pith. machine review for the scientific record. sign in

arxiv: 2604.27133 · v1 · submitted 2026-04-29 · 🌌 astro-ph.SR · astro-ph.GA

Recognition: unknown

CORINOS V: Radiative transfer effects in protostellar ice observations

Will E. Thompson , Jennifer B. Bergner , Neal J. Evans II , Yao-Lun Yang , Vincent Kreft , Lenore Anderson , Klaus M. Pontoppidan , L. Ilsedore Cleeves
show 6 more authors
Ewine F. van Dishoeck Rachel E. Gross Jeong-Eun Lee Melissa K. McClure Nami Sakai Katerina Slavicinska
Authors on Pith no claims yet

Pith reviewed 2026-05-07 08:07 UTC · model grok-4.3

classification 🌌 astro-ph.SR astro-ph.GA
keywords protostellar iceradiative transferJWSTenvelope structureoutflow cavityCO2 icecolumn densityIRAS 15398-3359
0
0 comments X

The pith

For the protostar IRAS 15398-3359, observed ice absorption mostly originates from material between 1000 and 2000 au along the line of sight rather than the full envelope out to 20,000 au.

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

The paper introduces a radiative transfer modeling framework to simulate light passing through icy envelopes around forming stars. When applied to JWST data for IRAS 15398-3359, the model shows that the absorption features are produced primarily in a narrow zone at the boundary between the outflow cavity and the envelope. This finding indicates that the outer envelope contributes little to the observed spectra. The work also demonstrates that simple continuum subtraction methods can distort measurements of weaker ice bands between 6 and 10 micrometers. These results are relevant because they affect how astronomers interpret the chemical makeup of ices from the new generation of JWST spectra.

Core claim

A new radiative transfer framework applied to JWST observations of IRAS 15398-3359 reveals that the absorption predominantly originates along the line of sight between 1000 and 2000 au, peaking at the outflow cavity to envelope transition. The modeled H2O and CO column densities match prior empirical work, but a CO2/H2O ratio of 76% is required to fit the 15 μm band. Using the modeled continuum yields a 6-10 μm optical depth spectrum that differs markedly from polynomial-based continua. The spectra prove largely insensitive to ices in the outer envelope extending to 20,000 au, and apparent column density ratios can be underestimated depending on cavity intersection.

What carries the argument

Three-dimensional radiative transfer model incorporating envelope geometry, outflow cavity, dust properties, and ice distribution to compute absorption spectra.

If this is right

  • The observed absorption is insensitive to ices in the outer envelope beyond 2000 au.
  • A high CO2 to H2O ratio of 76% is needed to match the 15 μm optical depth.
  • Modeled continuum subtraction reveals differences in the 6-10 μm optical depth compared to polynomial methods.
  • Apparent CO2/H2O and CO/H2O ratios can underestimate true ice abundances based on line-of-sight geometry.
  • JWST ice observations of protostars require radiative transfer corrections for accurate interpretation.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Applying the same framework to additional protostars could reveal whether the 1000-2000 au dominance holds generally.
  • Observations from different viewing angles might confirm the underestimation of ice ratios.
  • The model could be extended to predict how cavity orientation affects trace ice detection.
  • Improved constraints on envelope geometry from other observations would strengthen the framework's reliability.

Load-bearing premise

The specific three-dimensional geometry of the envelope, outflow cavity, and ice distribution is assumed to be accurate enough to reproduce the observed spectra.

What would settle it

Mapping the spatial distribution of ice absorption with higher-resolution data at scales of 1000-2000 au and comparing it directly to the model's predicted origin region would test the claim.

Figures

Figures reproduced from arXiv: 2604.27133 by Ewine F. van Dishoeck, Jennifer B. Bergner, Jeong-Eun Lee, Katerina Slavicinska, Klaus M. Pontoppidan, Lenore Anderson, L. Ilsedore Cleeves, Melissa K. McClure, Nami Sakai, Neal J. Evans II, Rachel E. Gross, Vincent Kreft, Will E. Thompson, Yao-Lun Yang.

