EXOA8
Determining the stable phase of the binary rock-ice mixture at extreme conditions is crucial for structure and evolution models. Yet, research into rock-ice interactions at pressure and temperature conditions exceeding those found on Earth remains limited. The discovery of new exoplanets points to some of them having substantial water abundance, implying that the interaction between an overlying layer of ice and the underlying rock would occur under several megabar of pressure. We determine the solvus temperatures for magnesium silicates and water across pressures relevant to the deep interiors of super-Earth to sub-Neptune sized bodies by atomistic simulations. Using density functional theory molecular dynamics simulations, we investigate the miscibility of magnesium silicates (MgSiO3 and MgO) and water ice (H2O) up to 8000 K and from 0.3-2 Mbar, using a heat-until-it-mixes approach to determine liquidus conditions. Our findings reveal that MgSiO3 becomes miscible in H2O upon melting in the entire pressure range we explored. Surprisingly, we observe a significant depression in the melting point of MgO by over 2000 K in the presence of H2O, highlighting complex interactions between rock and water at extreme conditions. These findings have implications for structure and evolution models, including those of the deep interiors of the ice giants, as well as for considerations ofplanet habitability.
How to cite: Kovacevic, T., González-Cataldo, F., and Militzer, B.: Simulations of Rock-Ice Mixtures in the mantles of water-rich planets, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-97, https://doi.org/10.5194/epsc2024-97, 2024.
Water is expected to be abundant component in planetary interiors, particularly in sub-Neptune planets, whose radii suggest the presence of volatiles in their atmospheres. However, directly observing the precise water mass fraction and water distribution remains unfeasible. In our study, we employ an internal structure code to model planets with high water content and explore potential interior distributions. Departing from traditional assumptions of a layered structure, we determine water and rock distribution based on water-rock miscibility criteria. We model wet sub-Neptunes with an iron core and a homogeneous mixture of rock and water above it. At the outer regions of the planet, the pressure and temperature decrease below the rock-water miscibility point (the second critical point), causing the segregation of water and rock. Consequently, a shell of water is formed in the outermost layers, resulting in a subsequent manifestation as a gaseous water atmosphere. By considering the water-rock miscibility and the gaseous state of water, our approach holds significant implications for estimating the water mass fraction of detected exoplanets.
We model two extreme cases: a fully homogeneous mass-rock envelope surrounding an iron core, and a more traditional three-layer structure where water and rock are separated. In both cases, the outermost water layers form an atmosphere.
With various equilibrium temperatures and masses, assuming different structures, we calculate different radii for various scenarios. Planetary interiors are modeled using a modified version of the Magrahtea code (Huang et al., 2022). With these tools, we model the internal structure of a sample of exoplanets (L 98-59 d, TOI-1685 b, TOI-776 b, TOI-270 d, K2-146 b, K2-146 c).
How to cite: Lozovsky, M. and Vazan, A.: Internal structure of Water-rich planets, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-150, https://doi.org/10.5194/epsc2024-150, 2024.
The magma ocean (MO) phase typically describes the early stage of rocky planets, during which the entire planet is molten due to heat generated by accretion processes. In the case of short-period exoplanets inside the runaway greenhouse limit, this phase may last Gyrs, until the inventory of major greenhouse gasses, such as H2O and H2, is exhausted. The internal evolution of these planets is influenced by various factors, including the exchange of volatiles between the molten planetary interior and the atmosphere. This exchange significantly impacts planetary climate, exoplanet bulk densities, surface conditions , and long-term geodynamic activity by controlling greenhouse effects, surface water stability, and atmospheric composition. This research focuses on modeling this interaction under different redox conditions. Using a coupled computational framework of the planetary interior and atmosphere, we study the detailed evolution of the magma oceans phase, aiming to understand the crystallization sequence and the resulting internal structure of the planet. We investigate the impact of the cooling sequence and evolving climatic conditions on mantle differentiation, mineralogy, formation of crusts, and the consequent composition of the atmosphere.
How to cite: Sastre, M., Lichtenberg, T., Nicholls, H., Bower, D., and Kamp, I.: Interior Evolution of Magma Oceans Exoplanets, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-459, https://doi.org/10.5194/epsc2024-459, 2024.
