10.1051/0004-6361/200913403

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

    2010 doi

  33. [41]

    B., & Lightman, A

    Rybicki, G. B., & Lightman, A. P. 1979, Radiative processes in astrophysics Sch¨ oier, F. L., van der Tak, F. F. S., van Dishoeck, E. F., &

    1979

  34. [42]

    Black, J. H. 2005, A&A, 432, 369, doi: 10.1051/0004-6361:20041729

    2005 doi

  35. [43]

    I., & Sunyaev, R

    Shakura, N. I., & Sunyaev, R. A. 1973, A&A, 24, 337

    1973

  36. [44]

    T., & Johnson, E

    Shen, Y., Draine, B. T., & Johnson, E. T. 2008, ApJ, 689, 260, doi: 10.1086/592765

    2008 doi

  37. [45]

    2019, ApJ, 885, 52, doi: 10.3847/1538-4357/ab45f0

    Tazaki, R., Tanaka, H., Kataoka, A., Okuzumi, S., & Muto, T. 2019, ApJ, 885, 52, doi: 10.3847/1538-4357/ab45f0

    2019 doi

  38. [46]

    Teague, R., Bae, J., Huang, J., & Bergin, E. A. 2019, ApJL, 884, L56, doi: 10.3847/2041-8213/ab4a83

    2019 doi

  39. [47]

    M., et al

    Teague, R., Bae, J., Andrews, S. M., et al. 2022, ApJ, 936, 163, doi: 10.3847/1538-4357/ac88ca

    2022 doi

  40. [48]

    2022, ApJ, 928, 49, doi: 10.3847/1538-4357/ac5111

    Tsukagoshi, T., Nomura, H., Muto, T., et al. 2022, ApJ, 928, 49, doi: 10.3847/1538-4357/ac5111

    2022 doi

  41. [49]

    2020, ApJ, 893, 125, doi: 10.3847/1538-4357/ab8223

    Ueda, T., Kataoka, A., & Tsukagoshi, T. 2020, ApJ, 893, 125, doi: 10.3847/1538-4357/ab8223

    2020 doi

  42. [50]

    D., & Sandell, G

    Vacca, W. D., & Sandell, G. 2011, ApJ, 732, 8, doi: 10.1088/0004-637X/732/1/8

    2011 doi

  43. [51]

    Warren, S. G. 1984, ApOpt, 23, 1206, doi: 10.1364/AO.23.001206

    1984 doi

  44. [52]

    G., & Brandt, R

    Warren, S. G., & Brandt, R. E. 2008, Journal of Geophysical Research (Atmospheres), 113, D14220, doi: 10.1029/2007JD009744

    2008 doi

  45. [53]

    C., & Draine, B

    Weingartner, J. C., & Draine, B. T. 2001, ApJ, 548, 296, doi: 10.1086/318651

    2001 doi

  46. [54]

    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

  47. [55]

    2017, Introduction to Astrochemistry: Chemical Evolution from Interstellar Clouds to Star and Planet Formation, doi: 10.1007/978-4-431-54171-4

    Yamamoto, S. 2017, Introduction to Astrochemistry: Chemical Evolution from Interstellar Clouds to Star and Planet Formation, doi: 10.1007/978-4-431-54171-4

    2017 doi

  48. [56]

    2022, ApJL, 937, L14, doi: 10.3847/2041-8213/ac903a

    Ueda, T. 2022, ApJL, 937, L14, doi: 10.3847/2041-8213/ac903a

    2022 doi

  49. [57]

    C., Nomura, H., Furuya, K., et al

    Yoshida, T. C., Nomura, H., Furuya, K., et al. 2024, ApJ, 966, 63, doi: 10.3847/1538-4357/ad2fb4

    2024 doi

  50. [58]

    N., & Lithwick, Y

    Youdin, A. N., & Lithwick, Y. 2007, Icarus, 192, 588, doi: 10.1016/j.icarus.2007.07.012

    2007 doi

  51. [59]

    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

  52. [60]

    2019, ApJL, 877, L18, doi: 10.3847/2041-8213/ab1f8c

    Zhu, Z., Zhang, S., Jiang, Y.-F., et al. 2019, ApJL, 877, L18, doi: 10.3847/2041-8213/ab1f8c

    2019 doi

  53. [61]

    G., Mennella, V., Colangeli, L., & Bussoletti, E

    Zubko, V. G., Mennella, V., Colangeli, L., & Bussoletti, E. 1996, MNRAS, 282, 1321, doi: 10.1093/mnras/282.4.1321

    1996 doi

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