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REVIEW 4 major objections 6 minor 56 references

Solid and Gaseous Methane in IRAS 23385+6053 as seen with Open JWST Data

T0 review · 4 major / 6 minor · reviewed 2026-08-11 · deepseek-v4-flash

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Pith's one-line read The 7.7 µm band toward IRAS 23385+6053 is a superposition of solid methane absorption and warm gaseous methane emission, fit simultaneously with open JWST MIRI/MRS data.

desk verdict A careful and honest lab-plus-JWST analysis worth refereeing, but the gas-phase CH4 column rests on an unquantified 2.3σ detection and a threshold-defined emitting area. read the letter →

arxiv 2412.17028 v1 pith:FXPA7EKB submitted 2024-12-22 astro-ph.GA

Ruslan Nakibov , Varvara Karteyeva , Igor Petrashkevich , Maksim Ozhiganov , Mikhail Medvedev , Anton Vasyunin This is my paper · ORCID
classification astro-ph.GA
keywords methaneicegaseousIRAS23385+6053JWSTMIRI/MRSinterstellaricesinfraredspectroscopyprotostarastrochemistry
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 reinterprets the 7.7 µm band toward the high-mass star-forming region IRAS 23385+6053, a feature usually attributed to methane ice alone. Using public JWST MIRI/MRS spectra, the authors argue the band is actually a wide solid-state absorption feature of methane ice overlapped by sharp emission lines from warm gaseous methane. They report the first simultaneous quantification of both phases in this source: gas at temperature 103 K, column density 0.78 × $10^{17}$ $cm^{-2}$, and emitting radius 2940 au, plus solid methane with total column density 3.99 × $10^{17}$ $cm^{-2}$. The ice is best reproduced by laboratory mixtures of CH4:CO2 = 1:5 at 27.4 K and CH4:H2O = 1:10 at 8.4 K, implying that methane ice in this object is predominantly carbon-dioxide-rich rather than water-rich. A residual near 1283–1297 $cm^{-1}$ is tentatively assigned to nitrous oxide in various ice environments.

What carries the argument

The band decomposition rests on a two-step fitting procedure. First, an LTE slab emission model built from the TheoReTS methane line list and partition function is fit to the flux spectrum after masking the ice continuum; the emitting area is fixed from the flux map using a S/N = 3 aperture, and temperature and column density come from χ² minimization with confidence regions from Δχ² maps. Then the solid-state part is fit in optical depth space with a linear combination of laboratory spectra of CH4-bearing ices made on the ISEAge setup — CH4:CO2 = 1:5 and CH4:H2O = 1:10 deposited at 6.7 K and warmed at 0.5 K per minute — together with OCN⁻, CH3CH2OH:H2O, and SO2:CH3OH reference spectra. The laboratory CH4:CO2 mixture uniquely reproduces the doublet width and both wings, and that match carries the CO2-rich conclusion.

What would settle it

Take a JWST MIRI/MRS spectrum of the 3.3 µm ν3 methane band toward the same 1.2 arcsec aperture: the gas-phase interpretation predicts an emission feature at the same temperature and column density, while a solid-state origin for the 1306 $cm^{-1}$ feature would show a different or absent 3.3 µm feature.

Watch

Extended reading notes

Core claim

The central claim is that the resolved doublet structure of the 7.58–7.8 µm methane ν4 deformation band in IRAS 23385+6053 is not a single ice feature. The sharp component at 1306 $cm^{-1}$ coincides with a ν4 gaseous methane transition and is modeled with an LTE slab emission model, while the broad wings are solid methane in a CO2-dominated matrix with a smaller water-rich component. The best-fit gas parameters are R = 2940 au, T = 103(+13/-11) K, and N = 0.78(+6.18/-0.64) × $10^{17}$ $cm^{-2}$; the solid methane column densities are 2.97 × $10^{17}$ $cm^{-2}$ in CH4:CO2 = 1:5 at 27.4 K and 1.02 × $10^{17}$ $cm^{-2}$ in CH4:H2O = 1:10 at 8.4 K, for a total solid column of 3.99 × $10^{17}$ $cm^{-2}$. The authors conclude that methane ice is mostly surrounded by CO2 rather than H2O, contrasting with the water-methane mixtures commonly used in previous literature.