Studying planetary habitability has become a major emerging research area, with critical implications for future exoplanet exploration and ambitious ground- and space-based telescopes. Efforts to design and optimize these missions have been focusing on maximizing the planet yield – the number of exoplanets a survey will be able to characterize – which is not necessarily equivalent to science return. We present Bioverse, a framework to quantify the diagnostic power of nextgeneration exoplanet surveys Bioverse allows to assess the detectability of population-level trends injected in simulated planet populations. Here, we apply Bioverse to explore the requirements for a mission to probe and characterize the inner edge of the habitable zone. We show that, through probing a discontinuity in the distribution of planetary radii and bulk densities caused by the runaway greenhouse transition, the PLATO mission will likely be able to constrain this demographic feature. This will constitute the first empirical test of the habitable zone concept.
We further use Bioverse to demonstrate how contextual information about a planet with a biosignature detection, such as its orbit or properties of its host star, lend or take away credibility from competing models of abiogenesis. We demonstrate that planet sample sizes ≥100 enable a strong test of a predicted correlation between past received nearultraviolet flux and the occurrence of biosignatures in the cyanosulfidic scenario for the origin of life.
Probabilistic assessments that take into account the population context will be critical for an effective search for extraterrestrial life in the Universe and to constrain the origin of life.
Figure 1. Detection of the Habitable Zone Inner Edge Discontinuity. We fit a population-level runaway greenhouse model (red posterior draws) to simulated radius measurements and test this hypothesis against the null hypothesis of an irradiation-independent distribution. In a large (N = 500) planet sample, the discontinuity is detected with high confidence.
References:
Bixel, A., & Apai, D. 2021, The Astronomical Journal, 161, 228, doi: 10.3847/1538-3881/abe042
Dorn, C., & Lichtenberg, T. 2021, ApJL, 922, L4, doi: 10.3847/2041-8213/ac33af
Ranjan, S., Wordsworth, R., & Sasselov, D. D. 2017, Astrobiology, 17, 687, doi: 10.1089/ast.2016.1596
Schlecker, M., Apai, D., Lichtenberg, T., et al., The Planetary Journal, in press. [arXiv:2309.04518]
Turbet, M., Bolmont, E., Chaverot, G., et al. 2021, Nature, 598, 276, doi: 10.1038/s41586-021-03873-w
How to cite: Schlecker, M., Apai, D., Lichtenberg, T., Bergsten, G., Salvador, A., Hardegree-Ullman, K., Affholder, A., Ranjan, S., Ferriere, R., Mazevet, S., and Heng, K.: Bioverse: Probing the Habitable Zone Inner Edge Discontinuity and the Origins of Life, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1374, https://doi.org/10.5194/epsc2024-1374, 2024.
How to cite: Koll, D. D. B. and Lyu, X.: Characterizing rocky exoplanets without atmospheres, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-700, https://doi.org/10.5194/epsc2024-700, 2024.
“Water worlds” - planets with rocky cores overlain by water-rich envelopes - may make up a significant proportion of the sub-Neptune population and their atmospheric characterisation with JWST can offer insights into planetary formation and migration (e.g., Benneke et al. 2024). Whereas colder water worlds may be able to form liquid water oceans and have hydrogen-rich upper atmospheres, warmer planets would contain water in a supercritical state. In this case, hydrogen in the envelope mixes with the supercritical water and the observable upper atmosphere would have a high mean molecular weight with a smaller scale height. In intermediate regimes, a supercritical water layer will lie below a condensing cloud deck and hydrogen-dominated upper atmosphere. In this work, we aim to define the boundary between these three regimes using a 1D radiative-convective model. Our model uses the SOCRATES radiative transfer code coupled to a radiative-convective driver to solve for equilibrium temperature-pressure profiles in a water world atmosphere. We account for the effects of convective inhibition in the condensing layers and the non-idealness of supercritical water at high temperatures and pressures, both of which can dramatically affect the structure of the atmosphere. The resulting framework allows us to demarcate the transition between ocean worlds and sub-Neptunes with a mixed envelope as a function of instellation, interior flux and envelope composition. In the case where water is supercritical, the level at which condensation occurs (and the cold-trapping of water vapour) determines whether the observable atmosphere is hydrogen or water-dominated. We discuss whether the change in composition of the upper atmosphere accompanied by this transition would be observable.
