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arxiv: 2510.00292 · v3 · submitted 2025-09-30 · 🌌 astro-ph.GA

The Colors of Ices: Measuring ice column density through photometry

Adam Ginsburg , Savannah R. Gramze , Matthew L. N. Ashby , Brandt A. L. Gaches , Nazar Budaiev , Miriam G. Santa-Maria , Alyssa Bulatek , A. T. Barnes
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Desmond Jeff Neal J. Evans II Cara D. Battersby
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Pith reviewed 2026-05-18 11:00 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords interstellar icesJWST photometryGalactic CenterCO icemetallicitycarbon freezeoutNIRCamice column density
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The pith

JWST photometry alone can quantify interstellar ices in the Galactic Center, showing over 25 percent of carbon frozen as CO and implying at least 2.5 times solar metallicity.

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

The paper establishes that broadband photometry from JWST can detect and measure column densities of ices like CO, H2O, and CO2 without spectroscopy. A new open-source tool generates synthetic filter photometry from laboratory ice spectra to interpret the data. Applied to NIRCam observations of background stars behind Galactic Center dust ridge clouds, the models reveal clear ice absorption signatures and higher water ice fractions than in the disk. This leads to the inference that a large fraction of carbon is locked in ices, exceeding the solar-neighborhood budget, and under an equal freezeout assumption yields a high metallicity for the Galactic Center.

Core claim

The central claim is that photometric measurements in JWST filters capture ice absorption features, enabling quantification of CO, H2O, and CO2 column densities in Galactic Center clouds. These abundances imply that more than 25 percent of the total carbon is frozen into CO ice, surpassing the entire solar-neighborhood carbon budget, and assuming identical freezeout fractions between center and disk clouds produces a metallicity estimate of at least 2.5 solar.

What carries the argument

The icemodels tool, which produces synthetic photometry of ices based on laboratory measurements to predict and fit absorption in JWST broadband filters.

If this is right

  • Ice ratios differ between Galactic disk and Center, with GC clouds showing a higher H2O fraction.
  • A large ice abundance in CO, H2O, and possibly complex molecules implies substantial freezeout and potential for ice-phase chemistry in non-star-forming gas.
  • Accounting for all likely ices shows that more than 25 percent of the total carbon is frozen into CO ice in the GC, exceeding the solar-neighborhood carbon budget.
  • Assuming the same freezeout fraction as in disk clouds yields a metallicity measurement of Z_GC at least 2.5 times solar.

Where Pith is reading between the lines

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

  • The photometric technique could be scaled to map ice and metallicity variations across many more lines of sight in the Milky Way using existing JWST survey data.
  • High ice abundances in cold non-star-forming gas may require revisions to models of molecular cloud chemistry and the efficiency of star formation.
  • If freezeout fractions vary with local conditions, the metallicity estimate would need adjustment, but the core photometric detection method would remain valid.

Load-bearing premise

The assumption that the ice freezeout fraction is identical between Galactic Center and Galactic disk clouds.

What would settle it

Spectroscopic measurements of the total carbon abundance or gas-phase metallicity in the same Galactic Center clouds that fall below 2.5 solar would falsify the metallicity inference.

Figures

Figures reproduced from arXiv: 2510.00292 by Adam Ginsburg, Alyssa Bulatek, A. T. Barnes, Brandt A. L. Gaches, Cara D. Battersby, Desmond Jeff, Matthew L. N. Ashby, Miriam G. Santa-Maria, Nazar Budaiev, Neal J. Evans II, Savannah R. Gramze.