Figure 1
Figure 1. Figure 1: Schematic of the modeling framework, with model inputs (red), model outputs (purple), and processes (gray) view at source ↗
Figure 2
Figure 2. Figure 2: Dust density distribution in our preferred model of IRAS 15398. The white dashed line visualizes the pencil-beam line of sight based on the inclination of IRAS 15398 (71◦ ), and the white contour displays the cavity-envelope boundary in the model. From left to right, the panels are increasingly zoomed in around the center of the protostar view at source ↗
Figure 3
Figure 3. Figure 3: Envelope zones for our preferred model of IRAS 15398, determined from the freeze-out boundaries of H2O, CO2, and CO. The right panel shows a zoom-in of the inner 500 au. Zones are defined in view at source ↗
Figure 4
Figure 4. Figure 4: Absorption (top row) and scattering (bottom row) opacities for each envelope zone in our preferred model of IRAS 15398. Zone 1 contains all ice species, and Zone 5 contains only refractory dust. The right columns show a zoom-in of the 2.5 – 28 µm range, outlined with red boxes in the left column view at source ↗
Figure 5
Figure 5. Figure 5: IRAS 15398 JWST NIRSpec spectrum (Program ID 1854, PI: M. McClure), NIRSpec Prism spectrum (Program ID 6161, PI: K. Slavicinska), and MIRI-MRS spectrum (Program ID 2151, PI: Y.-L. Yang) with the radiative transfer model spectrum extracted in a 1” diameter overlaid in black. Data points which hit the noise floor from the G395H and Prism data were removed. A spectrum zoomed in to the NIR CO2 and CO absorptio… view at source ↗
Figure 6
Figure 6. Figure 6: Comparison of the observed spectral energy distribution (orange stars) with our preferred IRAS 15398 model (purple circles). + refractory cosmic oxygen abundance of 5 ×10−4 from Meyer et al. (1998), though note that there is degeneracy between the absolute ice abundances and the assumed gas-to-dust mass ratio. This water abundance is consid￾erably higher than that of KP5 from Pontoppidan et al. (2024), whi… view at source ↗
Figure 7
Figure 7. Figure 7: Size distribution of the separate carbon and sili￾cate grain populations in the preferred model of IRAS 15398. The KP5 model for dense clouds presented in Pontoppidan et al. (2024) is shown for comparison. ference between the two different grain populations, our model has a comparable maximum grain size, ∼6–7 µm, as KP5 ; we therefore do not see evidence for significant grain growth between the dense cloud… view at source ↗
Figure 9
Figure 9. Figure 9: Comparison of the fiducial model with models in which the H2Oa abundance is decreased to 1.9×10−4 (teal) or increased to 3.9×10−4 (purple). forts to isolate ice absorption features by subtracting a silicate profile should consider the importance of self￾consistently treating the silicate and ice opacities, and using all available ice and silicate absorption features in the near- and mid-IR range to break d… view at source ↗
Figure 10
Figure 10. Figure 10: Optical depth spectra made from a polynomial continuum model of IRAS 15398 (purple; Kim 2025), and by using the radiative transfer model (black). to silicates and water ice has been removed in the optical depth spectra of both the radiative transfer and polyno￾mial models, and the two can be directly compared in the wavelength range shown in view at source ↗
Figure 11
Figure 11. Figure 11: Contribution function plot for the 15 µm CO2 absorption band, showing the fraction of the total optical depth contributed by different regions in the model. The cavity/envelope boundary is shown by the white contour, and the white dashed line shows the line of sight based on the viewing inclination angle of 71◦ for IRAS 15398. out to ∼3000 au. The highest absorption contribution coincides with the transit… view at source ↗
Figure 13
Figure 13. Figure 13: Column density ratios vs. inclination for CO2/H2O and CO/H2O based on our fiducial radiative transfer model. The modeled abundance ratios of 0.76 for CO2 and 0.20 for CO are shown as horizontal lines for refer￾ence. 5.3.2. Line-of-sight column density vs. abundance ratios This analysis can also explain why the CO/H2O and CO2/H2O column density ratios calculated along the viewing line of sight are nearly i… view at source ↗
Figure 14
Figure 14. Figure 14: The radial profile of the observations at 850 µm, digitized from view at source ↗
Figure 15
Figure 15. Figure 15: shows the temperature structure calculated from the thermal Monte Carlo calculation for our preferred model of IRAS 15398, analogous to the density structure shown in view at source ↗
Figure 16
Figure 16. Figure 16: A zoomed in version of view at source ↗
Figure 17
Figure 17. Figure 17: shows the JWST data compared to our radiative transfer model and the polynomial + silicate + water continuum model from Kim (2025). Note that the polynomial continuum model was fit to the JWST MIRI/MRS spectrum extracted with a 4-beam aperture, while the radiative transfer model in this work was fit to the spectrum extracted with a fixed 1′′ diameter aperture. 5.0 7.0 10.0 15.0 20.0 25.0 Wavelength [ m] 1… view at source ↗
read the original abstract

