JuanCastillo29/space-mission-intelligence-data huggingface dataset:
6S signal was observed, based on the DFMS data evaluated so far.

DFMS achieved a mass resolution of m/∆m=3000 at 1% of the peak height at m/z=28 (Balsiger et al. 2007), which is exceptional for space instruments and allows searching for the fingerprints of specific molecules in a complex analyte mixture as we explain in detail the in following two subsections.
2.2.

Electron Ionization-Induced Fragmentation EI mostly yields singly charged cations of the analyte molecules, which we refer to as molecular ions (M), or fragments thereof.

Fragmentation accompanying the EI process produces the so-called fragmentation pattern of an analyte species, which is the characteristic fingerprint of signals of all charged species, parents and fragments.

If the gaseous analyte is a complex mixture, such as that from a cometary coma, the fragmentation patterns of all species that are simultaneously ionized in the instruments’ ionization chamber overlap and the sum of their fragmentation patterns is detected.

As it is not possible to calibrate all volatile organic molecules on the DFMS laboratory twin instrument and the DMFS calibration facility is not equipped for handling corrosive or toxic species, like for instance DMS, we used reference fragmentation patterns from the National Institute of Standards and Technology (NIST) chemistry web-book EI-MS data base (Steins 2018) for this work.

Fragmentation patterns measured with DFMS are known to deviate little from those in the NIST data base, see, e.g., Schuhmann et al. (2019a,b).

This deviation is mostly due to the different ionization energies – DFMS uses 45 eV electrons while NIST standard spectra are usually measured using 70 eV electrons.

The ionization cross-section of DMS changes little between 45 and 70 eV (Kaur et al. 2015).

By trend, lower ionization energies may slightly enhance the relative abundance of the parent with respect to the fragments.

Also, differences in instrument geometries may play a role.

Here, we do not account for those deviations.

However, calibration experiments performed by Schuhmann et al. (2019a,b) and in the framework of several PhD theses (Calmonte 2015; Schroeder 2020; Schuhmann 2020) archived together with the ROSINA data on ESA’s Planetary Science Archive (PSA) and NASA’s Planetary Data System (PDS) show that they are generally small, normally below 10% relative intensity.

Figure 1 juxtaposes the NIST fragmentation patterns of DMS and its structural isomer ethanethiol, the topic of this work, normalized to the highest signal.

The most intense signal in both fragmentation patterns is the M signal on m/z=62.

Both isomers also produce a relevant M-H signal on m/z=61, which for DMS is more pronounced.

The lower-mass fragments, however, are distinct: DMS favorably loses a methyl group, leading to a strong group of signals on m/z=45-47, the M-CH3 fragment being the one on m/z=47.

Ethanethiol may also lose a methyl group, but more favorably loses the thiol function to produce a set of strong signals on m/z=27H¨anni et al.
ethanethiol (CH3−CH2−SH) dimethylsulfide (CH3−S−CH3)
rel. intensity (%)
10 20 30 40 50 60 m/z

[Figure: Figure 1. Juxtaposed NIST reference fragmentation patterns of the two structural isomers DMS and ethanethiol (Steins 2018). The relative intensity (rel. intensity; normalized to the highest signal in the spectrum) is plotted as a function of mass-per-charge (m/z).]
Figure 2 shows the mass spectra registered around the nominal masses m/z =62, where we expect the molecular ion
mass spectra:
In a first step, the absolute peak position and, consequently, the mass scale in the mass spectrum, has to be defined
via one known species-peak pair. Frequently observed continuation of homologous series in adjacent mass spectra (e.g.,
from one mass scan to the next.
Subsequently, the signal strengths must be extracted via peak fitting, using a Gaussian peak profile on a linear
background, see, e.g., Le Roy et al. (2015). A good fit is usually achieved by combining an intense and narrow first
Gaussian with a less intense and broader second Gaussian with fixed height and width ratios (De Keyser et al. 2019).
Here, we used a double-Gaussian peak profile for signals with intensities above 10 a.u. and a single-Gaussian one for
smaller signals where the second Gaussian disappears in the background. It can be seen from Figure 2 that signals
from multiple species are usually present in one mass spectrum. Thanks to the high mass resolution of DFMS, it is
often possible to distinguish species that have only small differences in the exact masses. The fitted peak position
have a mass difference of 7σ and 4.5σ, respectively, which renders their contributions negligible. The fit error for the
m/z =61.
Sometimes, corrections for a drift in the signal strength during the time of the data collection are necessary as a
change in cometary outgassing activity potentially distorts the observed fragmentation patterns. However, no such
Calmonte et al. 2017), which indicates stable coma conditions on the time scales relevant for this investigation. Also,
the water signal on m/z =18, additionally scanned first and last in every mode to track density fluctuations, shows Evidence for Abiotic Dimethyl Sulfide 5 a)

