arXiv subjects

Christiane Helling

Publications and source records attributed to Christiane Helling.

At least 19 recordsLinked to original sources

arXiv2026

The refractory fraction of phosphorus in planet-forming discs

Context. Phosphorus (P) is an essential element for life on Earth and a potential tracer of planet formation history. However, there has been no detection of P-bearing molecules in protoplanetary discs so far. Herbig Ae/Be stars constantly accrete matter from their pro- toplanetary disc, which alters the composition of the stellar photosphere due to their shallow convective, or fully radiative, envelope. The altered surface composition reflects the composition of the accreting matter, and thus that of the inner protoplanetary disc. This accretion contamination of stellar photosphere can persist after accretion has ended in young A and B-type stars (age < 50 Myr). Aims. We aim to quantify the fraction of P locked in dust (the refractory fraction of P) compared to gas in the inner protoplanetary disc around Herbig Ae/Be stars. Methods. We measure the stellar parameters and abundance of 5 Herbig Ae/Be stars using optical and UV spectra, to compare their P and Fe abundances. We also used a 20 Myrs old main sequence B-type star, which has P and Fe abundance estimated from optical spectrum. Fe is assumed to be completely locked in refractory reservoirs in the inner disc. A parameterised relationship between the stellar P and Fe abundance gives the fraction of P locked in refractory reservoirs. Results. We find the refractory fraction of P in the inner protoplanetary disc to be > 96 % within 95th percentile of the posterior distribution. Conclusions. Consistent with a previous finding in the HD 100546 system, we conclude most of the P in the inner protoplanetary disc is locked in dust, likely in refractory minerals like schreibersite or apatite. Our result, combined with the low cosmic abundance of P, is also consistent with the lack of infrared and mm-wavelength observations of P-bearing molecules in protoplanetary discs to date.

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arXiv2026

Chemical Tracers for 3D Atmospheric Asymmetries on WASP-69 b

Warm giant exoplanets exhibit strong three-dimensional temperature contrasts that can significantly alter atmospheric chemistry through quenching and photochemistry, yet transmission spectra are commonly interpreted using one-dimensional, limb-averaged models. Such simplifications may bias inferred atmospheric properties, particularly metallicity and C/O ratio. In this work we investigate the relative influence of atmospheric composition and three-dimensional thermal structure on atmospheric chemistry and transmission spectra using WASP-69b as a test case. WASP-69b is a ~900K warm Saturn, residing in a thermal regime especially sensitive to disequilibrium chemistry. We use three-dimensional general circulation model derived pressure-temperature profiles as inputs for a one-dimensional photochemical-kinetics model to resolve longitudinal and latitudinal chemical asymmetries across the atmosphere. We find that CH4 exhibits strong latitudinal variations linked to deep quench temperatures, while SO2 shows longitudinal asymmetries driven by upper-atmospheric photochemistry and irradiation geometry. In contrast, CO2 remains comparatively insensitive to spatial thermal variations and emerges as a robust tracer of atmospheric metallicity. Synthethic transmission spectra reveal that three-dimensional chemical asymmetries can produce spectral variations comparable to those induced by metallicity itself, demonstrating that limb-averaged interpretations can mask substantial spatial structure in warm giant exoplanet atmospheres.

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arXiv2026

The Tartu Observatory Fiber-fed Echelle Spectrograph (TOFES) Data Reduction Pipeline

We introduce the data reduction pipeline for the Tartu Observatory Fiber-fed Echelle Spectrograph (TOFES). TOFES is installed in the Coud\'e room and will be connected to the 1.5 m Tartu Observatory AZT-12 telescope through a four-channel instrument adapter to be mounted at the Cassegrain focus of the telescope. The spectrograph has an average spectral resolution of 30,000 and covers the 390 to 900 nm wavelength band in a single exposure. The data reduction pipeline, based on the PyReduce package, was tested on spectra of the Sun. We also present the Spectroscopy-Toolbox package, which was developed to provide additional tools for diagnostics and spectral line identification for radial velocity measurements. The spectrograph will address a range of scientific questions, including the stellar characterisation of Herbig AeBe stars to measure accretion contamination from their protoplanetary disks, the stellar characterisation of exoplanet host-stars including the Ariel space mission targets, and radial velocity monitoring of large-scale atmospheric variability in massive stars.