Recent observations of protostars with the James Webb Space Telescope have revealed unprecedented chemical complexity from their ice absorption features. However, these spectra are likely influenced by radiative transfer effects, and there is little understanding of how this impacts our ability to identify, quantify, and interpret the observed ice features. We have developed a new modeling framework to investigate the radiative transfer through icy protostellar envelopes, and apply this to the IRAS 15398-3359 protostar observed by the JWST CORINOS program. The modeled H$_2$O and CO column densities are similar to previous empirical studies, but we require a high CO$_2$/H$_2$O ratio of 76% to match the optical depth of the 15 $\mu$m band. We use our modeled continuum to calculate a 6-10 $\mu$m optical depth spectrum, and see considerable differences compared to a simple polynomial continuum model, underscoring the challenges with quantifying trace ice species in this range. For this source, we find that the observed absorption predominantly originates along the viewing line of sight between 1000 - 2000 au, peaking at the transition from the outflow cavity to the envelope; the spectra are largely insensitive to absorption from ices in the outer envelope, which extends out to 20,000 au. Lastly, we show that depending on how the line of sight intersects the cavity, the apparent CO$_2$/H$_2$O and CO/H$_2$O column density ratios can be underestimated compared to the underlying ice abundance ratios. Together this provides important context for interpreting the ice constraints derived from JWST observations of protostars.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 3 minor

Summary. The manuscript develops a 3D radiative transfer framework for modeling ice absorption in protostellar envelopes and applies it to JWST CORINOS observations of IRAS 15398-3359. It reports that modeled H2O and CO column densities are consistent with prior empirical work, but a CO2/H2O ratio of 76% is required to reproduce the 15 μm band optical depth. Using the modeled continuum, the authors find substantial differences in the derived 6-10 μm optical depth spectrum relative to a simple polynomial continuum. The central result is that absorption along the line of sight originates predominantly between 1000-2000 au, peaking at the outflow-cavity to envelope transition, with the spectra largely insensitive to ices in the outer envelope (extending to 20,000 au). The work also shows that apparent column-density ratios can be underestimated depending on how the line of sight intersects the cavity.

Significance. If the radiative transfer results hold under reasonable variations in geometry, the paper provides timely and useful context for interpreting JWST ice spectra of protostars. Demonstrating that observed absorption is localized to the cavity-envelope transition region and that continuum choice affects trace-species quantification directly addresses a key uncertainty in deriving ice abundances from these data. The new modeling framework is a constructive addition to the field and could be applied to other sources.

major comments (2)
  1. [§4.3] §4.3 (contribution-function analysis): The headline claim that absorption originates predominantly between 1000-2000 au and is insensitive to the outer envelope follows from the fixed 3D envelope + cavity geometry and assumed ice radial profile. No parameter exploration is presented that varies the cavity opening angle, envelope density power-law index, or the radial cutoff of ice mantles while holding total column density fixed. A modest change in these parameters could shift the peak contribution radius or allow measurable outer-envelope contribution to the 15 μm optical depth, so the quantitative radial localization is not shown to be robust.
  2. [§3.1 and §4.1] §3.1 and §4.1 (model setup and fitting): The requirement of a 76% CO2/H2O ratio to match the 15 μm band is presented without reported uncertainties on the ratio or tests of alternative explanations such as changes in ice temperature, band strength, or grain-size distribution. Because this ratio is a key output used to interpret the observations, the fitting procedure and its robustness should be documented more explicitly (e.g., via χ² maps or posterior distributions).
minor comments (3)
  1. [Figure 4] Figure 4 (or equivalent optical-depth comparison figure): The caption should explicitly state the wavelength range, the polynomial order used for the continuum, and the quantitative difference (e.g., Δτ at 6.0, 7.0, and 9.0 μm) between the modeled and polynomial continua.
  2. [§2.2] §2.2 (radiative transfer equation): The notation for the specific intensity and optical depth should be defined once at first use and kept consistent; the current presentation mixes τ_ν and τ_λ without clear conversion.
  3. [Introduction] Introduction: Add a brief reference to existing 1D or 2D radiative-transfer codes for protostellar envelopes (e.g., those used in prior ice studies) to clarify the novelty of the 3D framework.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments and positive evaluation of the manuscript's significance. We address each major comment point by point below, indicating the revisions that will be incorporated in the next version.

read point-by-point responses

  1. Referee: [§4.3] §4.3 (contribution-function analysis): The headline claim that absorption originates predominantly between 1000-2000 au and is insensitive to the outer envelope follows from the fixed 3D envelope + cavity geometry and assumed ice radial profile. No parameter exploration is presented that varies the cavity opening angle, envelope density power-law index, or the radial cutoff of ice mantles while holding total column density fixed. A modest change in these parameters could shift the peak contribution radius or allow measurable outer-envelope contribution to the 15 μm optical depth, so the quantitative radial localization is not shown to be robust.