b)

[Figure: Figure 2. DFMS mass spectra collected on 15 March 2016 around m/z equal to 62 (a) and 61 (b). The measured intensities per pixel are plotted with black squares, in arbitrary units (a.u.), and with their statistical uncertainties. The peaks are fitted with Gaussian functions. We show the individual Gaussians in gray, highlighting those representing the relevant S-bearing species in magenta, and the overall fit in purple. The exact mass positions of the different chemical species are indicated by dashed lines. The standard deviation of the fitted peak position is ≈6 × 10−4.]
Steins 2018).

Second, the C2H6S/CH4O abundance ratios, where CH4O corresponds to the methanol molecular ion, are surprisingly constant too, except for the one in August 2015 when there was a lot of sublimation also from dust and the cometary activity was highly variable.

In October 2014 and March 2016, however, the comet was at a comparable heliocentric distance of around 3 au and the activity was more stable and rather comparable.

The respective C2H6S/CH4O abundance ratios are identical within 1σ error margins.

This is an indication for DMS and methanol to sublimate from the same layer in the cometary nucleus, and possibly even hints at a common origin.

However, more detailed correlation studies are needed to support this hypothesis.

Time (UTC) Longitude (◦) Latitude (◦) C2H5S/C2H6S (%) C2H6S/CH4O (%) 15 March 2016, 03:12 29.08 -14.63 43 ± 6 0.13 ± 0.04 15 March 2016, 03:55 7.37 -17.10 31 ± 6 0.13 ± 0.04 15 March 2016, 04:40 -14.40 -19.59 36 ± 6 0.14 ± 0.04 17 March 2016, 03:27 -140.18 21.42 40 ± 7 0.11 ± 0.04 10 October 2014, 17:17 -13.45 6.59 100 ± 20 0.12 ± 0.04 3 August 2015, 16:48 -31.09 -13.78 95 ± 30 0.26 ± 0.06 [Table: Table 1.

Spacecraft relative position (longitude and latitude) and C2H5S/C2H6S and C2H6S/CH4O abundance ratios for the four spectra shown Figure 4 plus two additional spectra from 10 October 2014 (Calmonte et al. 2016) and 3 August 2015 (H¨anni et al. 2022), respectively.

REFERENCES
Altwegg, K., Balsiger, H., & Fuselier, S.

A. 2019, ARA&A, 57, 113, doi: 10.1146/annurev-astro-091918-104409
Altwegg, K., Balsiger, H., H¨anni, N., et al. 2020, Nature Astronomy, 4, 533, doi: 10.1038/s41550-019-0991-9]

10 H¨anni et al.
b)

[Figure: Figure 4. Time-variability of DFMS mass spectra collected around 67P’s outbound equinox and for the set masses m/z=61 (a) and m/z=62 (b). The measured intensities per pixel are plotted with line points and in arbitrary units (a.u.). To improve the visibility, statistical uncertainties are indicated as error bars for the 3/15 03:55 UTC spectrum only.]

Altwegg, K., Combi, M., Fuselier, S.

A., et al. 2022, MNRAS, 516, 3900, doi: 10.1093/mnras/stac2440
Drozdovskaya, M.

N., van Dishoeck, E.

F., Rubin, M., Jørgensen, J.

K., & Altwegg, K. 2019, MNRAS, 490, 50, doi: 10.1093/mnras/stz2430 Fayolle, E.

C., ¨Oberg, K.

I., Jørgensen, J.

K., et al. 2017, Nature Astronomy, 1, 703, doi: 10.1038/s41550-017-0237-7 Glein, C.