Figure 1
Figure 1. Figure 1: — Example JWST NIRSpec archival spectra with the filters used in project 2221 and emphasized throughout this work, F182M, F212N, F405N, F410M, and F466N, shown. HOPS-383 (left) from program 5804 is a Class 0 YSO (Megeath et al. 2012). IRAS16293 slit 74 from program 3222 is a star behind the IRAS16293 molecular cloud. The legend shows the synthetic magnitudes and colors computed from the spectrum. The title… view at source ↗
Figure 2
Figure 2. Figure 2: — F466N transmission spectrum (grey, arbitrary scaling) and ice effective opacity κeff (Eqn 2) as a function of wavelength across the F466N band. The colored curves show single-ice opaci￾ties for CO at 25 K (Gerakines et al. 2023), H2O at 25 K (Mastrapa et al. 2009), and OCN− (with contaminants) from Novozamsky et al. (2001) as described in the legend. online databases. The mean molecular weight µ is then … view at source ↗
Figure 3
Figure 3. Figure 3: — (top) Selected laboratory model ice opacities overlaid on the F405N, F410M, and F466N filter transmission profiles. The same opacity curves as in [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: — The distributions of Brick sources in the [F405N]−[F466N] and [F410M]−[F466N] vs [F182M]−[F212N] color-color spaces compared to the intrinsic estimated colors of ice mixtures as described in §5 and indicated with curves of different colors as shown above. These diagrams show photometry from narrow- and medium-band filters used in JWST program 2221. The model curves show the effect of adding the labeled i… view at source ↗
Figure 5
Figure 5. Figure 5: — The distributions of Brick, Cloud C, and Cloud D sources in the [F405N]−[F466N] and [F410M]−[F466N] vs [F182M]−[F212N] color-color spaces compared to the intrinsic estimated colors of ice mixtures as described in §5 and indicated with curves of different colors as shown above. The legend and models are the same as in figures 4 and 6. color-color diagrams, all model curves are drawn assum￾ing that the ice… view at source ↗
Figure 6
Figure 6. Figure 6: — The distributions of Brick, Cloud C, and Cloud D sources in the [F405N]−[F410M] vs [F182M]−[F212N] color-color space compared to the intrinsic estimated colors of ice mixtures as described in §5 and indicated with curves of different colors as shown above. sources are all similar YSOs is excluded. No sources with high signal-to-noise (mAB < 20) from projects 1611 or 3222 exhibit colors similar to the Gal… view at source ↗
Figure 7
Figure 7. Figure 7: — Color-color diagram like in [PITH_FULL_IMAGE:figures/full_fig_p012_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: — Reproduction of [PITH_FULL_IMAGE:figures/full_fig_p013_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: — As [PITH_FULL_IMAGE:figures/full_fig_p014_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: — Plot of CO ice abundance vs metallicity (top) and Galactocentric radius (bottom). See §6.5 for details. While there is a clear correlation between the F466N and F356W excess extinction, as shown in [PITH_FULL_IMAGE:figures/full_fig_p015_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: — Spatial distribution of the stars selected to have dered￾dened F405N-F466N < −0.4 and F356W-F444W > 0.4, respec￾tively. The background image is the ACES + MUSTANG-2 image that combines ALMA with Green Bank Telescope data to show the emission primarily from dust, which roughly traces the column density of the gas. The fields-of-view in these images are not the same because projects 2221 and 1182, which c… view at source ↗
Figure 12
Figure 12. Figure 12: — Opacities from several important ices (CO and H2O) overlaid on the JWST transmission curve (thick grey line) in the F466N band. The Hudgins et al. (1993) curve was used in Ginsburg et al. (2023), but was erroneously extrapolated from the cutoff edges seen in this figure. The other curves are from Mastrapa et al. (2009) and Gerakines et al. (2023) [PITH_FULL_IMAGE:figures/full_fig_p023_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: — A demonstration of the effect of CO2 ice on the F405N-F410M color. Both F405N and F410M are affected by CO2 ice absorption, but F410M is more strongly affected because it is closer to the CO2 ice absorption peak. See §5.2 [PITH_FULL_IMAGE:figures/full_fig_p024_13.png] view at source ↗
Figure 14
Figure 14. Figure 14: compares different possible choices of foreground extinction values adopting the CT06 extinction curve. An et al. (2011) and Jang et al. (2022), who examined Spitzer IRS spectra of icy sources in the Galactic Center, adopt AV,f g=20. Nogueras-Lara et al. (2021) adopt AK,f g = 1.87, or AV,f g ≈ 17. The leftmost figure shows that, for this adopted extinction curve, AV = 15 is too low - the red curves fall t… view at source ↗
Figure 15
Figure 15. Figure 15: — Comparison of different possible adopted extinction curves. See §E.2. / [PITH_FULL_IMAGE:figures/full_fig_p025_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: — Comparison of five plausible extinction vectors describing the foreground medium. The data shown are the ice-free data selected from the Brick data set. See §E.2 [PITH_FULL_IMAGE:figures/full_fig_p026_16.png] view at source ↗
Figure 17
Figure 17. Figure 17: — Comparison of different assumed CO/H2 ratios in color-color space used to evaluate the valid range of ice ratios H2O:CO:CO2 as shown in [PITH_FULL_IMAGE:figures/full_fig_p027_17.png] view at source ↗
Figure 18
Figure 18. Figure 18: — Comparison of different assumed ice ratios H2O:CO:CO2. See 3.3 [PITH_FULL_IMAGE:figures/full_fig_p027_18.png] view at source ↗
Figure 19
Figure 19. Figure 19: — CO ice abundance vs AV and column density in the Brick. The data are the same as those shown in [PITH_FULL_IMAGE:figures/full_fig_p028_19.png] view at source ↗
Figure 20
Figure 20. Figure 20: — Color-color diagrams showing the extinction-tracing F182M-F212N on the X axis vs F405N-F466N tracing CO (left) and F405N-F410M tracing CO2 (right). While the KP5 model produces qualitative agreement with the trend to the blue in F405N-F466N, which other extinction models (also plotted) do not, its slope does not match that of the Galactic Center data [PITH_FULL_IMAGE:figures/full_fig_p029_20.png] view at source ↗
Figure 21
Figure 21. Figure 21: — We show where the most ice-absorbed stars occur. The first figure shows stars with dereddened F405N-F466N < −0.3 and AV > 17, with extinction measured from F182M-F212N color. The backdrop is the star-subtracted F405N+F466N image from Ginsburg et al. (2023). The second shows stars with F356W-F444W > 0.3 and AV > 17, with extinction measured from F200W-F400W color. The backdrop is an RGB image composed of… view at source ↗
Figure 22
Figure 22. Figure 22: — ISO spectra of GCS 3 (top) and GCS 4 (bottom), pointings toward the Quintuplet cluster. See §J [PITH_FULL_IMAGE:figures/full_fig_p034_22.png] view at source ↗
Figure 23
Figure 23. Figure 23: shows a comparison between a linear combination of pure ices and a direct mixture of these ices. The curves are dramatically different in some regards. From 3.2-3.5 µm, the lab mixture is an order of magnitude more opaque than the linear combination or than the pure CH3OH ice, which likely indicates a change in the absorption cross section of those transitions (CH bonds) in this ice mixture. The peak from… view at source ↗
Figure 24
Figure 24. Figure 24: — Comparison of the effective opacities of the H2O:CO:CO2 ice mixtures considered. These are all normalized to the CO column density such that the opacity plotted is the total opacity of the ice per CO molecule. The second figure shows the same, but now with the individual pure ice components also shown. See §K [PITH_FULL_IMAGE:figures/full_fig_p036_24.png] view at source ↗
Figure 25
Figure 25. Figure 25: — Opacities used shown overplotted on the full NIRCam band. This plot can be used to guide filter selection or, at a glance, infer which ice species may affect a given photometric measurement. Curves are from Gerakines and Hudson (2020), Gerakines et al. (2023), and Mastrapa et al. (2009). 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Wavelength ( m) 10 21 10 20 10 19 10 18 10 17 eff [ = eff * N(ic e)] F277W F323N F360M F4… view at source ↗
Figure 26
Figure 26. Figure 26: — Opacities overplotted on the F277W, F323N, F360M, and F480M bands. Similar to the other opacity plots ( [PITH_FULL_IMAGE:figures/full_fig_p037_26.png] view at source ↗
Figure 27
Figure 27. Figure 27: — Reference figures showing opacities of water, ethanol, and water-ammonia ices on medium- and broad-band filters. In the 4µm medium-band filter figure, CO2 ice is also shown [PITH_FULL_IMAGE:figures/full_fig_p038_27.png] view at source ↗
read the original abstract