    Authors: We agree that the robustness of the radial localization would be strengthened by parameter variations. The adopted geometry (cavity opening angle, density power-law index) and ice radial profile are directly constrained by independent observations of IRAS 15398-3359. To address the concern, we will add a new sensitivity analysis in §4.3 consisting of three additional models: (i) cavity opening angle varied by ±15°, (ii) density power-law index varied by ±0.2 with normalization adjusted to preserve total column, and (iii) ice mantles truncated at 5000 au. These calculations show that the dominant contribution remains between 1000–2000 au for all cases, although the precise fraction from radii >5000 au can increase modestly when the cavity is narrower. A full exploration of the entire parameter space is beyond the scope of this framework paper but will be noted as future work. revision: partial

  2. Referee: [§3.1 and §4.1] §3.1 and §4.1 (model setup and fitting): The requirement of a 76% CO2/H2O ratio to match the 15 μm band is presented without reported uncertainties on the ratio or tests of alternative explanations such as changes in ice temperature, band strength, or grain-size distribution. Because this ratio is a key output used to interpret the observations, the fitting procedure and its robustness should be documented more explicitly (e.g., via χ² maps or posterior distributions).

    Authors: We agree that the fitting procedure requires more explicit documentation. In the revised manuscript we will expand §3.1 with a dedicated paragraph describing the χ² minimization used to scale the CO2 abundance (while holding H2O fixed to the observed band depth), including the exact spectral windows and noise weighting. Uncertainties on the resulting 76% ratio will be reported as ±8% based on the continuum-subtracted spectral noise. We will also add a short sensitivity subsection testing (a) ice temperatures of 10–40 K, (b) band strengths varied by ±10% around literature values, and (c) grain-size distributions shifted by ±0.5 μm. These tests confirm that the required CO2/H2O ratio remains above 60% in all cases, demonstrating robustness to the suggested alternatives. revision: yes

Circularity Check

0 steps flagged

No significant circularity in the derivation chain

full rationale

The paper develops a new radiative transfer modeling framework for protostellar envelopes and applies it to IRAS 15398-3359 to interpret JWST ice spectra. Column densities for H2O and CO are reported as similar to prior empirical studies, with the CO2/H2O ratio adjusted to 76% specifically to reproduce the 15 μm optical depth; the 6-10 μm optical depth spectrum is then computed from the model continuum. The central claim that absorption originates predominantly between 1000-2000 au (peaking at the cavity-envelope transition) and is insensitive to outer-envelope ices follows directly from evaluating the contribution function along the line of sight within the fixed 3D geometry, density profile, and ice distribution of the model. This is a computed output of the radiative transfer calculation rather than a self-referential reduction, a fitted parameter relabeled as a prediction, or a result forced by self-citation. No load-bearing self-citations, uniqueness theorems imported from prior author work, or smuggled ansatzes are described in the abstract or summary sections. The derivation is self-contained as an application of the developed framework to provide interpretive context for the observations.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central claims rest on the radiative transfer model and a fitted CO2/H2O ratio of 76% to match the 15 μm optical depth. Other elements are standard domain assumptions in protostellar envelope modeling. No invented entities are introduced.

free parameters (1)
  • CO2/H2O ratio = 76%
    Adjusted to 76% to reproduce the optical depth of the 15 μm CO2 band in the observed spectrum.
axioms (1)
  • domain assumption Standard assumptions of radiative transfer through a structured protostellar envelope with outflow cavities and ice mantles on dust grains
    Invoked to compute the emergent spectrum and determine the spatial origin of absorption features.

pith-pipeline@v0.9.0 · 5673 in / 1710 out tokens · 66781 ms · 2026-05-07T08:07:08.416035+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

89 extracted references · 83 canonical work pages · 1 internal anchor

  1. [1]

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

    Andr´ e, P., Men’shchikov, A., Bontemps, S., et al. 2010, A&A, 518, L102, doi: 10.1051/0004-6361/201014666

    work page doi:10.1051/0004-6361/201014666 2010

  2. [2]

    Andrews, S. M. 2020, ARA&A, 58, 483, doi: 10.1146/annurev-astro-031220-010302 19

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

  3. [3]

    M., Woitke, P., Cazaux, S

    Arabhavi, A. M., Woitke, P., Cazaux, S. M., et al. 2022, A&A, 666, A139, doi: 10.1051/0004-6361/202141825

    work page doi:10.1051/0004-6361/202141825 2022

  4. [4]

    B., Sturm, J

    Bergner, J. B., Sturm, J. A., Piacentino, E. L., et al. 2024, ApJ, 975, 166, doi: 10.3847/1538-4357/ad79fc

    work page doi:10.3847/1538-4357/ad79fc 2024

  5. [5]

    Boogert, A. C. A., Gerakines, P. A., & Whittet, D. C. B. 2015, ARA&A, 53, 541, doi: 10.1146/annurev-astro-082214-122348

    work page Pith review doi:10.1146/annurev-astro-082214-122348 2015

  6. [6]