How to cite: Innes, H. and Pierrehumbert, R.: Mapping the transition from liquid to supercritical water on sub-Neptunes, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-723, https://doi.org/10.5194/epsc2024-723, 2024.
Characterizing the interior structure of exoplanets, that is, the size and mass of their main compositional reservoirs, is an essential part in understanding the diversity of observed exoplanets and the processes that govern their formation and evolution. However, the interior of an exoplanet is inaccessible to observations, and can only be investigated via numerical structure models. This poses an inverse problem, where the structure models need to conform to observed parameters. Unlike the planets in the Solar System, for which a wealth of observational data is available, mass and radius often remain the only parameters which can be determined for an exoplanet. Since the relative proportions of iron, silicates, water ice, and volatile elements inside the planet are not known, this poses a highly non-unique problem, where even with accurate radius and mass measurements many different solutions for the internal structure can be found.
Probabilistic inference methods, such as Markov chain Monte Carlo sampling, are a common tool to solve this inverse problem and obtain a comprehensive picture of possible planetary interiors, while also taking into account observational uncertainties. However, these typically require the calculation of hundreds of thousands of interior structures per investigated planet, which makes the characterization of exoplanets a computationally expensive and time-consuming process.
We explore an alternative approach to interior characterization utilizing machine learning. The application of machine learning methods has seen an extensive growth in the geodynamics and planetary science community in recent years, primarily driven by the need to address increasingly complex and computationally and data intensive problems that traditional methods of modeling and analysis struggle to solve. In particular, machine learning offers the opportunity to speed up time-consuming numerical simulations.
We present here ExoMDN, a stand-alone machine-learning model based on mixture density networks (MDNs) that is capable of providing a full probabilistic inference of exoplanet interiors in under a second, without the need for extensive modeling of each exoplanet's interior or even a dedicated interior model. ExoMDN is trained on a large database of 5.6 million precomputed, synthetic interior structures of low mass exoplanets.
The fast prediction times allow investigations into planetary interiors which were not feasible before. We demonstrate how ExoMDN can be leveraged to perform large-scale interior characterizations across the entire population of low-mass exoplanets. We can show how ExoMDN can be used to comprehensively quantify the effect of measurement uncertainties on the ability to constrain the interior of a planet, and to which accuracy these parameters need to be measured to well characterize a planet’s interior.
Training the model on different (potentially) observable parameters allows us to search for parameters which can better constrain the interior. Among these, the inclusion of the fluid Love number k2 helps to significantly reduce the degeneracy of interior structures.
ExoMDN is freely accessible on GitHub at https://github.com/philippbaumeister/ExoMDN
How to cite: Baumeister, P. and Tosi, N.: ExoMDN: Rapid characterization of exoplanets interiors with machine learning, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-493, https://doi.org/10.5194/epsc2024-493, 2024.
The ESA M4 mission Ariel, the atmospheric remote-sensing infrared exoplanet large-survey, has been adopted in 2020 within the Cosmic Vision science programme of ESA. The goal of Ariel is to investigate the atmospheres of planets orbiting distant stars in order to address the fundamental questions on how planetary systems form and evolve and to study in detail the composition of exoplanetary atmospheres. During its 4-year mission, Ariel will observe up to 1000 exoplanets - building on (future) findings from space missions like PLATO, JWST, TESS, and CHEOPS - ranging from Jupiter- and Neptune-size down to super-Earth size, in a wide variety of environments, in the visible and the infrared. The main focus of the mission will be on warm and hot planets in orbits close to their star. Some of the planets may be in the habitable zones of their stars, however. The analysis of Ariel spectra and photometric data will allow to extract the chemical fingerprints of gases and condensates in the planets’ atmospheres, including the elemental composition for the most favourable targets. The Ariel mission has been developed by a consortium of more than 60 institutes from 15 ESA member state countries, including UK, France, Italy, Poland, Spain, the Netherlands, Belgium, Austria, Denmark, Ireland, Hungary, Sweden, Czech Republic, Germany, Portugal, with an additional contribution from NASA and CSA.
How to cite: Lueftinger, T., Tinetti, G., Salvignol, J.-C., and Eccleston, P.: Ariel - The ESA M4 Space Mission to Focus on the Nature Of Exoplanets, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1376, https://doi.org/10.5194/epsc2024-1376, 2024.