Ices imprint strong absorption features in the near- and mid-infrared, but until recently they have been studied almost exclusively with spectroscopy toward small samples of bright sources. We show that JWST photometry alone can reveal and quantify interstellar ices, and we present a new open-source modeling tool, icemodels, to produce synthetic photometry of ices based on laboratory measurements. We provide reference tables indicating which filters are likely to be observably affected by ice absorption. Applying these models to NIRCam data of background stars behind \refereeseveral Galactic Center (GC) clouds \referee(dust ridge clouds A [the Brick], C, and D), and validating against NIRSpec spectra of Galactic disk sources, we find clear signatures of CO, H$_2$O, and CO$_2$ ices and evidence for excess absorption in the F356W filter likely caused by CH-bearing species such as methanol. The ice ratios differ between the Galactic disk and Center, with GC clouds showing a higher H$_2$O fraction. \refereeA large ice abundance \refereeis observed in CO, H2O, and possibly complex molecules, \refereewhich implies that there is substantial freezeout and therefore potential for ice-phase chemistry in non-star-forming gas. Accounting for all likely ices, we infer that $>25%$ of the total carbon is frozen into CO ice in the GC, which exceeds the entire solar-neighborhood carbon budget. By assuming the freezeout fraction is the same in GC and disk clouds, we obtain a metallicity measurement indicating that $Z_GC\gtrsim2.5Z_\odot$. These results demonstrate that photometric ice measurements are feasible with JWST and capable of probing the metallicity structure of the cold interstellar medium.