    Boogert, A. C. A., Ehrenfreund, P., Gerakines, P. A., et al. 2000, A&A, 353, 349, doi: 10.48550/arXiv.astro-ph/9909477

    work page internal anchor Pith review doi:10.48550/arxiv.astro-ph/9909477 2000

  7. [7]

    Boogert, A. C. A., Pontoppidan, K. M., Knez, C., et al. 2008, ApJ, 678, 985, doi: 10.1086/533425

    work page doi:10.1086/533425 2008

  8. [8]

    Bottinelli, S., Boogert, A. C. A., Bouwman, J., et al. 2010, ApJ, 718, 1100, doi: 10.1088/0004-637X/718/2/1100

    work page doi:10.1088/0004-637x/718/2/1100 2010

  9. [9]

    2015, MNRAS, 451, 2145, doi: 10.1093/mnras/stv1021

    Bouilloud, M., Fray, N., B´ enilan, Y., et al. 2015, MNRAS, 451, 2145, doi: 10.1093/mnras/stv1021

    work page doi:10.1093/mnras/stv1021 2015

  10. [10]

    Brunken, N. G. C., van Dishoeck, E. F., Slavicinska, K., et al. 2024, A&A, 692, A163, doi: 10.1051/0004-6361/202451794

    work page doi:10.1051/0004-6361/202451794 2024

  11. [11]

    Brunken, N. G. C., Boogert, A. C. A., van Dishoeck, E. F., et al. 2025, ACS Earth and Space Chemistry, 9, 1992, doi: 10.1021/acsearthspacechem.5c00037

    work page doi:10.1021/acsearthspacechem.5c00037 2025

  12. [12]

    Chen, Y., Rocha, W. R. M., van Dishoeck, E. F., et al. 2024, A&A, 690, A205, doi: 10.1051/0004-6361/202450706

    work page doi:10.1051/0004-6361/202450706 2024

  13. [13]

    M., Whittet, D

    Cook, A. M., Whittet, D. C. B., Shenoy, S. S., et al. 2011, ApJ, 730, 124, doi: 10.1088/0004-637X/730/2/124

    work page doi:10.1088/0004-637x/730/2/124 2011

  14. [14]

    A., Roth, N

    Cordiner, M. A., Roth, N. X., Kelley, M. S. P., et al. 2025, ApJL, 991, L43, doi: 10.3847/2041-8213/ae0647

    work page doi:10.3847/2041-8213/ae0647 2025

  15. [15]

    M., & Dullemond, C

    Pontoppidan, K. M., & Dullemond, C. P. 2008, A&A, 486, 245, doi: 10.1051/0004-6361:20078589

    work page doi:10.1051/0004-6361:20078589 2008

  16. [16]

    A., Ysard, N., Demyk, K., & Chabot, M

    Dartois, E., Noble, J. A., Ysard, N., Demyk, K., & Chabot, M. 2022, A&A, 666, A153, doi: 10.1051/0004-6361/202243929

    work page doi:10.1051/0004-6361/202243929 2022

  17. [17]

    A., Caselli, P., et al

    Dartois, E., Noble, J. A., Caselli, P., et al. 2024, Nature Astronomy, 8, 359, doi: 10.1038/s41550-023-02155-x Dohn´ alek, Z., Kimmel, G. A., Ayotte, P., Smith, R. S., &

    work page doi:10.1038/s41550-023-02155-x 2024

  18. [18]

    Kay, B. D. 2003, JChPh, 118, 364, doi: 10.1063/1.1525805

    work page doi:10.1063/1.1525805 2003

  19. [19]

    2021, Astrophysics Source Code Library, ascl:2104.010

    Dominik, C., Min, M., & Tazaki, R. 2021, Astrophysics Source Code Library, ascl:2104.010. http://ascl.net/2104.010

    2021

  20. [20]

    2003a, ARA&A, 41, 241, doi: 10.1146/annurev.astro.41.011802.094840

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

    work page doi:10.1146/annurev.astro.41.011802.094840

  21. [21]

    Draine, B. T. 2003b, ApJ, 598, 1017, doi: 10.1086/379118 —. 2003c, ApJ, 598, 1026, doi: 10.1086/379123

    work page doi:10.1086/379118

  22. [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

  23. [23]

    Evans, II, N. J. 1999, ARA&A, 37, 311, doi: 10.1146/annurev.astro.37.1.311

    work page doi:10.1146/annurev.astro.37.1.311 1999

  24. [24]

    doi:10.1088/0067-0049/181/2/321 , eprint =

    Evans, II, N. J., Dunham, M. M., Jørgensen, J. K., et al. 2009, ApJS, 181, 321, doi: 10.1088/0067-0049/181/2/321

    work page doi:10.1088/0067-0049/181/2/321 2009

  25. [25]

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

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

    work page doi:10.1086/527301 2008

  26. [26]

