Using neural networks and clustering algorithms to understand the mass flows and energy cycles at the heart of our Galaxy

Supervisors: Steve Longmore (ARI, LJMU), Qizhou Zhang (CfA, Harvard University)

The inner few thousand light years of the Milky Way – the Central Molecular Zone (CMZ) – hosts the nearest supermassive black hole, largest reservoir of dense gas, most massive/dense stellar clusters, and highest volume density of supernovae in the Galaxy. As the nearest environment for which it is possible to simultaneously observe many of the extreme physical processes shaping the Universe, it is one of the most well-studied regions in astrophysics.

However, the potential of the CMZ as a laboratory of extreme physics is fundamentally limited by the lack of a unified framework to understand how global processes determine the location, intensity and timescales for star formation and feedback.

This joint PhD project with Harvard will be based on analysis of large datasets that we’ve been awarded on the world’s foremost mm-wave telescope, ALMA, intended to overcome this limitation. This project will produce the largest (250Tb), highest velocity resolution map of the most physically, chemically and kinematically complex region in the sky. The enormity and complexity of these data make the analysis particularly challenging and very well suited to a data intensive PhD project.