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 paper demonstrates that JWST NIRCam photometry can be used to detect and quantify interstellar ice column densities (primarily CO, H2O, CO2, and CH-bearing species) by forward-modeling laboratory absorption spectra with the new open-source icemodels package. It validates the approach against NIRSpec spectra of Galactic disk sources, applies the method to background stars behind several Galactic Center dust ridge clouds (A/the Brick, C, D), reports clear filter-specific absorption signatures and differing ice ratios (higher H2O fraction in the GC), infers that >25% of carbon is locked in CO ice (exceeding the solar-neighborhood budget), and derives Z_GC ≳ 2.5 Z_⊙ by assuming the CO freezeout fraction equals the disk value.

Significance. If the photometric technique and its validation hold, the work provides a practical, scalable complement to spectroscopy for mapping ices across wide fields with existing JWST data, which is a clear methodological advance. The open-source icemodels tool, reference tables for affected filters, and evidence for substantial freezeout in non-star-forming GC gas are concrete strengths. The quantitative carbon-budget and metallicity conclusions, however, rest on an untested modeling assumption whose relaxation would materially change the headline numbers.

major comments (2)
  1. [§5] §5 (metallicity and carbon-budget discussion): The Z_GC ≳2.5 Z_⊙ result is obtained only after scaling the photometrically fitted N(CO ice) by a freezeout fraction taken to be identical to the Galactic-disk value. The manuscript itself reports differing ice ratios (elevated H2O fraction in GC clouds), indicating distinct physical or chemical conditions that could plausibly alter CO depletion efficiency. No gas-phase CO data, chemical models, or sensitivity tests are used to justify or bound the equality assumption, so the factor-of-2.5 metallicity boost is not independently supported.
  2. [Results section] Results section (ice-column fits and carbon accounting): The claim that >25% of total carbon is frozen into CO ice (exceeding the entire solar-neighborhood carbon budget) compares the fitted N(CO) to a total carbon reservoir derived from measured N(H) and a solar C/H ratio. Because the subsequent metallicity inference assumes a higher total C reservoir, the two statements are interdependent; the manuscript should explicitly show the arithmetic, propagate uncertainties from the free ice-column parameters, and test how the >25% figure changes if the freezeout fraction is allowed to differ.
minor comments (3)
  1. [Abstract] Abstract: the phrasing 'several Galactic Center (GC) clouds (dust ridge clouds A [the Brick], C, and D)' is slightly ambiguous about the exact number of sightlines or background stars analyzed; a parenthetical count would improve clarity.
  2. [Methods] Methods: while the open-source status of icemodels is a strength, the main text should include a direct GitHub/DOI link or citation to the code repository rather than leaving it only in a footnote or data-availability statement.
  3. [Figures and tables] Figure captions and tables: ensure every filter listed in the reference tables is cross-referenced to the corresponding synthetic photometry panel so readers can immediately see which ice species drive the absorption in each band.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed review. The concerns regarding the assumptions underlying the metallicity inference and the carbon-budget accounting are valid and have prompted us to strengthen the presentation of these results. We have revised the manuscript to include explicit arithmetic derivations, propagated uncertainties, and sensitivity tests on the freezeout-fraction assumption. Our point-by-point responses follow.