R. 2024, ApJL, 964, L19, doi: 10.3847/2041-8213/ad3079 H¨anni, N., Altwegg, K., Combi, M., et al. 2022, Nature Communications, 13, 3639, doi: 10.1038/s41467-022-31346-9 H¨anni, N., Gasc, S., Etter, A., et al. 2019, Journal of Physical Chemistry A, 123, 5805, doi: 10.1021/acs.jpca.9b03534 H¨anni, N., Altwegg, K., Baklouti, D., et al. 2023, A&A, 678, A22, doi: 10.1051/0004-6361/202347059 H¨assig, M., Altwegg, K., Balsiger, H., et al. 2017, A&A, 605, A50, doi: 10.1051/0004-6361/201630140 Horita, J., & Berndt, M.

E. 1999, Science, 285, 1055, doi: 10.1126/science.285.5430.1055 Ilyushin, V., Armieieva, I., Dorovskaya, O., et al. 2020, Journal of Molecular Structure, 1200, 127114, doi: 10.1016/j.molstruc.2019.127114 Jabri, A., Van, V., Nguyen, H.

V.

L., et al. 2016, A&A, 589, A127, doi: 10.1051/0004-6361/201628074 Kaur, J., Singh, S., & Antony, B. 2015, Molecular Physics, 113, 3883, doi: 10.1080/00268976.2015.1075621 L¨auter, M., Kramer, T., Rubin, M., & Altwegg, K. 2020, MNRAS, 498, 3995, doi: 10.1093/mnras/staa2643 Le Roy, L., Altwegg, K., Balsiger, H., et al. 2015, A&A, 583, A1, doi: 10.1051/0004-6361/201526450 L´opez-Gallifa, ´A., Rivilla, V.

M., Beltr´an, M.

T., et al. 2024, MNRAS, 529, 3244, doi: 10.1093/mnras/stae676
Andreae, M.
: 10.1093/mnras/staa2643 Le Roy, L., Altwegg, K., Balsiger, H., et al. 2015, A&A, 583, A1, doi: 10.1051/0004-6361/201526450 L´opez-Gallifa, ´A., Rivilla, V.

M., Beltr´an, M.

T., et al. 2024, MNRAS, 529, 3244, doi: 10.1093/mnras/stae676
Andreae, M.

O., & Raemdonck, H. 1983, Science, 221, 744, doi: 10.1126/science.221.4612.744 Balsiger, H., Altwegg, K., Bochsler, P., et al. 2007, SSRv, 128, 745, doi: 10.1007/s11214-006-8335-3 Bardyn, A., Baklouti, D., Cottin, H., et al. 2017, MNRAS, 469, S712, doi: 10.1093/mnras/stx2640 Bieler, A., Altwegg, K., Balsiger, H., et al. 2015, Nature, 526, 678, doi: 10.1038/nature15707 Bockel´ee-Morvan, D., Lis, D.

C., Wink, J.

E., et al. 2000, A&A, 353, 1101 Bouquet, A., Mousis, O., Waite, J.

H., & Picaud, S. 2015, Geophys.

Res.

Lett., 42, 1334, doi: 10.1002/2014GL063013 Brasser, R., Mojzsis, S.

J., Werner, S.

C., Matsumura, S., & Ida, S. 2016, Earth and Planetary Science Letters, 455, 85, doi: 10.1016/j.epsl.2016.09.013 Calmonte, U., Altwegg, K., Balsiger, H., et al. 2016, MNRAS, 462, S253, doi: 10.1093/mnras/stw2601 —. 2017, MNRAS, 469, S787, doi: 10.1093/mnras/stx2534 Calmonte, U.

M. 2015, Sulfur isotopic ratios at 67P/Churyumov-Gerasimenko and characterization of ROSINA-DFMS FM and FS Catling, D.

C., Krissansen-Totton, J., Kiang, N.

Y., et al. 2018, Astrobiology, 18, 709, doi: 10.1089/ast.2017.1737 De Keyser, J., Altwegg, K., Gibbons, A., et al. 2019, International Journal of Mass Spectrometry, 446, 116232, doi: 10.1016/j.ijms.2019.116232 Domagal-Goldman, S.