Load-bearing premise

The whole gas-ice decomposition hangs on the sharp feature near 1306 $cm^{-1}$ being real gaseous methane emission; if it is instead a solid-state band, a noise fluctuation, or a residual continuum artifact, the gas parameters and the phase split collapse.

Editorial extensions

If this is right

  • With the gas-phase contribution removed, the residual 7.7 µm band is a single broad ice absorption that can be described by CH4:CO2 = 1:5 at 27.4 K plus CH4:H2O = 1:10 at 8.4 K, so solid methane toward this source is predominantly in a CO2-rich rather than water-rich environment.
  • The total solid CH4 column density of 3.99 × 10^17 cm^-2 gives Nice(CH4)/Nice(H2O) ≈ 2.44%, consistent with the earlier estimate of 2.72%, meaning the new decomposition preserves the overall methane abundance while changing its phase split.
  • Gaseous methane is spatially offset from the continuum peak and is present only near the most massive source, implying the emitting gas sits at the edge of the accretion disk or in the envelope rather than in the cold core.
  • If this doublet structure appears in other JWST spectra, the same two-step procedure offers a way to separate gas and ice methane columns without assuming the whole ν4 feature is solid-state.
  • The unassigned 1283–1297 cm^-1 residual is tentatively attributed to N2O in various ice matrices, making IRAS 23385+6053 a new candidate for interstellar nitrous oxide.

Reading between the lines

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

  • If the decomposition holds, the same doublet morphology in other protostellar MIRI/MRS spectra could serve as a general diagnostic for separating warm methane gas from methane ice, and the CO2-dominated environment would point to methane formation or processing in CO2-rich mantles rather than water-rich ones.
  • The laboratory result that a N2O:CO2 = 1:20 mixture shifts the N2O feature by 14.4 cm^-1 provides a diagnostic for identifying N2O in CO2-rich ices; future JWST observations of the stronger 4.5 µm N2O band would turn the tentative 7.7 µm detection into a secure one.
  • Because the gas-phase column density has very asymmetric error bars (0.78 +6.18/-0.64 × 10^17 cm^-2), the gas-to-ice methane ratio is not yet tightly constrained; a higher-S/N observation of the same source would make that ratio a useful probe of methane desorption and warm carbon-chain chemistry.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 6 minor

Summary. The paper analyzes the 7.7 μm region of the JWST MIRI/MRS spectrum of the high-mass star-forming region IRAS 23385+6053. The authors interpret the 7.58–7.8 μm band as a superposition of broad solid methane absorption and sharp gaseous methane emission. Using an LTE slab model with an external line list (TheoReTS) they derive gas parameters R = 2940 au, T = 103(+13/-11) K, N = 0.78(+6.18/-0.64) × 10^17 cm^-2, and using new laboratory ice spectra (ISEAge) plus literature data they derive solid methane column densities for CH4:CO2 = 1:5 at 27.4 K and CH4:H2O = 1:10 at 8.4 K, with a total ice column of 3.99 × 10^17 cm^-2. The paper also tentatively assigns a residual to N2O in various ice environments.

Significance. If the gas-phase detection and the gas–ice decomposition are secure, this would be the first simultaneous quantification of gaseous and solid methane toward IRAS 23385+6053, with implications for methane partitioning and for methane ice environments (favoring CO2-rich rather than water-rich mantles). The paper has clear strengths: it uses publicly available JWST data, combines an external spectroscopic line list with new laboratory measurements, and makes an explicit effort to treat residuals statistically with Anderson–Darling tests. However, the central gas detection is statistically fragile, and the current presentation does not provide an integrated detection significance or a robustness analysis of the continuum subtraction, so the central claim is not yet fully supported.