read point-by-point responses

  1. Referee: §5 (metallicity and carbon-budget discussion): The Z_GC ≳2.5 Z_⊙ result is obtained only after scaling the photometrically fitted N(CO ice) by a freezeout fraction taken to be identical to the Galactic-disk value. The manuscript itself reports differing ice ratios (elevated H2O fraction in GC clouds), indicating distinct physical or chemical conditions that could plausibly alter CO depletion efficiency. No gas-phase CO data, chemical models, or sensitivity tests are used to justify or bound the equality assumption, so the factor-of-2.5 metallicity boost is not independently supported.

    Authors: We agree that the differing ice ratios indicate distinct conditions and that the equality of CO freezeout fractions is an assumption rather than a directly tested result. The CO freezeout fraction depends primarily on local density and temperature in the dense gas we probe, which are expected to be comparable to disk clouds at similar extinctions. To address the referee's concern, the revised manuscript now includes sensitivity tests that vary the assumed freezeout fraction by factors of 0.5–2 relative to the disk value and report the resulting range in Z_GC. We also clarify that the >25% carbon-in-CO-ice statement is a direct lower limit independent of the metallicity scaling. While gas-phase CO data and full chemical models are beyond the scope of the current photometric study, the added tests bound the impact of relaxing the assumption. revision: yes

  2. Referee: Results section (ice-column fits and carbon accounting): The claim that >25% of total carbon is frozen into CO ice (exceeding the entire solar-neighborhood carbon budget) compares the fitted N(CO) to a total carbon reservoir derived from measured N(H) and a solar C/H ratio. Because the subsequent metallicity inference assumes a higher total C reservoir, the two statements are interdependent; the manuscript should explicitly show the arithmetic, propagate uncertainties from the free ice-column parameters, and test how the >25% figure changes if the freezeout fraction is allowed to differ.

    Authors: We concur that the carbon accounting requires clearer exposition and that the interdependence with the metallicity result should be quantified. The revised Results section now contains an explicit step-by-step derivation: the fraction of carbon in CO ice is computed as N(CO ice) / [N(H) × (C/H)_solar], with uncertainties propagated from the posterior distributions of the fitted ice columns (including covariances with N(H2O) and N(CO2)). We further test the robustness of the >25% figure by allowing the freezeout fraction to differ from the disk value; even under a factor-of-two lower freezeout, the carbon locked in CO ice remains ≳20% of the solar-neighborhood budget. These additions make the arithmetic transparent and demonstrate that the headline carbon-budget result is not solely dependent on the metallicity scaling. revision: yes

Circularity Check

0 steps flagged

No significant circularity in the derivation chain

full rationale

The paper fits ice column densities as adjustable parameters to match JWST photometry via laboratory-based synthetic models in the new icemodels tool. The >25% carbon-in-CO-ice fraction is computed directly from these fitted columns relative to an external total carbon budget. The Z_GC ≳2.5 Z_⊙ result is obtained only after an explicitly stated assumption that the CO freezeout fraction equals the disk value; this assumption is not derived from the photometry, not obtained by self-citation, and not equivalent to any fitted input by construction. No equations reduce outputs to inputs tautologically, and the chain relies on independent photometric data plus external lab spectra.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The results rest on laboratory ice spectra as input, fitted ice column densities per filter, and the explicit assumption of equal freezeout fractions between regions; no new particles or forces are postulated.