D., Meadows, V.

S., Claire, M.

W., & Kasting, J.

F. 2011, Astrobiology, 11, 419, doi: 10.1089/ast.2010.0509

Evidence for Abiotic Dimethyl Sulfide 11 Schroeder, I.

R.

H.

G. 2020, Isotopic Composition of Water
Madhusudhan, N., Piette, A.

A.

A., & Constantinou, S. 2021, ApJ, 918, 1, doi: 10.3847/1538-4357/abfd9c Madhusudhan, N., Sarkar, S., Constantinou, S., et al. 2023, ApJL, 956, L13, doi: 10.3847/2041-8213/acf577 Mahjoub, A., Poston, M.

J., Blacksberg, J., et al. 2017, ApJ, 846, 148, doi: 10.3847/1538-4357/aa85e0 Mahjoub, A., Altwegg, K., Poston, M.

J., et al. 2023, Science Advances, 9, eadh0394, doi: 10.1126/sciadv.adh0394 Pilcher, C.
, L13, doi: 10.3847/2041-8213/acf577 Mahjoub, A., Poston, M.

J., Blacksberg, J., et al. 2017, ApJ, 846, 148, doi: 10.3847/1538-4357/aa85e0 Mahjoub, A., Altwegg, K., Poston, M.

J., et al. 2023, Science Advances, 9, eadh0394, doi: 10.1126/sciadv.adh0394 Pilcher, C.

B. 2003, Astrobiology, 3, 471, doi: 10.1089/153110703322610582 Poch, O., Istiqomah, I., Quirico, E., et al. 2020, Science, 367, aaw7462, doi: 10.1126/science.aaw7462 Raulin, F., & Toupance, G. 1975, Origins of Life, 6, 91, doi: 10.1007/BF01372393 Rigby, F.

E., & Madhusudhan, N. 2024, MNRAS, 529, 409, doi: 10.1093/mnras/stae413 Roy, K.-M. 2000, Thiols and Organic Sulfides (John Wiley and Sons, Ltd), doi: https://doi.org/10.1002/14356007.a26 767 Rubin, M., Altwegg, K., Balsiger, H., et al. 2019, MNRAS, 489, 594, doi: 10.1093/mnras/stz2086 Rubin, M., Altwegg, K., Berthelier, J.-J., et al. 2023, MNRAS, 526, 4209, doi: 10.1093/mnras/stad3005 Sagan, C., Thompson, W.

R., Carlson, R., Gurnett, D., & Hord, C. 1993, Nature, 365, 715, doi: 10.1038/365715a0 Sandford, S.

A. 2008, Annual Review of Analytical Chemistry, 1, 549, doi: 10.1146/annurev.anchem.1.031207.113108 Schl¨appi, B., Altwegg, K., Balsiger, H., et al. 2010, Journal of Geophysical Research (Space Physics), 115, A12313, doi: 10.1029/2010JA015734
in Comet 67P/Churyumov-Gerasimenko and Characterisation of the ROSINA DFMS FS Schuhmann, M. 2020, An Investigation of CH- and CHO-bearing Molecules with the ROSINA-DFMS Schuhmann, M., Altwegg, K., Balsiger, H., et al. 2019a, ACS Earth and Space Chemistry, 3, 1854, doi: 10.1021/acsearthspacechem.9b00094 —. 2019b, A&A, 630, A31, doi: 10.1051/0004-6361/201834666 Schwieterman, E.

W., Kiang, N.

Y., Parenteau, M.

N., et al.
2018, Astrobiology, 18, 663, doi: 10.1089/ast.2017.1729 Seager, S., Bains, W., & Hu, R. 2013, ApJ, 777, 95, doi: 10.1088/0004-637X/777/2/95 Seager, S., Bains, W., & Petkowski, J.

J. 2016, Astrobiology, 16, 465, doi: 10.1089/ast.2015.1404 Shorttle, O., Jordan, S., Nicholls, H., Lichtenberg, T., & Bower, D.

