If I had to select a single word to define the field of exoplanets, that word would be revolutionary. During the past 20 years, about 3500 planets have been found around every type of star. The current statistical estimates indicate that, on average, every star in our Galaxy hosts at least one planetary companion, i.e. our Milky Way is crowded with a thousand billion planets!

The most revolutionary aspect of this young field is the discovery that the Solar System does not appear to be the paradigm in our Galaxy, but rather one of the many possible configurations we are seeing out there.

A key observable for planets is the chemical composition and state of their atmosphere. Knowing what atmospheres are made of is essential to clarify, for instance, whether a planet was born in the orbit it is observed in or whether it has migrated a long way; it is also critical to understand the role of stellar radiation on escape processes, chemical evolution and climate. The atmospheric composition is the only indicator able to discriminate an habitable/inhabited planet from a sterile one.

Decoding Lights from Exotic Worlds

The ExoLights team at UCL (PI G. Tinetti) has been funded by the European Research Council to develop novel techniques for data analysis and interpretation of exoplanet atmospheres as well as new space mission concepts for exoplanet spectroscopy.

Key results are summarised here .

The ExoLights team delivered several breakthrough scientific discoveries and an infrastructure of open source numerical codes to observe and interpret a large population of exoplanet atmospheres.

In 2018 we published the first catalogue of 30 exoplanet atmospheres being studied at any point (Tsiaras et al., 2018). This work has shifted the entire field of exoplanet atmospheres from the investigation of individual planets to the characterisation of populations. The focus on population analysis and infrastructure to monitor and process big data has been driving the entire exoplanet characterisation field towards these goals.

We have obtained also some high-impact results. One is the first analysis of an exoplanet’s atmosphere around a super-Earth (Tsiaras et al., 2017). Another is the first water vapour detection in the atmosphere of a small planet, in its parent star’s habitable zone (Tsiaras et al., 2019).

Space missions

Information theory and machine learning

I have worked on dynamical systems and information theory during my PhD and, more recently, I have discovered that many of these techniques are also very useful in the field of exoplanets, for data analysis and interpretation. Together with my team and collaborators UCL, we have pioneered the use of machine and deep learning techniques to the analysis of exoplanet atmospheres.