free parameters (2)
  • ice column densities for CO, H2O, CO2, and CH-bearing species
    Adjusted to reproduce the observed photometry in the selected NIRCam filters.
  • freezeout fraction
    Set equal between GC and disk clouds to derive the metallicity value.
axioms (1)
  • domain assumption Laboratory transmission spectra of ices accurately predict the absorption features observed in interstellar environments.
    Basis for the icemodels synthetic photometry.

pith-pipeline@v0.9.0 · 5908 in / 1484 out tokens · 59049 ms · 2026-05-18T11:00:29.530468+00:00 · methodology

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Works this paper leans on

13 extracted references · 13 canonical work pages

  1. [1]

    doi:10.1088/0004-637X/736/2/133. D. An, K. Sellgren, A. C. A. Boogert, S. V. Ram´ ırez, and T.-S. Pyo. Abundant Methanol Ice toward a Massive Young Stellar Object in the Central Molecular Zone.ApJ, 843(2):L36, July

    work page doi:10.1088/0004-637x/736/2/133

  2. [2]

    doi:10.3847/2041-8213/aa7cfe. K. Z. Arellano-C´ ordova, C. Esteban, J. Garc´ ıa-Rojas, and J. E. M´ endez-Delgado. The Galactic radial abundance gradients of C, N, O, Ne, S, Cl, and Ar from deep spectra of H II regions. MNRAS, 496(2):1051–1076, Aug. 2020. doi:10.1093/mnras/staa1523. M. L. N. Ashby, J. L. Hora, K. Lakshmipathaiah, S. Vig, R. K. Sai Subrahm...

    work page doi:10.3847/2041-8213/aa7cfe 2041

  3. [3]

    doi:10.1146/annurev.astro.45.071206.100404. M. P. Bernstein, D. P. Cruikshank, and S. A. Sandford. Near-infrared laboratory spectra of solid H 2O/CO 2 and CH 3OH/CO 2 ice mixtures.Icarus, 179(2):527–534, Dec. 2005. doi:10.1016/j.icarus.2005.07.009. 18 J. J. Bock, A. M. Aboobaker, J. Adamo, R. Akeson, J. M. Alred, F. Alibay, M. L. N. Ashby, Y. P. Bach, L. ...

    work page doi:10.1146/annurev.astro.45.071206.100404 2005

  4. [4]

    doi:10.1088/0004-637X/690/1/496. J. E. Chiar and A. G. G. M. Tielens. Pixie Dust: The Silicate Features in the Diffuse Interstellar Medium.ApJ, 637(2): 774–785, Feb. 2006. doi:10.1086/498406. J. E. Chiar, A. J. Adamson, Y. J. Pendleton, D. C. B. Whittet, D. A. Caldwell, and E. L. Gibb. Hydrocarbons, Ices, and “XCN” in the Line of Sight toward the Galactic...

    work page doi:10.1088/0004-637x/690/1/496 2006

  5. [5]

    doi:10.1088/0004-637X/809/2/143. P. Ehrenfreund, A. C. A. Boogert, P. A. Gerakines, D. J. Jansen, W. A. Schutte, A. G. G. M. Tielens, and E. F. van Dishoeck. A laboratory database of solid CO and CO 2 for ISO.A&A, 315:L341–L344, Nov. 1996a. P. Ehrenfreund, P. A. Gerakines, W. A. Schutte, M. C. van Hemert, and E. F. van Dishoeck. Infrared properties of iso...

    work page doi:10.1088/0004-637x/809/2/143 1997

  6. [6]

    doi:10.1038/s42004-024-01117-2. S. A. Federman, S. T. Megeath, A. E. Rubinstein, R. Gutermuth, M. Narang, H. Tyagi, P. Manoj, G. Anglada, P. Atnagulov, H. Beuther, T. L. Bourke, N. Brunken, A. Caratti o Garatti, N. J. Evans, W. J. Fischer, E. Furlan, J. D. Green, N. Habel, L. Hartmann, N. Karnath, P. Klaassen, H. Linz, L. W. Looney, M. Osorio, J. Muzeroll...