major comments (4)
  1. [Section 5] The gaseous methane detection rests on single-pixel S/N values ≤ 2.3, and the emitting area is defined by adopting an S/N threshold of 3, but no integrated detection significance is reported for the 1306 cm^-1 feature or for the full multi-line fit. Because the subsequent gas–ice decomposition depends on the reality of this emission, please compute and report the S/N after aperture integration over the chosen region, and the detection significance from the full spectral fit. If the integrated feature is not significant at the adopted threshold, the gas detection and the derived R, T, and N values are not secure.
  2. [Equation (1) and Section 6] Equation (1) constrains only the product S·N, and the paper separates S from N by thresholding the single-pixel S/N map. The uncertainty in S is not propagated into the reported N = 0.78(+6.18/-0.64) × 10^17 cm^-2, whose upper error bar is almost an order of magnitude larger than the central value. Please quantify the uncertainty on S, propagate it properly into N and T, and show confidence contours for the parameters (e.g., Δχ² maps in the S–N plane).
  3. [Section 5, continuum subtraction] The ice continuum is estimated by LOESS smoothing with a 20-point window after masking 'prominent gaseous features and heavy outliers of unknown origin'. This procedure can in principle introduce or suppress narrow residuals at the gas line positions. Please test the robustness of the 1306 cm^-1 feature and the derived gas parameters against the choice of smoothing window and mask selection, or alternatively fit the gas, ice, and continuum simultaneously. Without such a test, the sharp 1306 cm^-1 feature may be a continuum artifact rather than methane emission.
  4. [Section 6 and Table 1] The conclusion that solid methane is predominantly in a CO2-rich environment (CH4:CO2 = 1:5) rather than a water-rich environment rests on a restricted library of laboratory mixtures: only CH4:CO2 = 1:5 and CH4:H2O = 1:10, deposited at 6.7 K and warmed at 0.5 K/min, plus literature spectra. Please justify the choice of these specific ratios and temperatures, or test additional compositions (e.g., CH4:CO2 at other ratios, CH4:NH3, or different warm-up rates) to show that the CO2 dominance is not an artifact of the limited library.
minor comments (6)
  1. [Table 1] The band strengths for CH4:CO2 and CH4:H2O are listed as 'This work', but the derivation of these band strengths is not described in the main text; please add a brief description or a reference to the follow-up paper.
  2. [Figure 1 caption] The red circle and red cross in Figure 1 are not defined in the caption; please explain that they indicate the methane-emitting area and the gas emission peak, respectively.
  3. [Abstract and Introduction] The phrase 'for the first time gaseous and solid methane were analyzed simultaneously' should be qualified relative to Rocha et al. (2024), who already modeled the ice component toward this source; please clarify that the new contribution is the simultaneous treatment and the gas-phase detection.
  4. [Section 5] The text uses the symbol S both for the emitting area in Equation (1) and for signal-to-noise ratio in the S/N discussion; please use a distinct symbol (e.g., A) for the area to avoid ambiguity.
  5. [Section 5] The phrase 'Plank’s law' should be corrected to 'Planck’s law'.
  6. [Appendix A] The Anderson–Darling filtering uses α = 12% and 10% for the best fit and confidence regions, respectively; please state whether these thresholds are fixed a priori or chosen to obtain the reported fit, and how the results change with modest variations of α.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the gas-phase model uses the external TheoReTS line list and the ice decomposition uses external ISEAge laboratory spectra, so the central claims are not defined into existence by the fitting procedure.

full rationale

The derivation chain is self-contained against external inputs. The gaseous methane parameters are obtained from an LTE slab model (Eq. 1) using the TheoReTS methane line list (Rey et al. 2013) and a chi-square fit (Eq. 2) to the observed spectrum, with the emitting area S estimated independently from flux intensity maps rather than from the spectral fit. The solid methane decomposition uses ISEAge laboratory spectra of CH4:CO2 and CH4:H2O mixtures with known column densities, and the derived ice column densities come from scaling these laboratory templates and measured band strengths to the observation. The iterative gas/ice separation, in which the ice continuum is estimated after masking gas features and the gas fit is subtracted before the ice fit, is a standard two-step spectral decomposition rather than a logical loop, because each component is anchored to independent data: an external line list for the gas and external laboratory ice spectra for the solid. Self-citations (Ozhiganov et al. 2024 for the ISEAge setup, and Karteyeva in prep. for future data release) are not load-bearing for the central result. The low single-pixel S/N of 2.3 for the 1306 cm^-1 feature and the S/N=3 aperture threshold are legitimate detection-significance concerns, but they are statistical weaknesses, not circular reductions; no equation in the paper makes a prediction equivalent to its input by construction.