J. 2024, ApJL, 962, L8, doi: 10.3847/2041-8213/ad206e Steins, S.

E. 2018, Chemistry WebBook, NIST Standard Reference Database Number 69, National Institute of Standards and Technology Taubner, R.-S., Pappenreiter, P., Zwicker, J., et al. 2018, Nature Communications, 9, 748, doi: 10.1038/s41467-018-02876-y Waite, J.

H., Glein, C.
D.

J. 2024, ApJL, 962, L8, doi: 10.3847/2041-8213/ad206e Steins, S.

E. 2018, Chemistry WebBook, NIST Standard Reference Database Number 69, National Institute of Standards and Technology Taubner, R.-S., Pappenreiter, P., Zwicker, J., et al. 2018, Nature Communications, 9, 748, doi: 10.1038/s41467-018-02876-y Waite, J.

H., Glein, C.

R., Perryman, R.

S., et al. 2017, Science, 356, 155, doi: 10.1126/science.aai8703 Wogan, N.

F., Batalha, N.

E., Zahnle, K.

J., et al. 2024, ApJL, 963, L7, doi: 10.3847/2041-8213/ad2616
We review the current state of knowledge of the long-term evolution of the small bodies that give rise to comets and exocomets, as well as their reservoirs. The active cometary phase is only transitory, and bodies that become comets pass from a source population, such as the Kuiper Belt, Oort cloud or their extra-solar analogues, through the active cometary phase, to eventual dormancy or destruction. We discuss dynamical delivery channels that can move comets from their source reservoirs to orbits with small periapsides, and the depletion of these reservoirs by dynamical and collisional means. We also discuss the physical evolution of cometary nuclei, especially in light of recent advances from missions to Solar System comets such as Rosetta’s visit to 67P. We then describe our current knowledge of interstellar objects, which can originate from the same source regions as exocomets but be amenable to detailed study when they enter the Solar System. We include a summary of stellar winds emanating from different types of stars, which become increasingly strong once stars leave the Main Sequence. This is followed by a description of how small bodies are affected by stellar evolution, and the range of comet-like phenomena observed towards white dwarf stars.

Overall, while we have an increasingly good picture of the physical and dynamical evolution of Solar System comets, a number of large gaps remain in our knowledge of the physics of exocomets, related to our inability to directly probe these bodies and many of the planets that might be affecting their orbits.
Keywords: Comets — Kuiper Belt Objects — Oort Cloud — planets and satellites: dynamical evolution and stability — planet–disc interactions — circumstellar matter
An exocomet is a small body orbiting another star that is undergoing detectable mass loss, either through sublimation or by some other means1 (Iglesias et al, 2025). Comets and other small bodies of planetary systems are constantly evolving, both as isolated bodies and as populations. Most clearly, when a small body presents as an active comet it is, by definition, losing mass which becomes visible as its coma and tails; this implies that a body’s existence as an active comet cannot continue indefinitely. The mass loss arises because of changing conditions as the cometary nucleus approaches orbital periapsis, notably the increased instellation which heats the body and leads to outgassing. As an orbit in the Newtonian two-body problem is invariant, this in turn implies that a comet’s orbit must have been changed in the relatively recent past so that it has not spent too long with its current, small, orbital periapsis. This in turn implies the existence of one or more cometary reservoirs where the comets are “stored” for long periods (up to Gyrs) at large radii from their host star, and some perturbing forces that can remove them from these reservoirs to be driven onto orbits with small periapsides where they become visible as active comets. In the Solar System, these delivery processes are reasonably well understood, with distinct dynamical populations of comets being known, together with the means by which they are removed from their source reservoirs of the Kuiper Belt, Scattered Disc and Oort Cloud (Dones et al, 2015; Peixinho et al, 2020). The two major populations of comets are (1) ecliptic comets, which are moved by perturbations induced by the giant planets from their source in the trans-Neptunian disc (Kuiper Belt proper and scattered disc), via the Centaur population, to become Jupiter-Family Comets, and (2) the nearly-isotropic comets, which have been scattered into the Oort cloud by the giant planets earlier in the Solar System’s history, and later re-appear with small perihelia following perturbations to their orbits induced by nearby stars and the Galactic tide. Further details and subtleties of this dynamical classification can be found in, e.g., Dones et al (2015). Over the past few decades we have also made great strides in characterising both the populations and the dynamical and collisional conditions within the Solar System’s source reservoirs, with the number of known Trans-Neptunian Objects (TNOs) growing from one (the binary Pluto–Charon system) in 1990 to many thousands at present. The detected TNOs, however, are much larger than typical cometary nuclei owing to detection biases: we still lack a census
1This could include tidal disruption, as is likely the case for some bodies orbiting white dwarfs.
ital timescales, see Vrignaud et al (2026, this issue). We begin the work by discussing the different dynamical mechanisms that have been proposed to move bodies out of their debris disc reservoirs to small periapsides (Section 2). We then discuss the long-term evolution of the source reservoirs, both by the aforementioned dynamical processes as well as by collisions between small bodies, which are unimportant in the present TNO and Oort Cloud populations in the Solar System
2Specifically, we mean interior to the orbit of Jupiter, although some comets do show activity at larger heliocentric distances.