In this study, we go beyond the usage of a single modeling approach and employ a range of scalable ML models, including Random Forest (RF), Decision Tree (DT), K-Nearest Neighbors (KNN), and Gradient Boosting (GB). However, to comprehensively evaluate the performance of these ML models, we compare their results with those obtained from the ExoRotGP model. By comparing the outcomes of these ML models with the reference GP results, we aim to rigorously assess their respective abilities in accurately extracting transit and rotation parameters from Kepler light curves. Specifically, we emphasize determining the rotation period of the host star for a given exoplanet. Through this meticulous comparative analysis, we seek to gain valuable insights into the strengths and limitations of different modeling approaches, thereby contributing to the advancement of exoplanet characterization techniques. This approach allows us to explore the diverse perspectives and potential synergies between the ML models and the ExoRotGP model, leading to a more comprehensive understanding of the underlying data and enhancing our ability to uncover important insights from exoplanetary systems.
How to cite: Fazel, F.: Advancing Exoplanet Transit Characterization through Machine Learning, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1088, https://doi.org/10.5194/epsc2024-1088, 2024.
To fulfil its science requirements, the Ariel space mission[1] has been specifically designed to have a stable payload and satellite platform optimised to provide a broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify/characterize clouds and monitor the stellar activity. The chosen wavelength range, from 0.5 to 7.8 µm, covers all the expected major atmospheric gases from, e.g. H2O, CO2, CH4, NH3, HCN, H2S, through to the more exotic metallic compounds, such as TiO, VO, and condensed species.
In the frame of the "Spectral Data and databases" working group, 50+ members of the Ariel science team and colleagues were invited to contribute to a White Paper entitled: "Data availability and requirements relevant for the Ariel space mission and other exoplanet atmosphere applications"[2]. The goal of this 70-pages work submitted for a publication to RASTI is to provide a snapshot of the data availability and data needs primarily for the Ariel space mission, but also for related atmospheric studies of exoplanets and brown dwarfs in general. It covers the following data-related topics: molecular and atomic line lists, line profiles, computed cross-sections and opacities, collision-induced absorption and other continuum data, optical properties of aerosols and surfaces, atmospheric chemistry, UV photodissociation and photoabsorption cross-sections, and standards in the description and format of such data. These data aspects are discussed by addressing the following questions for each topic, based on the experience of the "data-provider" and "data-user" communities: (1) what are the types and sources of currently available data, (2) what work is currently in progress, and (3) what are the current and anticipated data needs. Our aim is to provide practical information on existing sources of data whether in databases, theoretical, or literature sources.
In addition, a project on the GitHub platform - https://github.com/Ariel-data -has been created to foster collaboration between the communities. As an open access tool, GitHub provides huge advantages of forming direct dialogues and become a go-to place for both data users and data providers, even for those who are currently not directly involved in the Ariel consortium or in the field of exoplanetary science in general.
References
[1] G. Tinetti et al., ESA Definition Study Report},(2020) - https://sci.esa.int/documents/34022/36216/Ariel_Definition_Study_Report_2020.pdf
[2] K.L. Chubb, S. Robert, C. Sousa-Silva, S.N. Yurchenko, et al., RAS Techniques and Instruments, submitted (2024) - arXiv:2404.02188.
How to cite: Robert, S., Chubb, K., Sousa-Silva, C., Yurchenko, S., and Tinetti, G.: Data availability and requirements relevant for the Ariel space mission, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1132, https://doi.org/10.5194/epsc2024-1132, 2024.
Convective mantle flow in terrestrial planets is governed by a temperature- and pressure-
dependent rheology. This results in a stagnant-lid regime observed on most terrestrial planets.
Plastic deformation can lead to breaking of the strong upper lithosphere, which resembles plate
tectonics on Earth. With Venus being the most Earth-like planet we can closely study, identifying
the factors that led to the apparent absence of plate tectonics on Venus is vital in understanding
the evolution of rocky exoplanets in general.
In order to determine the likelihood of plate tectonics, we investigate the influence of internal and
external planetary factors, mainly surface temperature and yield stress. We employ a viscoplastic
rheology in a 2D-spherical annulus geometry. The models are evaluated by computing common
diagnostic values used to recognize plate-like surface deformation. The goal of this study is to
identify key planetary factors for the occurrence or absence of plate tectonics.