Assumptions & free parameters 7 free parameters · 6 assumptions · 0 invented entities

The paper introduces no new physical entities. It uses fitted parameters for gas temperature, column density, emitting area, and ice mixture scale factors. The main load-bearing domain assumptions are the gas-plus-solid decomposition of the band and the representativeness of the chosen laboratory ice spectra.

free parameters (7)
  • Gaseous methane emitting area radius R = 2940 au (S = 2.7e7 au^2)
    Estimated from intensity maps after setting a significance threshold S/N = 3; this parameter directly sets the column density scale N = S*N / S.
  • Gaseous methane temperature T = 103(+13/-11) K
    Minimized in the chi-square fit over a 10-150 K grid using TheoReTS line lists.
  • Gaseous methane column density N = 0.78(+6.18/-0.64) x 10^17 cm^-2
    Derived from the fitted product S*N and the independently estimated area S; the uncertainty is dominated by the area determination.
  • Ice scale coefficients for CH4:CO2 and CH4:H2O = not individually quoted
    The linear combination coefficients are fitted to the observed optical depth and then converted to column densities via band strengths.
  • Ice temperatures for each mixture = T_CO2 = 27.4 K, T_H2O = 8.4 K
    Selected from the grid of laboratory warm-up spectra; these temperatures control the shape of the solid-state absorption profile.
  • Scale coefficients for OCN-, CH3CH2OH, and SO2 components = not quoted
    Added to the solid fit to describe the blue wing of the band, following Rocha et al. (2024); their amplitudes are free in the chi-square minimization.
  • Anderson-Darling p-value thresholds = alpha = 12% for best fit, 10% for confidence regions
    Fits are filtered by whether residuals pass a normality test at these hand-chosen significance levels, which affects which temperature combinations are accepted.
assumptions (6)
  • domain assumption The 7.7 micron doublet is a sum of solid methane absorption and gaseous methane emission.
    Stated at the start of Section 5; if the sharp features are not gas emission, the decomposition fails.
  • domain assumption Gaseous methane emission is described by an LTE slab model in the optically thin limit (Eq. 1), with linearization adding only 5% error.
    Adopted from Francis et al. (2024) and used to fit temperature and column density.
  • domain assumption The TheoReTS 80 K methane line list and partition function are accurate at the fitted temperature of 103 K.
    Used to generate the modeled emission spectrum; no alternate line list is tested.
  • standard math Residuals after subtraction follow a normal distribution, and the Anderson-Darling test is an appropriate filter.
    Assumed in the appendix to justify chi-square fitting and the residual normality filter.
  • domain assumption The laboratory spectra of CH4:CO2 and CH4:H2O mixtures, plus the Leiden Ice Database spectra for OCN-, ethanol, and SO2, are representative of the interstellar ice components along this line of sight.
    The solid fit is limited to this restricted set of laboratory mixtures; missing ice components would be absorbed into the fitted scales.
  • domain assumption Grain shape effects on the methane band are negligible because the band is more sensitive to molecular environment than to grain morphology.
    Invoked in Section 5 with a citation to Dartois et al. (2024) and Boogert et al. (1997b).

