Stellar and planetary astrophysics

Exploring chemical evolution and origin of elements

Research projects in this theme also look at stellar structure, clusters and populations, galactic archaeology and formation, as well as planet formation and exoplanet detection.

Typical facilities used by our group are:

• European Southern Observatory telescopes, such as the Very Large Telescope
• space telescopes like Gaia or the James Webb Space Telescope
• bespoke surveys like Galah at the Anglo-Australian Telescope
• the Vista Survey of the Magellanic Clouds undertaken with the ESO/VISTA telescope.

Learn more about the projects we are undertaking, the researchers engaged in them, and who you can contact to get involved.

Using dying stars to reveal the origin of elemental isotopes in the universe

How the elements in the universe are synthesised is one of the defining questions of astrophysics.

Low- and intermediate-mass (LIM) stars are key contributors to the chemical enrichment of their host galaxies. However, understanding how they produce their elements remains an unsolved problem.

Using high-resolution spectra of post-AGB stars – obtained from facilities such as the 8-metre Very Large Telescopes at the European Southern Observatory, the Australian-led million-star GALactic Archaeology with HERMES (GALAH) survey, and other international surveys – this project will conduct a comprehensive and homogeneous chemical analysis, finally revealing the process of element production in LIM stars.

To get involved in this project, contact: Devika Kamath

Imaging Exoplanets with the James Webb Space Telescope

To take direct images of exoplanets means pushing instruments to their limits - even NASA's flagship observatory, the James Webb Space Telescope, demands very sophisticated data analysis to see the faint specks of planets next to bright stars. Our team have recently demonstrated a totally new approach to data analysis with one of the JWST cameras, achieving the telescope's highest resolution images by combining machine learning with physical models of the camera. If you like Python and you like imaging science, this is a PhD with considerable scope: we want to extend these ideas to all the other observing modes with JWST, and the next generation of instruments on Roman and Lazuli. We will combine physics models, neural networks, and modern Bayesian statistics to dig faint planets out of the noise and measure their properties, paving the way for the long-term search for alien life.

Supervisor: Benjamin Pope

Finding Earth's Neighbours with Extremely Precise Radial Velocities

The first exoplanets were discovered by the radial velocity method, measuring the tiny Doppler shift in their star's spectral lines as it wobbles back and forth under the planet's gravity. Today these instruments should almost be stable enough to pick up exo-Earths — but we are limited not by hardware, but by an imperfect knowledge of how stars vary. In this project we aim to machine-learn models of stellar spectra and how they can change with stellar magnetism, and use these better models to analyse the data from the world's leading exoplanet spectrographs NEID and HPF. Working with A/Prof Christian Schwab, who designed these two instruments, with A/Prof Benjamin Pope on the stats and machine learning, and other students and postdocs, you will build and apply better data analysis software to pick up the tiny signals of Earth-mass planets out of these data and find some of the first rocky worlds around neighbouring stars.

Supervisor: Benjamin Pope