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arXiv2026

Phase-dependent chemistry of WASP-43 b revealed with a suite of one-, two-, and three-dimensional models

Our goal is to investigate the chemistry of the hot Jupiter WASP-43 b in detail using theoretical models, considering the constraints of the James Webb Space Telescope MIRI phase curve. With a suite of pseudo-two-dimensional and three-dimensional photochemical models, we simulate the composition of WASP-43 b in various configurations, and compare them with atmospheric retrieval models. We confirm that disequilibrium chemistry in our theoretical models reduces the methane concentration on the planet night side for wind jet speeds > 500 m/s. Varying the metallicity in the models induces large changes in the CO$_2$ and SO$_2$ concentrations, with SO$_2$ producing mid-infrared absorption features in synthetic emission spectra of the night side at atmospheric metallicities > 10x solar. Our models provide evidence for pole-to-equator circulation enhancing the CH$_4$, NH$_3$, and HCN abundances, which is nonetheless insufficient for detectable spectral features. Finally, we show that H$_2$O, CO, and CO$_2$ are robustly modeled, but species affected by photochemistry are more sensitive to model-specific assumptions and pathways. We conclude that horizontal quenching is the prime mechanism that explains the non-detection of methane in the MIRI phase-curve of WASP-43 b. This mechanism requires only moderate wind speeds and is operative at various thermal structures and atmospheric metallicities. Furthermore, coupled carbon-sulfur chemistry leads to an additional decrease in methane compared to previous models in the literature that did not contain sulfur chemistry. We do not favor a high metallicity as it would have led to observable SO$_2$ features in the MIRI spectra. Our study shows that phase-dependent photochemistry models are essential tools in the interpretation of hot-Jupiter phase curves, but benchmarking is needed to improve the accuracy of photochemical models in the future.

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arXiv2026

The panchromatic JWST dayside spectrum of WASP-121 b reveals a refractory-rich formation

One path to understand how planets form is to link their present-day atmospheric composition to predictions from planet formation models. For the hottest planets, the abundances of refractory species can provide a useful formation tracer, complementing the traditionally used C/O and overall metallicity. Here we investigate the refractory abundance in the atmosphere of the ultra-hot Jupiter WASP-121 b, combining new JWST MIRI/LRS observations with archival NIRSpec/G395H and NIRISS/SOSS data to obtain a panchromatic dayside emission spectrum from 0.6 to 12 $\mu$m. Our retrieval analysis detects the refractory tracer SiO gas at high confidence, in addition to previously detected volatile species. The atmosphere is enriched in volatile and refractory species, with enhanced refractory-to-volatile ratios of Si/O=$3.54^{+0.86}_{-0.69}$x stellar and Si/C=$3.05^{+1.12}_{-0.80}$x stellar, relative to new stellar abundance constraints from ESPRESSO data. In addition, we confirm the depletion of TiO and the need for an additional source of reflected light opacity with a geometric albedo of $0.22\pm0.03$. The retrieved dayside temperature profile has a strong inversion layer, with a more complex structure than standard parameterizations can accommodate, and an eclipse map analysis indicates a small eastward hotspot offset of $4.8^{+2.7\circ}_{-2.8}$. Comparing our results with models of planet formation, we find that the measured enrichment pattern was shaped by accretion from multiple reservoirs, either through a mixture of solid and gas accretion interior to the water ice line or through continued solid accretion during inward migration from farther out in the disk. Finally, we model the planet's dynamical history and find that it could reach its current high-obliquity orbit as a consequence of a post-formation dynamical event, such as planet-planet scattering or von Zeipel-Lidov-Kozai cycles.

