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Exoplanets

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People & Projects

The Exoplanet research group at UCL is highly cross disciplinary, with several members working in both exoplanets and other fields. Below you can find a list of the group members and the main Exoplanets projects and grants.

Key Contacts:

Role:Name:Contact:
Planetary Science MSc Programme Lead & Admissions TutorDr Ingo Waldmanningo.waldman@ucl.ac.uk
ARIEL Mission LeadProf Giovanna Tinettig.tinetti@ucl.ac.uk
Twinkle Mission Project Manager and CEO Blue Skies LtdDr Marcell Tessenyim.tessenyi@ucl.ac.uk
Centre for Space Exochemistry Data (CSED) Operations AdministratorEmma Dunforde.dunford@ucl.ac.uk

 

Research Staff
Name, position:Contact:
Dr Jo Barstow (Eberhardt), RAS Fellowj.eberhardt@ucl.ac.uk
Dr Jay Farihi, Associate Professorj.farihi@ucl.ac.uk
Dr Steve Fossey, Teaching Fellows.fossey@ucl.ac.uk
Dr Jincheng Guo, Research Associatejincheng.guo@ucl.ac.uk
Dr Nikos Nikolaou, Research Associaten.nikolaou@ucl.ac.uk
Dr Marco Rocchetto, Honorary Research Associatem.rocchetto@ucl.ac.uk
Prof Jonathan Tennyson, Professor of Physicsj.tennyson@ucl.ac.uk
Dr Marcell Tessenyi, Senior Research Associatem.tessenyi@ucl.ac.uk
Prof Giovanna Tinetti, Professor of Astrophysicsg.tinetti@ucl.ac.uk
Dr Angelos Tsiaras, Research Associateangelos.tsiaras.14@ucl.ac.uk
Dr Ingo Waldmann, Lectureringo.waldman@ucl.ac.uk
Dr Sergey Yurchenko, Associate Professors.yurchenko@ucl.ac.uk
Students
Name:Contact:
George Canngeorge.cann.15@ucl.ac.uk
Quentin Changeatquentin.changeat.18@ucl.ac.uk
Billy Edwardsbilly.edwards.16@ucl.ac.uk
Mario Morvanmario.morvan.18@ucl.ac.uk
Andrew Swanna.swann.17@ucl.ac.uk
Kai (Gordon) Yipkai.yip.13@ucl.ac.uk

Projects

The main projects and grants of the UCL Astrophysics Exoplanets Group.

ExoLights: Decoding Lights from Exotic Worlds, ERC Consolidator Grant 617119 (PI: Tinetti)

It is now accepted that exoplanets are ubiquitous. However little is known about those planets we have detected beyond the fact they exist and their location. For a minority, we know their weight, size and orbital parameters. For less than twenty, we have some clues about their atmospheric temperature and composition. How do we progress from here?

We are still far from a hypothetical Hertzsprung–Russell diagram for planets and we do not even know whether there ever will be such classification for planets. The planetary parameters mass, radius and temperature alone do not explain the diversity revealed by current observations. The chemical composition of these planets is needed to trace back their formation history and evolution, as was the case for the Solar System.

Pioneering results were obtained through transit spectroscopy with Hubble, Spitzer and ground-based facilities, enabling the detection of ionic, atomic and molecular species and of the planet’s thermal structure. With the arrival of improved or dedicated instruments in the coming decade, planetary science will expand beyond the narrow boundaries of our Solar System to encompass our whole Galaxy.

ExoLights will address the following fundamental questions:
– Why are exoplanets as they are?
– What are the causes for the observed diversity?
– Can their formation history be traced back from their current composition and evolution?

Spectroscopic observations of a select sample of exoplanets’ atmospheres will be analysed with state-of-the art statistical techniques and interpreted through a comprehensive set of spectral retrieval models, developed by the PI and her team. This programme, together with the homogeneous re-analysis of archive observations of a larger sample of exoplanets, will allow us to use the chemical composition as a powerful diagnostic of the history, formation mechanisms and evolution of gaseous and rocky exoplanets.

ExoAI: Deciphering super-Earths using Artificial Intelligence, ERC Starting Grant 173948 (PI: Waldmann)

The fields of deep learning and machine learning have recently revolutionised many fields of science and industry. The ExoAI project is trying to do the same for extrasolar planets by making current algorithms more precise and more generally applicable using machine learning techniques. By adopting a holistic approach and look at, say, all data ever taken by an instrument, it becomes possible to gain a new and improved understanding of how to calibrate an instrument. Machine learning, and in particular deep learning – i.e. the use of neural networks - is ideally suited for this task.

The ExoAI projects aims to solve long standing data analysis problems in the fields of planet detection, observations of exoplanet atmospheres using space and ground-based instruments, as well as modelling of exoplanet atmospheres. For an up-to-date blog on current ExoAI projects, please follow the ExoAI webpage.

ExoMol database: Molecular linelists for exoplanets and other hot atmospheres 

The ExoMol project, originally funded by ERC Advanced Investigator Project 267219 (PI: Tennyson), aims to produce high temperature line lists of spectroscopic transitions for key molecular species likely to be significant in the analysis of the atmospheres of extrasolar planets and cool stars. This molecular data is crucial for accurate astrophysical models of the opacity and spectroscopy of these atmospheres.

RAS Research Fellowship: Dr Joanna Barstow

The discovery of planetary systems around other stars has transformed planetary science over the last 25 years, and challenged our understanding of how planets work. From hot, Jupiter-sized bodies that orbit their stars in a little over a day to cloudy worlds resembling miniature Neptunes, these exoplanets and their atmospheres demonstrate astounding variety. The key question for the next decade is which factors are responsible for driving these differences, and in particular what is the role of irradiation from the parent star? A comparative study of known planets, including those in the solar system, can provide answers.