    work page doi:10.1038/s42004-024-01117-2 2024

  7. [7]

    doi:10.1086/307611. P. A. Gerakines, C. K. Materese, and R. L. Hudson. Carbon monoxide ices - a semicentennial review and update for crystalline CO along with the first IR spectrum and band strength for amorphous CO.MNRAS, 522(2):3145–3162, June

    work page doi:10.1086/307611

  8. [8]

    doi:10.1093/mnras/stad1164. E. L. Gibb, D. C. B. Whittet, A. C. A. Boogert, and A. G. G. M. Tielens. Interstellar Ice: The Infrared Space Observatory Legacy.ApJS, 151(1):35–73, Mar. 2004. doi:10.1086/381182. 19 A. Ginsburg, B. M. Sip˝ ocz, C. E. Brasseur, P. S. Cowperthwaite, M. W. Craig, C. Deil, J. Guillochon, G. Guzman, S. Liedtke, P. Lian Lim, K. E. L...

    work page doi:10.1093/mnras/stad1164 2004

  9. [9]

    doi:10.1007/978-3-642-18418-5˙17. K. D. Gordon, K. A. Misselt, J. Bouwman, G. C. Clayton, M. Decleir, D. C. Hines, Y. Pendleton, G. Rieke, J. D. T. Smith, and D. C. B. Whittet. Milky Way Mid-Infrared Spitzer Spectroscopic Extinction Curves: Continuum and Silicate Features.ApJ, 916(1):33, July 2021. doi:10.3847/1538-4357/ac00b7. K. D. Gordon, G. C. Clayton...

    work page doi:10.1007/978-3-642-18418-5 2021

  10. [10]

    doi:10.1038/s41586-020-2649-2. J. D. Henshaw, A. Ginsburg, T. J. Haworth, S. N. Longmore, J. M. D. Kruijssen, E. A. C. Mills, V. Sokolov, D. L. Walker, A. T. Barnes, Y. Contreras, J. Bally, C. Battersby, H. Beuther, N. Butterfield, J. E. Dale, T. Henning, J. M. Jackson, J. Kauffmann, T. Pillai, S. Ragan, M. Riener, and Q. Zhang. ‘The Brick’ is not a brick...

    work page doi:10.1038/s41586-020-2649-2 2019

  11. [11]

    doi:10.1007/BF00057607. G. Nandakumar, N. Ryde, M. Schultheis, B. Thorsbro, H. J¨ onsson, P. S. Barklem, R. M. Rich, and F. Fragkoudi. Chemical characterization of the inner Galactic bulge:North-South symmetry.MNRAS, 478(4):4374–4389, Aug. 2018. doi:10.1093/mnras/sty1255. M. F. Nieva and N. Przybilla. Present-day cosmic abundances. A comprehensive study o...

    work page doi:10.1007/bf00057607 2018

  12. [12]

    doi:10.3847/1538-4357/ad072d. J. Rigby, M. Perrin, M. McElwain, R. Kimble, S. Friedman, M. Lallo, R. Doyon, L. Feinberg, P. Ferruit, A. Glasse, M. Rieke, G. Rieke, G. Wright, C. Willott, et al. The Science Performance of JWST as Characterized in Commissioning. PASP, 135(1046):048001, Apr. 2023. doi:10.1088/1538-3873/acb293. T. P. Robitaille. A modular set...

    work page doi:10.3847/1538-4357/ad072d 2023

  13. [13]

    doi:10.1051/0004-6361/201425486. W. Rocha and S. Pilling. Determination of optical constants n and k of thin films from absorbance data using kramers-kronig relationship.Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 123:436–446, 2014. ISSN 1386-1425. doi:https://doi.org/10.1016/j.saa.2013.12.075. URLhttps://www.sciencedirect.com/sci...

    work page doi:10.1051/0004-6361/201425486 2014