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arXiv2026

Metal Oxide Clusters in Gas Giant Exoplanet Atmospheres

This study investigates the thermal stability and absorption of metal oxide clusters in exoplanetary atmospheres. Utilizing our thermochemical data, we analyze eight distinct cluster families: magnesium oxide (MgO), silicon monoxide (SiO), titanium monoxide (TiO), vanadium monoxide (VO), titanium dioxide (TiO$_2$), vanadium dioxide (VO$_2$), aluminum oxide (Al$_2$O$_3$), and vanadium pentoxide (V$_2$O$_5$). Equilibrium cluster populations as a function of gas temperature and pressure reveal distinct stability regimes. Under solar elemental abundances, (TiO$_2$)$\rm\rm_N$ and (Al$_2$O$_3$)$\rm_N$ are favored at higher temperatures, while (MgO)$\rm_N$ and (SiO)$\rm_N$ dominate at lower temperatures. Computed absorption spectra exhibit strong size- and composition-dependent absorption features in the mid-infrared (8--50~$\mu$m), many of which fall within the wavelength range accessible to \texttt{JWST/MIRI}. We further coupled cluster thermodynamics with 3D general circulation model (GCM) outputs to investigate the cluster stability across the ultra-hot Jupiters (UHJs) WASP-121 b and WASP-18 b, the hot Jupiter (HJ) WASP-39 b, and the warm Jupiter (WJ) WASP-69 b. In WASP-121 b and WASP-18 b, extreme dayside temperatures suppress large-cluster stability, yielding atmospheres dominated by metal ions at low pressures and neutral metals at depth, with limited cluster survival on the nightside and morning terminator. In WASP-39 b, larger clusters are not thermochemically favoured despite the enhanced metallicity; instead, equilibrium chemistry stabilises smaller species, with only TiO showing a tendency toward stable larger cluster forms, likely due to its open d-orbitals. In contrast, WASP-69 b favors the formation of larger metal oxide clusters across an extended pressure range, highlighting WJs as a favorable environment for metal oxide cluster stability.

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arXiv2026

Inhomogeneous magnetic coupling in exoplanets: the stop & go of WASP-18 b's atmospheric flows

Early studies of ionization in hot Jupiter atmospheres suggest that magnetic coupling can shape their dynamics. These effects may be most pronounced in ultra-hot Jupiters that sustain global magnetic fields. WASP-18 b hosts an ionized dayside atmosphere extending deep enough to be strongly influenced by magnetic forces. Phase curve observations suggest effective magnetic drag, yet its impact on the atmospheric circulation remains poorly constrained. This work explores how magnetic drag in an inhomogeneously ionized atmosphere shapes local and global dynamics to provide a pathway to constrain the planet's magnetic field strength. An analytical parameterization for anisotropic magnetic drag, including both Pedersen and Hall drag components, and associated frictional heating in the globally neutral atmosphere, is implemented in the 3D General Circulation Model ExoRad to study WASP-18 b's atmosphere. Climate characteristics are compared for different drag formulations to assess whether anisotropic physics is required to capture magnetic coupling effects. Anisotropic magnetic drag and frictional heating, both set by local ionization, strongly affect wind strength and direction in the upper atmosphere, modify the day-night circulation, and produce observable temperature asymmetries. They enhance the evening-morning terminator temperature difference near 0.1 bar and generate two off-equator hotspots with reduced eastward shift. The terminator regions are particularly sensitive to how magnetic drag is modeled. Anisotropic magnetic drag damps and redirects dayside-to-nightside winds, partially decoupling the equatorial flow at the morning terminator while maintaining the nightside jet. Locally varying drag forces and frictional heating create asymmetric temperature patterns manifesting as primary and secondary hotspot regions.

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arXiv2025

Direct imaging characterization of cool gaseous planets

Cool gas giant exoplanets, particularly those with properties similar to those of Jupiter and Saturn, remain poorly characterized due to current observational limitations. This white paper outlines the transformative science case for the Habitable Worlds Observatory (HWO) to directly image and spectroscopically characterize a broad range of gaseous exoplanets with effective temperatures below 400 K. The study focuses on determining key atmospheric properties, including molecular composition, cloud and haze characteristics, and temperature structure, across planets of varying sizes and orbital separations. Leveraging reflected light spectroscopy and polarimetry, HWO will enable comparative planetology of cool gas giants orbiting both solar-type and M-dwarf stars, bridging the observational gap between hot exoplanets and Solar System giants. We present observational requirements and survey strategies necessary to uncover correlations between atmospheric properties and planetary or stellar parameters. This effort will establish critical constraints on planetary formation, cloud microphysics, and the role of photochemistry under diverse irradiation conditions. The unique capabilities of HWO will make it the first facility capable of characterizing true exo-Jupiters in reflected light, thus offering an unprecedented opportunity to place the Solar System in a broader galactic context.