How to cite: Henke-Seemann, O. and Noack, L.: The influence of external factors on surface regimes of terrestrial planets, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1017, https://doi.org/10.5194/epsc2024-1017, 2024.
How to cite: Thamm, A., Balduin, A., Carone, L., and Noack, L.: Compositional variations within the TRAPPIST-1 planets, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1154, https://doi.org/10.5194/epsc2024-1154, 2024.
M dwarfs are the most common stars in our solar neighborhood. Due to the improvements in radial velocity and transit techniques, we know that rocky planets, in particular close-in super-Earths, in compact configurations are the most common ones around M dwarfs. On the other hand, thanks to the high angular resolution of ALMA we know that most disks around very low mass stars are rather compact and small, which favors the idea of an efficient radial drift that could enhance planet formation in the terrestrial zone. Motivated by these results, we have investigated rocky planet formation around M dwarfs driven by pebble accretion through N-body simulations. We assumed that planet formation took place in compact dust disks caused by efficient dust radial drift. In the simulations we incorporated planet-disk interactions and tidal and relativistic corrections that include the evolution of the luminosity, radius and rotational period of the star. For our standard model we used different gas-disk viscosities and initial embryo distributions. For different stellar masses we also studied planet formation by planetesimal accretion. Our main result is that the sample of simulated planets that grow by pebble accretion in a gas-disk with low viscosity can reproduce the low-mass exoplanet population around M dwarfs in terms of multiplicity, masses and semi-major axis. Furthermore, we found that a gas disk with high viscosity can not reproduce the observed planet masses. Also, we show that planetesimal accretion favors the formation of water worlds and small planets that so far have not been detected. This work points towards a new approach for the disk conditions needed to study rocky planet formation around M dwarfs.
How to cite: Sanchez, M., van der Marel, N., Lambrechts, M., Mulders, G., and Guerra-Alvarado, O.: Super-Earth formation in compact disks around M dwarfs, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1060, https://doi.org/10.5194/epsc2024-1060, 2024.
The newly selected Venus missions EnVISION and VERITAS (Venus Emissivity, Radio Science, InSAR, Topography, and Spectroscopy) offer new opportunities for studying Venus but will also contribute to furthering our knowledge of Venus as an exoplanet. Hot rocky planets are favored targets due to generally more frequent transits than cooler Earth-like objects. In this work we simulate Venus as an exoplanet varying stellar, orbital, planetary and atmospheric parameters and study the effect upon atmospheric composition, climate and spectral detectability.
How to cite: Grenfell, J. L., Helbert, J., Arnold, G., Herbst, K., Sinnhuber, M., and Rauer, H.: Venus as an Exoplanet: Effect of varying stellar, orbital, planetary andatmospheric properties upon composition, habitability and detectability, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-954, https://doi.org/10.5194/epsc2024-954, 2024.
How to cite: Noack, L., Lichtenberg, T., Alei, E., Angerhausen, D., and Quanz, S. and the LIFE team: Characterization of Exoplanets with LIFE (Large Interferometer For Exoplanets), Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-711, https://doi.org/10.5194/epsc2024-711, 2024.
In our search for life in the Universe, there may be planetary bodies that are more conducive to life than Earth. Even Earth's habitability has varied enormously throughout the eons. We call worlds that are more habitable than Earth today ‘superhabitable’. In the pursuit of superhabitable worlds, K dwarf stars emerge as promising candidates due to their stable luminosity evolution, offering prolonged stability within the habitable zone conducive to life's emergence and sustainability (Arney 2019; Heller and Armstrong 2014; Schulze-Makuch, Heller, and Guinan 2020). A planet with up to 2 times Earth’s mass and around 25% larger than Earth orbiting such a K dwarf star could qualify as superhabitable. Such dimensions would result in surface pressures of roughly 1.2 bar, exceeding Earth's current pressure by 20%. This configuration would offer expanded living space and enable the retention of a denser atmosphere, providing the necessary mass and energy to support a more extensive biosphere. Moreover, the denser atmosphere would enhance detectability through remote observations. A superhabitable planet would also likely exhibit a slightly warmer climate than present-day Earth, with temperatures elevated by approximately 5 degrees Celsius. This modest increase aligns with historical trends, as biodiversity flourished during warmer epochs, with tropical zones hosting the majority of Earth's current biodiversity (Vilović, Schulze-Makuch, and Heller 2023). In terms of atmospheric compositions, such planets would exhibit heightened oxygen concentrations which contribute to expanded metabolic networks and support larger body sizes among organisms.