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Pith. "Pith review of Solid and Gaseous Methane in IRAS 23385+6053 as seen with Open JWST Data." pith.science (2026). https://pith.science/paper/FXPA7EKB

@misc{pith2026241217028,
  author       = {Pith},
  title        = {Pith review of: Solid and Gaseous Methane in IRAS 23385+6053 as seen with Open JWST Data},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/FXPA7EKB}},
  note         = {Machine review of arXiv:2412.17028}
}
abstract

We present a new description of the 7.7~$\mu$m region towards the high-mass star-forming region IRAS 23385+6053 taken from open James Webb Space Telescope Mid-Infrared Instrument Medium Resolution Spectrometer (JWST MIRI/MRS) data. This area is commonly attributed to the $\nu_4$ deformation mode of methane ice. For the first time gaseous and solid methane were analyzed simultaneously in IRAS 23385+6053. The band at 7.58--7.8 $\mu$m (1320--1280 cm$^{-1}$) is interpreted as a wide solid absorption methane feature overlapped by the sharp features of the methane emission. We report the detection of gaseous methane and estimate its emitting area radius~$R$, temperature~$T$ and column density~$N$ as $R=2940$~au, $T=103^{+13}_{-11}$~K, and $N=0.78_{+6.18}^{-0.64}\times10^{17}$~cm$^{-2}$, correspondingly. The ice content was analyzed with the laboratory spectra dataset of methane in different molecular environments obtained on the Ice Spectroscopy Experimental Aggregate (ISEAge). We were able to describe the wide feature of solid methane with the following laboratory spectra: CH$_4$~:~CO$_2$~=~1~:~5 (at $27.4^{+6.0}_{-10.8}$~K) and CH$_4$~:~H$_2$O~=~1~:~10 (at $8.4^{+16.4}_{-1.7}$~K) deposited at 6.7~K and warmed up at a rate of 0.5 K per minute. The derived column densities are $N_{\text{CH}_4}$(CO$_2$)~=~$2.97^{+0.37}_{-0.57}\times10^{17}$~cm$^{-2}$ and $N_{\text{CH}_4}$(H$_2$O)~=~$1.02^{+0.46}_{-0.27}\times10^{17}$~cm$^{-2}$. According to the best fit solid methane is mostly surrounded by CO$_2$ rather than H$_2$O. The residuals analysis reveals the unassigned region at 1283--1297~cm$^{-1}$ (7.71--7.79~$\mu$m) which is tentatively assigned to nitrous oxide (N$_2$O) in various environments.

Figures

Figures reproduced from arXiv: 2412.17028 by the authors.

Figure 1
Figure 1. Intensity maps of IRAS 23385+6053 at different wavelengths from the first, second, third and fourth channels of JWST MIRI-MRS spectrograph. The white circle shows 2.4′′ aperture from which the spectrum is extracted. Channels have different pixel size and map size depending on the observed wavelength. The young stellar objects are designated as A and B as in Francis et al. (2024). The white circle in the lower left c… view at source ↗
Figure 2
Figure 2. Panel a — The IRAS 23385+6053 spectrum after background subtraction. Global continuum is adopted from Rocha, W. R. M. et al. (2024). The inset shows a zoom in on the 7.7 µm region. Panel b — A processed spectrum after global, local continuum and a silicate profile subtraction. Panel c — Same as b, but with non-CH4 ices (OCN−, CH3CH2OH, SO2) subtracted following Rocha, W. R. M. et al. (2024) (2015) for peak position … view at source ↗
Figure 3
Figure 3. Top panel — the warm up of the mixture CH4 : CO2 = 1 : 5 from 6.7 K and 10 K with 0.5 K per minute; bottom panel — the warm up of the mixture CH4 : H2O = 1 : 10 from 6.7 K and 10 K with 0.5 K per minute. The CO2 mixture is seen to be strongly influenced by the deposition temperature. The dotted lines mark the peak positions for H2O mixtures observed before the warm up and serve as visual guides. a permanent electric… view at source ↗
Figures from the paper (3 more)
Figure 4
Figure 4. Figure 4: Best simulated gaseous methane spectrum plotted against observational data with subtracted ice continuum. A good agreement is shown between the prominent gaseous features and outlying sharp features in the observational spectrum. The subtraction of fitted gaseous featu…
Figure 5
Figure 5. Figure 5: Observational data fitted with ISEAge laboratory mixtures (solid lines), LIDA data (dashed/dotted lines), and simulated methane emission spectrum derived from TheoReTS data [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 6
Figure 6. Figure 6: Laboratory spectra data of pure N2O, N2O : H2O = 1 : 20, N2O : CO = 1 : 20, N2O : CO2 = 1 : 20. All the mixtures have the same column density of both N2O and a matrix molecule. The dashed lines mark the extreme peak positions of the N2O features. matrix molecule. The b…

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Works this paper leans on

56 extracted references · 22 canonical work pages

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts ...