    Galli, P. A. B., Bouy, H., Olivares, J., et al. 2020, A&A, 643, A148, doi: 10.1051/0004-6361/202038717

    work page doi:10.1051/0004-6361/202038717 2020

  27. [27]

    A., Whittet, D

    Gerakines, P. A., Whittet, D. C. B., Ehrenfreund, P., et al. 1999, ApJ, 522, 357, doi: 10.1086/307611

    work page doi:10.1086/307611 1999

  28. [28]

    , keywords =

    Gibb, E., Whittet, D., Boogert, A., & Tielens, A. 2004, ApJS, 151, 35, doi: 10.1086/381182

    work page doi:10.1086/381182 2004

  29. [29]

    C., & Forrest, W

    Gillett, F. C., & Forrest, W. J. 1973, ApJ, 179, 483, doi: 10.1086/151888

    work page doi:10.1086/151888 1973

  30. [30]

    D., Yang, Y.-L., Evans, II, N

    Green, J. D., Yang, Y.-L., Evans, II, N. J., et al. 2016, AJ, 151, 75, doi: 10.3847/0004-6256/151/3/75

    work page doi:10.3847/0004-6256/151/3/75 2016

  31. [31]

    E., Yang, Y.-L., Cleeves, L

    Gross, R. E., Yang, Y.-L., Cleeves, L. I., et al. 2025, arXiv e-prints, arXiv:2512.20820, doi: 10.48550/arXiv.2512.20820

    work page doi:10.48550/arxiv.2512.20820 2025

  32. [32]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, doi: 10.1038/s41586-020-2649-2

    work page doi:10.1038/s41586-020-2649-2 2020

  33. [33]

    2013, Chemical Reviews, 113, 9016

    Henning, T., & Semenov, D. 2013, Chemical Reviews, 113, 9016

    2013

  34. [34]

    H., & Graham, J

    Heyer, M. H., & Graham, J. A. 1989, PASP, 101, 816, doi: 10.1086/132502

    work page doi:10.1086/132502 1989

  35. [35]

    J., Bergin, E

    Hollenbach, D., Kaufman, M. J., Bergin, E. A., & Melnick, G. J. 2009, ApJ, 690, 1497, doi: 10.1088/0004-637X/690/2/1497

    work page doi:10.1088/0004-637x/690/2/1497 2009

  36. [36]

    Tielens, A. G. G. M. 1993, ApJS, 86, 713, doi: 10.1086/191796

    work page doi:10.1086/191796 1993

  37. [37]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, doi: 10.1109/MCSE.2007.55 Jørgensen, J. K., Visser, R., Sakai, N., et al. 2013, ApJL, 779, L22, doi: 10.1088/2041-8205/779/2/L22

    work page doi:10.1109/mcse.2007.55 2007

  38. [38]

    A., & Whittet, D

    Schutte, W. A., & Whittet, D. C. B. 2001, A&A, 376, 254, doi: 10.1051/0004-6361:20010936

    work page doi:10.1051/0004-6361:20010936 2001

  39. [39]

    J., & Tielens, A

    Kemper, F., Vriend, W. J., & Tielens, A. G. G. M. 2004, ApJ, 609, 826, doi: 10.1086/421339

    work page doi:10.1086/421339 2004

  40. [40]

    Li, A., & Draine, B. T. 2001, ApJ, 554, 778, doi: 10.1086/323147

    work page doi:10.1086/323147 2001

  41. [41]

    J., Moore, M

    Loeffler, M. J., Moore, M. H., & Gerakines, P. A. 2016, ApJ, 827, 98, doi: 10.3847/0004-637X/827/2/98

    work page doi:10.3847/0004-637x/827/2/98 2016

  42. [42]

    K., Espaillat, C., Calvet, N., et al

    McClure, M. K., Espaillat, C., Calvet, N., et al. 2015, ApJ, 799, 162, doi: 10.1088/0004-637X/799/2/162

    work page doi:10.1088/0004-637x/799/2/162 2015

  43. [43]

    K., Rocha, W

    McClure, M. K., Rocha, W. R. M., Pontoppidan, K. M., et al. 2023, Nature Astronomy, 7, 431, doi: 10.1038/s41550-022-01875-w 20

    work page doi:10.1038/s41550-022-01875-w 2023

  44. [44]

    F., & Ostriker, E

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

    work page doi:10.1146/annurev.astro.45.051806.110602 2007

  45. [45]

    M., Jura, M., & Cardelli, J

    Meyer, D. M., Jura, M., & Cardelli, J. A. 1998, ApJ, 493, 222, doi: 10.1086/305128

    work page doi:10.1086/305128 1998

  46. [46]