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arXiv2025

Exoplanet climate characterization with transit asymmetries -- A comprehensive population study from the optical to the infrared

Space missions (CHEOPS, JWST, PLATO) facilitate detailed characterization of exoplanets. This work provides a framework to characterize cloud and climate properties of close-in gas giants via transit depth asymmetries from the optical to the infrared (0.33 ...10 $\mu$m). The AFGKM ExoRad 3D GCM grid provides gas temperature profiles for an ensemble of 50 tidally locked gaseous planets orbiting diverse host stars. It is combined with a detailed kinetic cloud formation model. The end result is a set of synthetic transit spectra and evening-to-morning transit asymmetries that span climate regimes: warm (T=800 K ... 1000K), intermediately hot (T=1200 K ... 2000 K) and ultrahot (T =2200 K ... 2600 K). WASP-39b observations suggest iron-free clouds with less abundant cloud condensation nuclei than previously expected. The ensemble study shows that clouds increase transit limb differences due to asymmetries in cloud coverage and by enhancing horizontal differences in the gas temperatures. For hot planets, evening-to-morning differences of up to 150 ppm are suggested in the optical and 100 ppm in the infrared (2-8 micron). For ultra-hot Jupiters, evening-to-morning transit differences are dominated by the morning cloud for a cloud-free evening limb: They are strongly negative in the PLATO band (0.5-1~$\mu$m, -500 ppm), moderately negative in the near-infrared (1-1.5~$\mu$m, -200 ppm) and moderately positive (+100 ppm) for $\lambda > 2\mu$m. For a partly cloudy evening terminator, the evening-to-morning transit asymmetry is moderately positive in the whole wavelength range. Warm Jupiter planets exhibit negligible transit asymmetries. PLATO and JWST transit asymmetry observations between 1-2 $\mu$m are optimal to characterize cloudy planetary atmospheres around K -A stars. JWST observations are most effective for M star planets with transit differences > +500 ppm for 8-10 $\mu$m.

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arXiv2025

Limb Asymmetries on WASP-39b: A Multi-GCM Comparison of Chemistry, Clouds, and Hazes

With JWST, observing separate spectra of the morning and evening limbs of hot Jupiters has finally become a reality. The first such observation was reported for WASP-39b, where the evening terminator was observed to have a larger transit radius by about 400 ppm and a stronger 4.3 $\mu$m CO$_2$ feature than the morning terminator. Multiple factors, including temperature differences, photo/thermochemistry, clouds and hazes, could cause such limb asymmetries. To interpret these new limb asymmetry observations, a detailed understanding of how the relevant processes affect morning and evening spectra grounded in forward models is needed. Focusing on WASP-39b, we compare simulations from five different general circulation models (GCMs), including one simulating disequilibrium thermochemistry and one with cloud radiative feedback, to the recent WASP-39b limb asymmetry observations. We also post-process the temperature structures of all simulations with a 2D photochemical model and one simulation with a cloud microphysics model. Although the temperatures predicted by the different models vary considerably, the models are remarkably consistent in their predicted morning--evening temperature differences. Several equilibrium-chemistry simulations predict strong methane features in the morning spectrum, not seen in the observations. When including disequilibrium processes, horizontal transport homogenizes methane, and these methane features disappear. However, even after including photochemistry and clouds, our models still cannot reproduce the observed ${\sim}2000$ ppm asymmetry in the CO$_2$ feature. A combination of factors, such as varying metallicity and unexplored parameters in cloud models, may explain the discrepancy, emphasizing the need for future models integrating cloud microphysics and feedback across a broader parameter space.