  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]

    ".R늈Զ b YvY@ [x m ci1ƴ1 3H c1x 5=Yw 3o y `8 y 5;÷ BC 90TO (, lsoן 韅

    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...

    work page arXiv 2021

  4. [4]

    W., & Darling, D

    Anderson, T. W., & Darling, D. A. 1952, The Annals of Mathematical Statistics, 23, 193 , 10.1214/aoms/1177729437

    arXiv 1952

  5. [5]

    Anscombe, F. J. 1973, The American Statistician, 27, 17, 10.1080/00031305.1973.10478966

    work page Pith review arXiv 1973

  6. [6]

    1976, , 210, 642, 10.1086/154870

    Avni , Y. 1976, , 210, 642, 10.1086/154870

    doi:10.1086/154870 1976

  7. [7]

    S., Konopacky, Q

    Barman, T. S., Konopacky, Q. M., Macintosh, B., & Marois, C. 2015, ApJ, 804, 61, 10.1088/0004-637X/804/1/61

    doi:10.1088/0004-637x/804/1/61 2015

  8. [8]

    J., Welbanks , L., Schlawin , E., et al

    Bell , T. J., Welbanks , L., Schlawin , E., et al. 2023, , 623, 709, 10.1038/s41586-023-06687-0

    doi:10.1038/s41586-023-06687-0 2023

Show all 56 references
  1. [9]

    C., Ahmadi , A., et al

    Beuther , H., Mottram , J. C., Ahmadi , A., et al. 2018, , 617, A100, 10.1051/0004-6361/201833021

    2018 doi

  2. [10]

    F., Tychoniec , L., et al

    Beuther , H., van Dishoeck , E. F., Tychoniec , L., et al. 2023, , 673, A121, 10.1051/0004-6361/202346167

    2023 doi

  3. [11]

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

    2015 doi

  4. [12]

    Boogert , A. C. A., Helmich , F. P., van Dishoeck , E. F., et al. 1998, A&A, 336, 352. https://ui.adsabs.harvard.edu/abs/1998A&A...336..352B

    1998

  5. [13]

    Boogert , A. C. A., Schutte , W. A., Helmich , F. P., Tielens , A. G. G. M., & Wooden , D. H. 1997 a , , 317, 929. https://ui.adsabs.harvard.edu/abs/1997A&A...317..929B

    1997

  6. [14]

    Boogert , A. C. A., Schutte , W. A., Helmich , F. P., et al. 1997 b , A&A, 317, 929. https://ui.adsabs.harvard.edu/abs/1997A&A...317..929B

    1997

  7. [15]

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

    Bouilloud, M., Fray, N., B \'e nilan, Y., et al. 2015, MNRAS, 451, 2145, 10.1093/mnras/stv1021

    2015 doi

  8. [16]

    2019, , 627, A68, 10.1051/0004-6361/201935506

    Cesaroni , R., Beuther , H., Ahmadi , A., et al. 2019, , 627, A68, 10.1051/0004-6361/201935506

    2019 doi

  9. [17]

    Childs, W. H. J., & Bragg, W. H. 1936, Proceedings of the Royal Society of London. Series A - Mathematical and Physical Sciences, 153, 555, 10.1098/rspa.1936.0022

    1936

  10. [18]

    Cleveland, W. S. 1979, Journal of the American Statistical Association, 74, 829, 10.1080/01621459.1979.10481038

    1979

  11. [19]

    A., Caselli , P., et al

    Dartois , E., Noble , J. A., Caselli , P., et al. 2024, NatAs, 8, 359, 10.1038/s41550-023-02155-x

    2024 doi

  12. [20]

    2021, Astrophysics Source Code Library, ascl:2104.010

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

    2021

  13. [21]