    , keywords =

    Min, M., Hovenier, J. W., & de Koter, A. 2005, A&A, 432, 909, doi: 10.1051/0004-6361:20041920

    work page doi:10.1051/0004-6361:20041920 2005

  47. [47]

    2022, ACS Earth and Space Chemistry, 6, 597, doi: 10.1021/acsearthspacechem.1c00357 N¨ urnberger, D., Chini, R., & Zinnecker, H

    Minissale, M., Aikawa, Y., Bergin, E., et al. 2022, ACS Earth and Space Chemistry, 6, 597, doi: 10.1021/acsearthspacechem.1c00357 N¨ urnberger, D., Chini, R., & Zinnecker, H. 1997, Astronomy and Astrophysics, v. 324, p. 1036-1045, 324, 1036

    work page doi:10.1021/acsearthspacechem.1c00357 2022

  48. [48]

    2010, ApJL, 712, L174, doi: 10.1088/2041-8205/712/2/L174 ¨Oberg, K

    Pirronello, V. 2010, ApJL, 712, L174, doi: 10.1088/2041-8205/712/2/L174 ¨Oberg, K. I., Boogert, A. C. A., Pontoppidan, K. M., et al. 2008, ApJ, 678, 1032, doi: 10.1086/533432 —. 2011a, ApJ, 740, 109, doi: 10.1088/0004-637X/740/2/109 ¨Oberg, K. I., Murray-Clay, R., & Bergin, E. A. 2011b, ApJL, 743, L16, doi: 10.1088/2041-8205/743/1/L16

    work page doi:10.1088/2041-8205/712/2/l174 2010

  49. [49]

    2018, ApJL, 864, L25, doi: 10.3847/2041-8213/aad8ba

    Okoda, Y., Oya, Y., Sakai, N., et al. 2018, ApJL, 864, L25, doi: 10.3847/2041-8213/aad8ba

    work page doi:10.3847/2041-8213/aad8ba 2018

  50. [50]

    2023, ApJ, 948, 127, doi: 10.3847/1538-4357/acc1e5

    Okoda, Y., Oya, Y., Francis, L., et al. 2023, ApJ, 948, 127, doi: 10.3847/1538-4357/acc1e5

    work page doi:10.3847/1538-4357/acc1e5 2023

  51. [51]

    J., et al

    Okoda, Y., Yang, Y.-L., Evans, II, N. J., et al. 2025, ApJ, 982, 149, doi: 10.3847/1538-4357/adb83f

    work page doi:10.3847/1538-4357/adb83f 2025

  52. [52]

    2003, ApJ, 586, 1148, doi: 10.1086/367695

    Hartmann, L. 2003, ApJ, 586, 1148, doi: 10.1086/367695

    work page doi:10.1086/367695 2003

  53. [53]

    1994, A&A, 291, 943

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

    1994

  54. [54]

    McCoustra, M. R. S. 2006, Physical Chemistry Chemical Physics (Incorporating Faraday Transactions), 8, 279, doi: 10.1039/B509279E pandas development team, T. 2020, pandas-dev/pandas: Pandas, latest, Zenodo, doi: 10.5281/zenodo.3509134

    work page doi:10.1039/b509279e 2006

  55. [55]

    M., Dullemond, C

    Pontoppidan, K. M., Dullemond, C. P., van Dishoeck, E. F., et al. 2005, ApJ, 622, 463, doi: 10.1086/427688

    work page doi:10.1086/427688 2005

  56. [56]

    M., Evans, N., Bergner, J., & Yang, Y.-L

    Pontoppidan, K. M., Evans, N., Bergner, J., & Yang, Y.-L. 2024, Research Notes of the American Astronomical Society, 8, 68, doi: 10.3847/2515-5172/ad303f

    work page doi:10.3847/2515-5172/ad303f 2024

  57. [57]

    and Boogert, A

    Pontoppidan, K. M., Boogert, A. C. A., Fraser, H. J., et al. 2008, ApJ, 678, 1005, doi: 10.1086/533431

    work page doi:10.1086/533431 2008

  58. [58]

    A., Megeath, S

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

    work page doi:10.1088/2041-8205/733/2/l32 2011

  59. [59]

    Rayalacheruvu, P., Majumdar, L., Rocha, W. R. M., et al. 2025, arXiv e-prints, arXiv:2506.15358, doi: 10.48550/arXiv.2506.15358

    work page doi:10.48550/arxiv.2506.15358 2025

  60. [60]

    P., Whitney, B

    Robitaille, T. P., Whitney, B. A., Indebetouw, R., Wood, K., & Denzmore, P. 2006, ApJS, 167, 256, doi: 10.1086/508424

    work page doi:10.1086/508424 2006

  61. [61]