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arXiv2025

Prediction of sulphate hazes in the lower Venus atmosphere

We study the amount, size distribution and material composition of (sub-)mic aerosol particles in the lower Venus atmosphere < 50 km. Our GGchem phase-equilibrium model predicts metal-chloride and metal-fluoride molecules to be present in the gas over the Venus surface in trace concentrations < 2.E-12, in particular FeCl2, NaCl, KCl and SiF4. Using an improved version of the DiffuDrift model developed by Woitke et al.2020, we find that these molecules deposit to form solid potassium sulphate K2SO4, sodium sulphate Na2SO4, and pyrite FeS2 above about 15.5 km, 9.5 km and 2.4 km, respectively. These heights coincide well with the three potential haze layers found in the Pioneer Venus Large Probe neutral mass spectrometer data by Mogul et al.2023. The particles with radius < 0.3 mic can be dredged up from the ground to reach the sulphuric acid cloud base from below by diffusion. The particle density decreases from ~ 5000/cm3 at ground level to ~100/cm3 at a height of 45 km. Particles larger than about 1 mic are found to stay confined to the ground < 10 km, indicating that the larger, so-called mode 3 particles, if they exist, cannot originate from the surface. All particles are expected to be coated by a thin layer of FeS2, Na2SO4 and K2SO4. We have included the repelling effect of particle charges on the coagulation, without which the model would predict much too steep gradients close to the surface, which is inconsistent with measured opacity data. Our models suggest that the particles must have at least 100 negative charges per micron of particle radius at ground level, and > 50/mic at a height of 45 km.

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arXiv2025

Accelerating exoplanet climate modelling: A machine learning approach to complement 3D GCM grid simulations

With the development of ever-improving telescopes capable of observing exoplanet atmospheres in greater detail and number, there is a growing demand for enhanced 3D climate models to support and help interpret observational data from space missions like CHEOPS, TESS, JWST, PLATO, and Ariel. However, the computationally intensive and time-consuming nature of general circulation models (GCMs) poses significant challenges in simulating a wide range of exoplanetary atmospheres. This study aims to determine whether machine learning (ML) algorithms can be used to predict the 3D temperature and wind structure of arbitrary tidally-locked gaseous exoplanets in a range of planetary parameters. A new 3D GCM grid with 60 inflated hot Jupiters orbiting A, F, G, K, and M-type host stars modelled with Exorad has been introduced. A dense neural network (DNN) and a decision tree algorithm (XGBoost) are trained on this grid to predict local gas temperatures along with horizontal and vertical winds. To ensure the reliability and quality of the ML model predictions, WASP-121 b, HATS-42 b, NGTS-17 b, WASP-23 b, and NGTS-1 b-like planets, which are all targets for PLATO observation, are selected and modelled with ExoRad and the two ML methods as test cases. The DNN predictions for the gas temperatures are to such a degree that the calculated spectra agree within 32 ppm for all but one planet, for which only one single HCN feature reaches a 100 ppm difference. The developed ML emulators can reliably predict the complete 3D temperature field of an inflated warm to ultra-hot tidally locked Jupiter around A to M-type host stars. It provides a fast tool to complement and extend traditional GCM grids for exoplanet ensemble studies. The quality of the predictions is such that no or minimal effects on the gas phase chemistry, hence on the cloud formation and transmission spectra, are to be expected.

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arXiv2025

Can thermodynamic equilibrium be established in planet-forming disks?

The inner regions of planet-forming disks are warm and dense. The chemical networks used for disk modelling so far were developed for a cold and dilute medium and do not include a complete set of pressure-dependent reactions. The chemical networks developed for planetary atmospheres include such reactions along with the inverse reactions related to the Gibb's free energies of the molecules. The chemical networks used for disk modelling are thus incomplete in this respect. We want to study whether thermodynamic equilibrium can be established in a planet-forming disk. We identify the regions in the disk most likely to reach thermodynamic equilibrium and determine the timescale over which this occurs. We employ the theoretical concepts used in exoplanet atmosphere chemistry for the disk modelling with PROtoplanetary DIsk MOdel ({\sc ProDiMo}). We develop a chemical network called CHemistry Assembled from exoplanets and dIsks for Thermodynamic EquilibriA ({\sc ChaiTea}) that is based on the UMIST 2022, STAND, and large DIscANAlysis (DIANA) chemical networks. It consists of 239 species. From the STAND network, we adopt the concept of reversing all gas-phase reactions based on thermodynamic data. We use single-point models for a range of gas densities and gas temperatures to verify that the implemented concepts work and thermodynamic equilibrium is achieved in the absence of cosmic rays and photoreactions including radiative associations and direct recombinations. We then study the impact of photoreactions and cosmic rays that lead to deviations from thermodynamic equilibrium. We explore the chemical relaxation timescales towards thermodynamic equilibrium. Lastly, we study the predicted 2D chemical structure of a typical T\,Tauri disk when using the new {\sc ChaiTea} network instead of the large DIANA standard network, including photorates, cosmic rays, X-rays, and ice....