    P., & Davis , D

    Drapatz , S., Larson , H. P., & Davis , D. S. 1987, , 187, 497. https://ui.adsabs.harvard.edu/abs/1987A&A...187..497D

    1987

  14. [22]

    M., Toriello, F., He, J., & Vidali, G

    Emtiaz, S. M., Toriello, F., He, J., & Vidali, G. 2020, The Journal of Physical Chemistry A, 124, 552, 10.1021/acs.jpca.9b10643

    2020 doi

  15. [23]

    2004, A&A, 414, 299, 10.1051/0004-6361:20031623

    Fontani, F., Cesaroni, R., Testi, L., et al. 2004, A&A, 414, 299, 10.1051/0004-6361:20031623

    2004 doi

  16. [24]

    L., van Dishoeck , E

    Francis , L., van Gelder , M. L., van Dishoeck , E. F., et al. 2024, , 683, A249, 10.1051/0004-6361/202348105

    2024 doi

  17. [25]

    A., & Hudson, R

    Gerakines, P. A., & Hudson, R. L. 2015, ApJL, 805, L20, 10.1088/2041-8205/805/2/L20

    2015 doi

  18. [26]

    F., et al

    Gieser , C., Beuther , H., van Dishoeck , E. F., et al. 2023, , 679, A108, 10.1051/0004-6361/202347060

    2023 doi

  19. [27]

    2008, , 685, 272, 10.1086/590468

    Harada , N., & Herbst , E. 2008, , 685, 272, 10.1086/590468

    2008 doi

  20. [28]

    E., Herbst , E., & Garrod , R

    Hassel , G. E., Herbst , E., & Garrod , R. T. 2008, , 681, 1385, 10.1086/588185

    2008 doi

  21. [29]

    D., Carrasco , N., et al

    Kobayashi , K., Geppert , W. D., Carrasco , N., et al. 2017, AsBio, 17, 786, 10.1089/ast.2016.1492

    2017

  22. [30]

    Krissansen-Totton , J., Garland , R., Irwin , P., & Catling , D. C. 2018, , 156, 114, 10.3847/1538-3881/aad564

    2018 doi

  23. [31]

    , Argyriou, I

    Labiano, A. , Argyriou, I. , Álvarez-Márquez, J. , et al. 2021, A&A, 656, A57, 10.1051/0004-6361/202140614

    2021 doi

  24. [32]

    J., et al

    Lacy, J., Carr, J., Evans, N. J., et al. 1991, Astrophysical Journal, Part 1 (ISSN 0004-637X), vol. 376, Aug. 1, 1991, p. 556-560. Research supported by Texas Advanced Research Program., 376, 556, 10.1086/170304

    1991 doi

  25. [33]

    2024, The Spatial Distribution of CH_4 and CO_2 Ice around Protostars IRAS 16253-2429 and IRAS 23385+6053

    Lei, L., Feng, L., & Fan, Y.-Z. 2024, The Spatial Distribution of CH_4 and CO_2 Ice around Protostars IRAS 16253-2429 and IRAS 23385+6053. 2409.04217

    2024 arXiv

  26. [34]

    2023, NatAs, 7, 431, 10.1038/s41550-022-01875-w

    McClure, M., Rocha, W., Pontoppidan, K., et al. 2023, NatAs, 7, 431, 10.1038/s41550-022-01875-w

    2023 doi

  27. [35]

    L., & Lora, J

    Mitchell, J. L., & Lora, J. M. 2016, AREPS, 44, 353, 10.1146/annurev-earth-060115-012428

    2016 doi

  28. [36]

    2008, , 487, 1119, 10.1051/0004-6361:200809821

    Molinari , S., Faustini , F., Testi , L., et al. 2008, , 487, 1119, 10.1051/0004-6361:200809821

    2008 doi

  29. [37]

    1998, , 505, L39, 10.1086/311591

    Molinari , S., Testi , L., Brand , J., Cesaroni , R., & Palla , F. 1998, , 505, L39, 10.1086/311591

    1998 doi

  30. [38]