In our most recent study, we tested the effects of simulated K-dwarf radiation on the phototrophic organisms garden cress and cyanobacteria using an LED stellar simulator. We found that both organisms are capable of growing under this modified radiation environment, with cyanobacteria exhibiting significantly better responses to K dwarf compared to solar radiation (Vilović et al. 2024). Expanding upon these laboratory results, we now turn to theoretical models to assess the detectability of superhabitability with the James Webb Space Telescope (JWST). We combine the results of the 1D coupled climate-photochemistry model Atmos for modeling superhabitable atmospheres (Kopparapu et al. 2013) as well as the POSEIDON forward modeling code to calculate synthetic planetary spectra (MacDonald and Madhusudhan 2017; MacDonald 2023), with the PandExo tool for simulating observations of transiting exoplanets with the JWST (Batalha et al. 2017). Preliminary results indicate that superhabitable conditions positively impact the observability of key spectral features, including the oxygen features at 0.69, 0.77 and 1.24 micrometers, as well as the carbon dioxide feature at 4.3 micrometers and the ozone feature at 9.6 micrometers. Furthermore, these spectral features may require fewer transits for detection with the JWST compared to a modern Earth counterpart. This underscores the importance of prioritizing exoplanets orbiting K dwarf stars within the center of their habitable zones in our search for life outside of the Solar System using state of the art instrumentation.
References
Arney, Giada N. 2019. “The K Dwarf Advantage for Biosignatures on Directly Imaged Exoplanets.” The Astrophysical Journal Letters 873 (1): L7.
Batalha, Natasha E., Avi Mandell, Klaus Pontoppidan, Kevin B. Stevenson, Nikole K. Lewis, Jason Kalirai, Thomas Greene, Loïc Albert, Louise D. Nielsen, and Nick Earl. 2017. “PandExo: A Community Tool for Transiting Exoplanet Science with JWST & HST.” arXiv [astro-ph.IM]. arXiv. http://arxiv.org/abs/1702.01820.
Heller, René, and John Armstrong. 2014. “Superhabitable Worlds.” Astrobiology. https://doi.org/10.1089/ast.2013.1088.
Kopparapu, Ravi Kumar, Ramses Ramirez, James F. Kasting, Vincent Eymet, Tyler D. Robinson, Suvrath Mahadevan, Ryan C. Terrien, Shawn Domagal-Goldman, Victoria Meadows, and Rohit Deshpande. 2013. “Habitable Zones around Main-Sequence Stars: New Estimates.” The Astrophysical Journal 765 (2): 131.
MacDonald, Ryan J. 2023. “POSEIDON: A Multidimensional Atmospheric Retrieval Code for Exoplanet Spectra.” Journal of Open Source Software 8 (81): 4873.
MacDonald, Ryan J., and Nikku Madhusudhan. 2017. “HD 209458b in New Light: Evidence of Nitrogen Chemistry, Patchy Clouds and Sub-Solar Water.” Monthly Notices of the Royal Astronomical Society 469 (August): 1979–96.
Schulze-Makuch, Dirk, René Heller, and Edward Guinan. 2020. “In Search for a Planet Better than Earth: Top Contenders for a Superhabitable World.” Astrobiology 20 (12): 1394–1404.
Vilović, Iva, Dirk Schulze-Makuch, and René Heller. 2023. “Variations in Climate Habitability Parameters and Their Effect on Earth’s Biosphere during the Phanerozoic Eon.” Scientific Reports 13 (1): 12663.
Vilović, I., Schulze-Makuch, D. & Heller, R. (2024). Observation of Significant Photosynthesis in Garden Cress and Cyanobacteria under Simulated Illumination from a K Dwarf Star. International Journal of Astrobiology. (In Review)
How to cite: Vilovic, I., Goyal, J., and Heller, R.: Probing Superhabitable Worlds: Modeling Exoplanetary Atmospheres for simulated JWST Observations, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-106, https://doi.org/10.5194/epsc2024-106, 2024.
