12 citations · 18 across the 7 of their papers we have counts for
9 papers
Probing Exoplanetary Chemistry with Ariel: Scientific Priorities and Observational Strategies
Olivia Venot, Yamila Miguel, Robin Baeyens +30
Over the past two decades, increasingly precise observations have revealed that exoplanet atmospheres are chemically diverse and often far from equilibrium, with processes such as…
Faithful Neural Embeddings for 3D Exoplanet Climate Modeling
Amit Reza, Ludmila Carone, Christiane Helling
With the rapid advancement of telescopes like JWST and Ariel, there is an urgent need for efficient 3D climate models to interpret observations of exoplanet atmospheres. Traditiona…
Chemical Tracers for 3D Atmospheric Asymmetries on WASP-69 b
Nidhi Bangera, Ludmila Carone, Vikas Soni +6
Warm giant exoplanets exhibit strong three-dimensional temperature contrasts that can significantly alter atmospheric chemistry through quenching and photochemistry, yet transmissi…
The Tartu Observatory Fiber-fed Echelle Spectrograph (TOFES) Data Reduction Pipeline
Sandipan P. D. Borthakur, Tõnis Eenmäe, Nikolai Piskunov +9
We introduce the data reduction pipeline for the Tartu Observatory Fiber-fed Echelle Spectrograph (TOFES). TOFES is installed in the Coudé room and will be connected to the 1.5 m T…
Metal Oxide Clusters in Gas Giant Exoplanet Atmospheres
Deepak Bisht, Christiane Helling, David Gobrecht +6
This study investigates the thermal stability and absorption of metal oxide clusters in exoplanetary atmospheres. Utilizing our thermochemical data, we analyze eight distinct clust…
Accelerating exoplanet climate modelling: A machine learning approach to complement 3D GCM grid simulations
Alexander Plaschzug, Amit Reza, Ludmila Carone +2
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…
Grid-based exoplanet atmospheric mass loss predictions through neural network
Amit Reza, Daria Kubyshkina, Luca Fossati +1
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…
Kinetic and photochemical disequilibrium in the potentially carbon-rich atmosphere of the warm-Jupiter WASP-69b
Nidhi Bangera, Christiane Helling, Gloria Guilluy +5
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 imp…
Machine learning-based classification for Single Photon Space Debris Light Curves
Nadine M. Trummer, Amit Reza, Michael A. Steindorfer +1
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 hig…