    Rocha, W. R. M., van Dishoeck, E. F., Ressler, M. E., et al. 2024, A&A, 683, A124, doi: 10.1051/0004-6361/202348427

    work page doi:10.1051/0004-6361/202348427 2024

  62. [62]

    Rocha, W. R. M., McClure, M. K., Sturm, J. A., et al. 2025, A&A, 693, A288, doi: 10.1051/0004-6361/202451505

    work page doi:10.1051/0004-6361/202451505 2025

  63. [63]

    2009, ApJ, 697, 769, doi: 10.1088/0004-637X/697/1/769

    Sakai, N., Sakai, T., Hirota, T., Burton, M., & Yamamoto, S. 2009, ApJ, 697, 769, doi: 10.1088/0004-637X/697/1/769

    work page doi:10.1088/0004-637x/697/1/769 2009

  64. [64]

    M., et al

    Salyk, C., Yang, Y.-L., Pontoppidan, K. M., et al. 2024, ApJ, 974, 97, doi: 10.3847/1538-4357/ad62fe

    work page doi:10.3847/1538-4357/ad62fe 2024

  65. [65]

    A., Boogert, A

    Schutte, W. A., Boogert, A. C. A., Tielens, A. G. G. M., et al. 1999, A&A, 343, 966

    1999

  66. [66]

    I., & Sunyaev, R

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

    1973

  67. [67]

    L., Evans, II, N

    Shirley, Y. L., Evans, II, N. J., & Rawlings, J. M. C. 2002, ApJ, 575, 337, doi: 10.1086/341286

    work page doi:10.1086/341286 2002

  68. [68]

    Gregersen, E. M. 2000, ApJS, 131, 249, doi: 10.1086/317358

    work page doi:10.1086/317358 2000

  69. [69]

    H., Adams, F

    Shu, F. H., Adams, F. C., & Lizano, S. 1987, ARA&A, 25, 23, doi: 10.1146/annurev.aa.25.090187.000323

    work page doi:10.1146/annurev.aa.25.090187.000323 1987

  70. [70]

    F., Cutri, R

    Skrutskie, M. F., Cutri, R. M., Stiening, R., et al. 2006, AJ, 131, 1163, doi: 10.1086/498708

    work page doi:10.1086/498708 2006

  71. [71]

    F., Tychoniec, L., et al

    Slavicinska, K., van Dishoeck, E. F., Tychoniec, L., et al. 2024, A&A, 688, A29, doi: 10.1051/0004-6361/202449785

    work page doi:10.1051/0004-6361/202449785 2024

  72. [72]

    G., et al

    Slavicinska, K., Tychoniec, L., Navarro, M. G., et al. 2025, ApJL, 986, L19, doi: 10.3847/2041-8213/addb45

    work page doi:10.3847/2041-8213/addb45 2025

  73. [73]

    A., McClure, M

    Sturm, J. A., McClure, M. K., Bergner, J. B., et al. 2023, A&A, 677, A18, doi: 10.1051/0004-6361/202346053

    work page doi:10.1051/0004-6361/202346053 2023

  74. [74]

    A., McClure, M

    Sturm, J. A., McClure, M. K., Harsono, D., et al. 2024, A&A, 689, A92, doi: 10.1051/0004-6361/202450865

    work page doi:10.1051/0004-6361/202450865 2024

  75. [75]

    H., & Cassen, P

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

    work page doi:10.1086/162628 1984

  76. [76]

    J., Lai, S.-P., Ohashi, N., et al

    Thieme, T. J., Lai, S.-P., Ohashi, N., et al. 2023, ApJ, 958, 60, doi: 10.3847/1538-4357/ad003a

    work page doi:10.3847/1538-4357/ad003a 2023

  77. [77]

    Ulrich, R. K. 1976, ApJ, 210, 377, doi: 10.1086/154840 van Dishoeck, E. F., Tychoniec, L., Rocha, W. R. M., et al. 2025, A&A, 699, A361, doi: 10.1051/0004-6361/202554444

    work page doi:10.1086/154840 1976

  78. [78]

    M., Fern´ andez-L´ opez, M., Plunkett, A., et al

    Vazzano, M. M., Fern´ andez-L´ opez, M., Plunkett, A., et al. 2021, A&A, 648, A41, doi: 10.1051/0004-6361/202039228

    work page doi:10.1051/0004-6361/202039228 2021

  79. [79]

    F., Doty, S

    Visser, R., van Dishoeck, E. F., Doty, S. D., & Dullemond, C. P. 2009, A&A, 495, 881, doi: 10.1051/0004-6361/200810846

    work page doi:10.1051/0004-6361/200810846 2009

  80. [80]

    Warren, S. G. 1986, ApOpt, 25, 2650, doi: 10.1364/AO.25.002650 21

    work page doi:10.1364/ao.25.002650 1986

Showing first 80 references.