A cometary fluorescence model of cyanogen in the near-infrared
Bibliographic record
Abstract
While the cyano radical (CN) is a well-known and prominent feature in cometary optical spectra, its origin remains poorly understood. In particular, although hydrogen cyanide (HCN) is considered the primary parent molecule of CN, it is not abundant enough to account for the observed amounts of the radical (Fray et al., 2005). As a result, cyanogen (C2N2) has been proposed as a secondary potential parent molecule.Among the major breakthroughs achieved by the Rosetta mission, the discovery of around 40 new molecular species—previously undetected in comets—by the ROSINA mass spectrometer has considerably improved our understanding of cometary chemical diversity. Cyanogen was among the most recently identified molecules in the coma of 67P (Hänni et al., 2021). Although the low derived mixing ratios suggest it is unlikely to produce CN in sufficient amounts on its own, further investigation of its abundance in other comets is essential to better constrain its potential role as a CN precursor and to improve our understanding of cometary chemistry.In this context, we investigated the presence of cyanogen in near-infrared cometary spectra. In the HITRAN database (Gordon et al., 2022), only the far-infrared ν5 band of C2N2 (Fayt et al., 2012) is currently included, and no spectroscopic data are available above 310 cm-1. Notably, one of the molecule's fundamental vibrational bands, ν3, centered at 2158 cm-1 (4.63 μm), has never been studied at high spectral resolution. This band is particularly interesting as it lies within the M-infrared atmospheric window, a region relatively free from atmospheric emission lines of H2O and CO2.We present here, for the first time, a high-resolution analysis of line positions and intensities in the ν3 band region of C2N2, based on laboratory infrared spectra. From this, we derived molecular parameters for both the ground and excited vibrational states using PGOPHER (Western, 2017).This spectroscopic analysis enabled the construction of the first line-by-line fluorescence model of cyanogen. Excitation rates for individual lines of the ν3 band in cometary comae are also presented (Fig. 1).Finally, we present an upper limit for the abundance of cyanogen in comet C/2022 E3 (ZTF), observed in 2023 with JWST (Milam et al., 2023). We discuss how future instruments such as METIS on the ELT could further improve this limit, or even allow a detection of cyanogen in a bright comet. Figure 1: Emission g-factors of C2N2 expressed in photons s-1 molecule-1 at T=50 K. This work is part of the COSMIC project (Computation and Spectroscopy of Molecules in the Infrared for Comets), funded by the EIPHI Graduate School. https://gradschool.eiphi.ubfc.fr/?p=3710 References Fayt A., Joly A., Benilan Y., Manceron L., Kwabia-Tchana F., Guillemin J.-C., 2012, Frequency and intensity analyses of the far infrared ν5 band system of cyanogen (C2N2) and applications to Titan, Journal of Quantitative Spectroscopy and Radiative Transfer 113, 1195-1219.Fray N., Bénilan Y., Cottin H., Gazeau M.-C., Crovisier J., 2005, The origin of the CN radical in comets: A review from observations and models. Planetary and Space Sciences 53(12), 1243–1262.Gordon I.E., Rothman L.S., Hargreaves R.J. et al., 2022, The HITRAN2020 molecular spectroscopic database, Journal of Quantitative Spectroscopy and Radiative Transfer 277.Hänni N., Altwegg K., Balsiger H. et al., 2021, Cyanogen, cyanoacetylene, and acetonitrile in comet 67P and their relation to the cyano radical, Astronomy And Astrophysics, 647.Milam S. N., Roth N. X., Villanueva G.L., Wong I., Kelley M. S. P., Bockelée-Morvan D., Hammel H. B., 2023, Asteroids, Comets, Meteors Conference 2023, LPI Contrib. No 2851.Western C.M., 2017, PGOPHER: A program for simulating rotational, vibrational and electronic spectra, Journal of Quantitative Spectroscopy and Radiative Transfer 186, 221-242.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".