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arXiv2025

Grid-based exoplanet atmospheric mass loss predictions through neural network

The fast and accurate estimation of planetary mass-loss rates is critical for planet population and evolution modelling. We use machine learning (ML) for fast interpolation across an existing large grid of hydrodynamic upper atmosphere models, providing mass-loss rates for any planet inside the grid boundaries with superior accuracy compared to previously published interpolation schemes. We consider an already available grid comprising about 11000 hydrodynamic upper atmosphere models for training and generate an additional grid of about 250 models for testing purposes. We develop the ML interpolation scheme (dubbed "atmospheric Mass Loss INquiry frameworK"; MLink) using a Dense Neural Network, further comparing the results with what was obtained employing classical approaches (e.g. linear interpolation and radial basis function-based regression). Finally, we study the impact of the different interpolation schemes on the evolution of a small sample of carefully selected synthetic planets. MLink provides high-quality interpolation across the entire parameter space by significantly reducing both the number of points with large interpolation errors and the maximum interpolation error compared to previously available schemes. For most cases, evolutionary tracks computed employing MLink and classical schemes lead to comparable planetary parameters at Gyr-timescales. However, particularly for planets close to the top edge of the radius gap, the difference between the predicted planetary radii at a given age of tracks obtained employing MLink and classical interpolation schemes can exceed the typical observational uncertainties. Machine learning can be successfully used to estimate atmospheric mass-loss rates from model grids paving the way to explore future larger and more complex grids of models computed accounting for more physical processes.

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arXiv2025

Kinetic and photochemical disequilibrium in the potentially carbon-rich atmosphere of the warm-Jupiter WASP-69b

High-resolution transmission spectroscopy of the warm gas-giant WASP-69b has revealed the presence of H2O, CO, CH4, NH3, and C2H2 in its atmosphere. This study investigates the impact of vertical diffusion and photochemistry on its atmospheric composition, with a focus on the detected species plus HCN and CO2, to constrain the atmospheric C/O ratio. We utilize non-equilibrium gas-phase simulations to conduct a parameter study for vertical diffusion strength, local gas temperature, and C/O ratio. Our results indicate that a carbon-rich atmosphere enhances CH4 and C2H2 concentrations, while NH3 undergoes chemical conversion into HCN in carbon-rich, high-temperature environments. Consequently, HCN is abundantly produced in such atmospheres, though its strong spectral features remain undetected in WASP-69b. Photochemical production of HCN and C2H2 is highly sensitive to vertical diffusion strength, with weaker diffusion resulting in higher concentrations. Cross-correlation of synthetic spectra with observed data shows that models with C/O=2 best match observations, but models with C/O=0.55 and 0.9 lead to statistically equivalent fits, leaving the C/O ratio unconstrained. We highlight the importance of accurately modeling NH3 quenching at pressures greater than 100 bars. Models for WASP-69b capped at 100 bars bias cross-correlation fits towards carbon-rich values. We suggest that if the atmosphere of WASP-69b is indeed carbon-rich with a solar metallicity, future observations should reveal the presence of HCN.

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arXiv2025

The $\texttt{MSG}$ model for cloudy substellar atmospheres: A grid of self-consistent substellar atmosphere models with microphysical cloud formation

State-of-the-art JWST observations are unveiling unprecedented views into the atmospheres of substellar objects in the infrared, further highlighting the importance of clouds. Current forward models struggle to fit the silicate clouds absorption feature at ~$10\,\mu$m observed in substellar atmospheres. In the MSG model, we aim to couple the MARCS 1D radiative-convective equilibrium atmosphere model with the 1D kinetic, stationary, non-equilibrium, cloud formation model DRIFT, to create a new grid of self-consistent cloudy substellar atmosphere models with microphysical cloud formation. We aim to test if this new grid is able to reproduce the silicate cloud absorption feature at ~$10\,\mu$m. We model substellar atmospheres with effective temperatures in the range 1200-2500 K and with $\log(g)=4.0$. We compute atmospheric structures that self-consistently account for condensate cloud opacities based on microphysical properties. We present an algorithm based on control theory to help converge such self-consistent models. Synthetic atmosphere spectra are computed for each model to explore the observable impact of the cloud microphysics. We additionally explore the impact of choosing different nucleation species (TiO$_2$ or SiO) and the effect of less efficient atmospheric mixing on these spectra. The new MSG cloudy grid using TiO$_2$ nucleation shows spectra which are redder in the near-infrared compared to the currently known population of substellar atmospheres. We find the models with SiO nucleation, and models with reduced mixing efficiency are less red in the near-infrared. The grid is unable to reproduce the silicate features similar to those found in recent JWST observations and Spitzer archival data. We thoroughly discuss further work that may better approximate the impact of convection in cloud-forming regions and steps that may help resolve the silicate cloud feature.

