Reconstruction of the dayside magnetopause using machine learning methods


   Department of Space & Climate Physics

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  Dr Colin Forsyth, Dr Andrei Samsonov  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

The Earth’s magnetopause is the boundary between the solar wind and the magnetosphere. During coronal mass ejections, the solar wind dynamic pressure often increases and the magnetopause comes closer to the Earth. This may damage spacecraft travelling around the Earth on geosynchronous orbits. Besides, strong magnetospheric compression may influence the particles in the ring current.

During the last 50 years, space physicists have developed a number of empirical models to predict the magnetopause position using the database of in-situ spacecraft magnetopause crossings. However, empirical models usually assume a predefined analytical shape of the magnetopause and this may result in poor accuracy in some areas, particularly under extremes of solar wind driving. Numerical magnetohydrodynamic models (see Figure 1) also predict the magnetopause position, but they may not fully include all magnetospheric currents and physical processes, and therefore provide imprecise predictions as well.

We have now a very large database of magnetopause crossings in different regions and for different solar wind conditions. This growing number of space observations and outstanding advances in machine learning and artificial intelligence provide an opportunity for a breakthrough in our understanding of the magnetopause and modelling its global state.

This project will be directly related to the forthcoming Solar wind Magnetosphere Ionosphere Link Explorer (SMILE – https://mssl.ucl.ac.uk/SMILE/) mission. SMILE is a joint mission of the Chinese Academy of Sciences and the European Space Agency that will study the interaction of the solar wind with the Earth’s magnetosphere. One of the main instruments on board SMILE will be the Soft X-ray Imager (SXI) that will measure soft X-rays emitted in the magnetosheath and cusps. The SMILE team has been developing special numerical methods to find three-dimensional magnetopause shapes and positions from two-dimensional SXI images. SMILE is due for launch in 2025. A new state-of-the-art magnetopause model being available during the mission live time will provide predictions of magnetopause position near the subsolar point based on the solar wind observations, and, therefore, will facilitate the proper interpretation of SXI observations.

The electric current density distribution obtained by an MHD model indicates the magnetopause and bow shock positions. Adapted from Samsonov et al. (2016).

Desired Knowledge and Skills

  • Undergraduate in physics, Earth sciences or astrophysics
  • Strong computational skills (students will be encouraged to develop their own code as appropriate to deliver parts of the project)

Entry requirements

An upper second-class Bachelor’s degree, or a second-class Bachelor’s degree together with a Master's degree from a UK university in a relevant subject, or an equivalent overseas qualification.

Additional eligibility requirements

The STFC studentship will pay your full tuition fees and a maintenance allowance for 3.5 years (subject to the PhD upgrade review).

Additional information

This project is based in the Department of Space & Climate Physics, located at the Mullard Space Science Laboratory (MSSL) in Holmbury, Surrey. MSSL is located in remote countryside in Surrey. There is limited public transport to reach the site. Before you apply to study for a PhD in our department, please check our location carefully and consider how you will regularly commute to MSSL.

How to apply

Our STFC studentships starting in September 2024 are open for applications until 26th January 2024.  

For details of how to apply please refer to our website: PhD Opportunities | UCL Department of Space and Climate Physics - UCL – University College London


Computer Science (8) Physics (29)

 About the Project