Linking planet formation and the composition of the host star
All planets are intimately related to their host star. Within this PhD project, you will research new aspects of the connection between planetary systems and the chemical composition of their central star. What might these connections be? The best-known is the correlation of stellar metallicity with the occurrence rate of hot Jupiter exoplanets, which has been known since the mid-2000s and is hypothesised to arise from the increased dust content in higher-metallicity protoplanetary disks. In the 2010s, the potential to use the planetary carbon-to-oxygen (C/O) ratio as a tracer of a planet's formation history has gained popularity, and this is intimately tied to the bulk content of C and O in a given system, which can be measured in the star itself. Recent studies have also proposed other elemental ratios, such as N/O, as potential planetary formation history tracers. Furthermore, in 2015 we provided evidence for planet-induced dust traps in protoplanetary disks causing a strong underabundance of dust-forming elements in the surface of the central star. We have since used "accretion contamination" on the central star to study the behaviour of elements in protoplanetary material. The web of connections described above is ripe for further exploration. You would have the opportunity to work on models of planet-forming environments underlying these star-and-planet links, to yield new insights into the meaning and origins of planetary and stellar composition.
Contact: Dr. Mihkel Kama (m.kama AT ucl.ac.uk)
Probing the origins of planets with the James Webb Space Telescope
In the 2020s, exoplanet studies will move increasingly towards their chemical composition and its origins in protoplanetary disks. Some of the key goals are to link planetary elemental abundances to their formation location and migration history in a disk, and to establish the origins of habitable chemical compositions. The James Webb Space Telescope, due to launch within 1-2 years, is poised to provide a wealth of new spatially and spectrally resolved data on the composition of planet-forming material around young stars on Solar System spatial scales. This has the potential to revolutionise our understanding of planetary origins. Some of the most pressing problems involve the delivery of water to terrestrial planets and the early budget of volatile vs refractory carbon. More generally, questions abound on the detailed budget of volatile and semi-volatile elements, including the bio-essential ones, at the time of incorporation into planets. JWST will help to address these issues by revealing the presence, abundance, and spatial distribution of important gas-phase molecules, ices, and minerals. PhD projects are available to analyse and model the extraordinary upcoming JWST and other telescope data on protoplanetary environments, and to draw links with the properties of mature planetary systems.
Contact: Dr. Mihkel Kama (m.kama AT ucl.ac.uk)
Spectroscopy of hot rocky Super-Earths
Thousands of exoplanets have been discovered in the recent years, most of them are gas giants and hundreds appear to be rocky (silicate-rich). Many of these exoplanets have very short orbital period, hence hot atmospheres. Some of the rocky super-Earths are evaporating with complex atmospheric compositions. These planets have a lot in common with the young Earth; the massive amounts of water in their atmospheres can melt rocks and put their constituents into the atmosphere. Similar processes are expected in the atmospheres of the post-impact planets.
The atmospheres of hot rocky super-Earths have very different spectroscopic signatures than gas giants or cooler objects, which will influence interpretation of the atmospheric observations. Examples of the recent atmospheric retrievals (e.g. of HD 209458b, GJ 1214b, 55 Cancri e and HD 189733b) show that transit observations can help to establish the bulk composition of a planet. However, it is only with good predictions of likely atmospheric composition allied to a comprehensive database of spectral signatures that the observed spectra can be deciphered. This PhD project will aim to produce a comprehensive library of molecular opacities specific to lava-planets. The results will be incorporated into exoplanet models developed at UCL and made available to the scientific community. These models will enable the interpretation of present and future spectroscopic studies of rocky super-Earths. Exactly these types of hot solid planets will be the likely targets of NASA's JWST or ESA's ARIEL.
Contact: Prof. Sergey Yurchenko (s.yurchenko AT ucl.ac.uk)
Pandemonium in the planetary graveyard
Defying the notion of the silent graveyard, planetary systems refuse to go quietly into the long night. Instead, a significant fraction show one or more signs of dynamical reanimation, with strong indications of general mayhem during the final stages of stellar evolution. These rejuvenated planetary systems manifest as irregular and complex transit events, transient optical emission features, and variable infrared fluxes from dust production and destruction. Ultimately, all leave their detailed chemical signatures on the surface of the white dwarf stars they orbit, and provide powerful insight into the masses and geochemical structures of the planetary bodies. At UCL, we are leading the study of these evolved planetary systems in the infrared via their dusty debris disks, in the optical via transiting events, and in the ultraviolet where elemental abundances can be measured from the polluted stellar surfaces. The project will involve at least two observational approaches, including but not limited to: studies of available transit data, infrared data that track debris disk variability, and importantly bulk compositions for minor and major planetary bodies.