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arXiv2024

From CO$_2$- to H$_2$O-dominated atmospheres and back -- How mixed outgassing changes the volatile distribution in magma oceans around M dwarf stars

We investigate the impact of CO$_2$ on TRAPPIST-1 e, f and g during the magma ocean stage. These potentially habitable rocky planets are currently the most accessible for astronomical observations. A constraint on the volatile budget during the magma ocean stage is a link to planet formation and also needed to judge their habitability. We perform simulations with 1-100 terrestrial oceans (TO) of H$_2$O with and without CO$_2$ and for albedos 0 and 0.75. The CO$_2$ mass is scaled with initial H$_2$O by a constant factor between 0.1 and 1. The magma ocean state of rocky planets begins with a CO$_2$-dominated atmosphere but can evolve into a H$_2$O dominated state, depending on initial conditions. For less than 10 TO initial H$_2$O, the atmosphere tends to desiccate and the evolution may end with a CO$_2$ dominated atmosphere. Otherwise, the final state is a thick (>1000 bar) H$_2$O-CO$_2$ atmosphere. Complete atmosphere desiccation with less than 10 TO initial H$_2$O can be significantly delayed for TRAPPIST-1e and f, when H$_2$O has to diffuse through a CO$_2$ atmosphere to reach the upper atmosphere, where XUV photolysis occurs. As a consequence of CO$_2$ diffusion-limited water loss, the time of mantle solidification for TRAPPIST-1 e, f, and g can be significantly extended compared to a pure H$_2$O evolution by up to 40 Myrs for albedo 0.75 and by up to 200 Mrys for albedo 0. The addition of CO$_2$ further results in a higher water content in the melt during the magma ocean stage. Our compositional model adjusted for the measured metallicity of TRAPPIST-1 yields for the dry inner planets (b, c, d) an iron fraction of 27 wt-%. For TRAPPIST-1 e, this iron fraction would be compatible with a (partly) desiccated evolution scenario and a CO$_2$ atmosphere with surface pressures of a few 100 bar. A comparative study between TRAPPIST-1 e and the inner planets may yield the most insights about formation and evolution scenarios.

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arXiv2024

Machine learning-based classification for Single Photon Space Debris Light Curves

The growing number of man-made debris in Earth's orbit poses a threat to active satellite missions due to the risk of collision. Characterizing unknown debris is, therefore, of high interest. Light Curves (LCs) are temporal variations of object brightness and have been shown to contain information such as shape, attitude, and rotational state. Since 2015, the Satellite Laser Ranging (SLR) group of Space Research Institute (IWF) Graz has been building a space debris LC catalogue. The LCs are captured on a Single Photon basis, which sets them apart from CCD-based measurements. In recent years, Machine Learning (ML) models have emerged as a viable technique for analyzing LCs. This work aims to classify Single Photon Space Debris using the ML framework. We have explored LC classification using k-Nearest Neighbour (k-NN), Random Forest (RDF), XGBoost (XGB), and Convolutional Neural Network (CNN) classifiers in order to assess the difference in performance between traditional and deep models. Instead of performing classification on the direct LCs data, we extracted features from the data first using an automated pipeline. We apply our models on three tasks, which are classifying individual objects, objects grouped into families according to origin (e.g., GLONASS satellites), and grouping into general types (e.g., rocket bodies). We successfully classified Space Debris LCs captured on Single Photon basis, obtaining accuracies as high as 90.7%. Further, our experiments show that the classifiers provide better classification accuracy with automated extracted features than other methods.

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