but are significant in observable extra-solar debris discs (Section 3). Following that, we discuss the dynamics of the Oort Cloud and exo-Oort Clouds (Section 4), where previously we focused on delivery from flatter disc populations. After that, we briefly discuss our state of knowledge surrounding direct observations that can probe these dynamical links in specific cases (Section 5). We then switch our attention to discuss the evolution of small bodies as individual objects. In Section 6 we discuss nongravitational forces acting on small bodies to change their orbits and spin states, as well as tidal disruption as an ultimate end state. We then discuss the physical processes affecting small bodies in themselves, rather than their orbits, discussing storage and the transition to activity, followed by their death or dormancy (Section 7). These processes are best studied for the Solar System, where a succession of space missions have visited comets to study them as geological bodies. We follow this with a description of the three hitherto-detected interstellar objects (ISOs), both as individual objects, and looking ahead what we might learn from statistical studies of the Galactic kinematics of ISOs about minor body formation in different stellar populations (Section 8). Finally, we turn our attention to how exocometary bodies and reservoirs are affected by the evolution of the host star. Stellar winds are discussed in Section 9 and Appendix A. Small body evolution around giant branch stars is discussed in Section 10, and around white dwarfs (WDs) in Section 11. WDs are now known to display a host of phenomena related to cometary activity: asymmetric transits, the existence of dust on close-in orbits, and the deposition of material into the WD atmosphere. While it is unclear whether the original composition of the bodies responsible for these phenomena is volatile-rich or volatile-poor, their delivery from a source region to close to the WD is a problem closely related to the delivery of comets around main sequence stars, and we discuss them here without prejudice. We finish with a list of open questions (Section 12) and conclusions (Section 13).
For uniform activity, the symmetry of all shapes in the last
observation corresponds to an increasing (decreasing) rotation
period before (after) the first equinox of the 2015 apparition of
comet 67P/C-G as described by Keller et al. (2015a). Eq. (A.2)
x × ν. This relation does not transfer to the complete integrals
distributed surface activity. For southern irradiation conditions
argument for northern irradiation conditions (and positive SSL)
to Fig. 9 for the bilobed shape. The appropriate weights for the
superposition in Eq. (8) will be able to create torque formation
in Sect. 3.1 is independent of the specific shape, Eq. (14) is true
for shape 67P as well.

-1,-1,-1 1,-1,-1
1,1,-1 -1,1,-1
-1,-1,1 1,-1,1
1,1,1 -1,1,1
135° 90° 45°
s for T
0° 45° 90° 135°
45° 30° 15° 0° 15° 30° 45° subsolar latitude of rs
-1,-1,-1 1,-1,-1
1,1,-1 -1,1,-1
-1,-1,1 1,-1,1
1,1,1 -1,1,1
90° 60° 30°
s for T
0° 30° 60° 90°
45° 30° 15° 0° 15° 30° 45° subsolar latitude of rs

[Figure: Fig. 10. Direction of torque, T, for the shape 67P. Torque, T, in Eq. (12) is shown with model A and fEAF = χAi, j,k for region Ai,j,k in Eq. (6). Uniform activity fEAF = 1 is shown with dotted black lines. λs and ϕs denote longitude and latitude for T with respect to the solar basis in Fig. 2. The solar vector, rs, changes SSL from −45◦to 45◦.]