Contact: Prof Jay Farihi (j.farihi AT ucl.ac.uk)
Unveiling the nature of super-Earths with current and future observatories
Super-Earths, i.e. planets lighter than ten Earth masses, appear to be the most common planets in our galaxy. Being absent in our Solar Systems, their nature is rather mysterious: from their densities we gather there is a large variety of cases, ranging from big rocky planets to small Neptunes or more exotic types. The chemical composition and state of their atmospheres, can be used as a powerful diagnostic of the history, formation mechanisms and evolution of these planets. In the past fifteen years, the UCL exoplanet team led by Prof. Tinetti has worked at the forefront of the spectral/photometric measurements of exoplanet atmospheres and their interpretation, with molecular species being detected in the atmospheres of giant planets and super-Earths (e.g. extremely hot 55 Cnc-e and habitable-zone K2-18b). As part of the PhD, the student will have the opportunity to work in collaboration with Prof. Giovanna Tinetti, Dr. Angelos Tsiaras and Dr. Yuichi Ito on a number of aspects connected with the observations and modelling of super-Earths’ atmospheres with current and future observatories (HST, JWST) and dedicated space missions (ARIEL).
Using deep learning to model complex chemistries of exoplanet atmospheres
To determine the make-up of an exoplanet atmosphere, we solve the Bayesian inverse problem by iteratively fitting atmospheric models to the data to determine the statistically most likely distribution of atmospheric model parameters, such as water abundance (e.g. Al-Rafaie et al. 2021). Current atmospheric retrieval frameworks approximate the complex 3D nature of planetary atmospheres through 1D radiative transfer models coupled with heuristic or equilibrium chemical schemes. These approximations are sufficient in effectively describing Hubble data but break down profoundly when applied to the more complex JWST and Ariel data. For chemistry, the fundamental reactions, mixing through the atmosphere and its evolution over thousands of years, must be accounted for to solve the next-generation inverse problem. Current modelling of these disequilibrium schemes (e.g. Venot et al. 2012) are too slow or make approximations that oversimplify. Given that the Ariel mission will increase the number of spectroscopically characterised planets from 50 currently to 1000, the need for faster modelling techniques that maintain accuracy is apparent. This PhD project will focus on the fundamental issues of improving sampling speeds by approximating complex chemical models using neural networks (NNs) and improving the NNs' explainability. Simply put, we want to design a neural network that can both rapidly simulate non-linear chemical networks and explain why it chose that particular solution. The PhD candidate will build on initial work by the UCL Exoplanet group (e.g. Yip et al. 2021) to extend the atmospheric modelling framework to modelling complex disequilibrium/photochemical atmospheric chemistry pathways.
Contact: Dr Ingo Waldmann (ingo.waldmann AT ucl.ac.uk)
The orbits of charged particles in planetary magnetospheres, and the dynamics of the orbits of stars in galaxies, are the result of how the ‘test particles’ within each system - individual ions / electrons or individual stars - respond to either gravitational or electromagnetic fields. This project is principally a project in planetary plasma physics, but has an 'interdisciplinary element' based on exploring analysis techniques used in other areas of astrophysics, and seeing how they can be applied to model spacecraft magnetic field data which probe the plasma sheet regions of the planets Saturn and Jupiter. The main 'strands' of the project would be: (i) To develop a general magnetic field model for a planetary magnetospheric plasma sheet, by testing a variety of different multi-parameter fitting techniques; (ii) A minor work component related to the less 'fully formed' idea of exploring the role of action integrals (a central concept in dynamical systems) in modelling the trajectories of charged particles in magnetic fields - and whether this could lead to alternative, useful ways to represent such trajectories in a global magnetosphere.
Contact: Prof Nick Achilleos (nicholas.achilleos AT ucl.ac.uk)
Modelling satellite drag in the thermosphere by modifying a solar radiation model
The number of artificial objects in orbit is growing at an unprecedented rate. The situation is particularly drastic in the Low-Earth Orbit (LEO) region as a number of organisations, including Space-X and Amazon, race to deploy LEO satellite mega-constellations to provide next-generation internet services. The population of operational objects in orbit is predicted to increase from ~ 3,000 today to ~ 30,000 by 2030. This dramatic increase in population density also increases the chance of on-orbit collisions. This risk must be properly managed to avoid a runaway situation, known as the Kessler syndrome, where on-orbit collisions create space debris, and thus increasing the risk of further collisions, until eventually, it becomes too dangerous to launch future space missions. To effectively manage the future space population, among other things, we must advance our ability to know where things are in the space (orbit determination) and where they are going (orbit prediction). This project will contribute to the latter. For accurate orbit prediction, we require accurate force models. At lower altitudes in the LEO region, the influence of atmospheric drag force is second only to gravity. Current operational atmosphere models have fairly simple assumptions. However, solar heating and geomagnetic storms stir up the upper atmosphere, changing the chemistry, and consequently the drag effects. The aim of the project is to modify a state-of-the art solar photon radiation model to model the drag caused by the atoms and molecules of the upper atmosphere.
Contact: Dr Anasuya Aruliah (anasuya AT star.ucl.ac.uk)