    F., & Zhang , Q

    Molinari , S., Testi , L., Rodr \' guez , L. F., & Zhang , Q. 2002, , 570, 758, 10.1086/339630

    2002 doi

  31. [39]

    J., DiSanti, M

    Mumma, M. J., DiSanti, M. A., Russo, N. D., et al. 1996, Science, 272, 1310, 10.1126/science.272.5266.1310

    1996

  32. [40]

    , Rocha, W

    Nazari, P. , Rocha, W. R. M. , Rubinstein, A. E. , et al. 2024, A&A, 686, A71, 10.1051/0004-6361/202348695

    2024 doi

  33. [41]

    H., Schutte , W

    Novozamsky , J. H., Schutte , W. A., & Keane , J. V. 2001, , 379, 588, 10.1051/0004-6361:20011332

    2001 doi

  34. [42]

    2024, ApJL, 972, L10, 10.3847/2041-8213/ad6d5c

    Ozhiganov, M., Medvedev, M., Karteyeva, V., et al. 2024, ApJL, 972, L10, 10.3847/2041-8213/ad6d5c

    2024 doi

  35. [43]

    M., Wah, Y

    Razali, N. M., Wah, Y. B., et al. 2011, J. Stat. Model. Analytics, 2, 21

    2011

  36. [44]

    1984, Icarus, 60, 236, 10.1016/0019-1035(84)90187-8

    Reid Thompson , W., & Sagan, C. 1984, Icarus, 60, 236, 10.1016/0019-1035(84)90187-8

    1984 doi

  37. [45]

    V., & Tyuterev, V

    Rey, M., Nikitin, A. V., & Tyuterev, V. G. 2013, Phys. Chem. Chem. Phys., 15, 10049, 10.1039/C3CP50275A

    2013 doi

  38. [46]

    Rocha, W. R. M., McClure, M. K., Sturm, J. A., et al. 2024, Ice inventory towards the protostar Ced 110 IRS4 observed with the James Webb Space Telescope. Results from the ERS Ice Age program. 2411.19651

    2024 arXiv

  39. [47]

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

    2024 doi

  40. [48]

    2008, ApJ, 672, 371, 10.1086/523635

    Sakai, N., Sakai, T., Hirota, T., & Yamamoto, S. 2008, ApJ, 672, 371, 10.1086/523635

    2008 doi

  41. [49]

    Slavicinska , K., Rachid, M. G. , Rocha, W. R. M. , et al. 2023, A&A, 677, A13, 10.1051/0004-6361/202346996

    2023 doi

  42. [50]

    2011, Icarus, 215, 292, https://doi.org/10.1016/j.icarus.2011.06.024

    Sromovsky, L., Fry, P., & Kim, J. 2011, Icarus, 215, 292, https://doi.org/10.1016/j.icarus.2011.06.024

    2011 doi

  43. [51]

    Stephens, M. A. 1974, Journal of the American Statistical Association, 69, 730. http://www.jstor.org/stable/2286009

    1974

  44. [52]

    R., Vasisht , G., & Tinetti , G

    Swain , M. R., Vasisht , G., & Tinetti , G. 2008, , 452, 329, 10.1038/nature06823

    2008 doi

  45. [53]

    , Ligterink, N

    Terwisscha van Scheltinga, J. , Ligterink, N. F. W. , Boogert, A. C. A. , van Dishoeck, E. F. , & Linnartz, H. 2018, A&A, 611, A35, 10.1051/0004-6361/201731998

    2018 doi

  46. [54]

    A., Krissansen-Totton, J., Wogan, N., Telus, M., & Fortney, J

    Thompson, M. A., Krissansen-Totton, J., Wogan, N., Telus, M., & Fortney, J. J. 2022, Proceedings of the National Academy of Sciences, 119, e2117933119, 10.1073/pnas.2117933119

    2022 doi

  47. [55]

    E., et al

    Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261, 10.1038/s41592-019-0686-2

    2020 doi

  48. [56]

    I., Boogert, A

    Öberg, K. I., Boogert, A. C. A., Pontoppidan, K. M., et al. 2008, ApJ, 678, 1032, 10.1086/533432

    2008 doi

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