Context
- 2022 Master 1 internship
- 2023-2026 PhD Thesis
Our work
Modeling the Earth Bow Shock
During her internship, Ambre worked with me and Bayane Michotte de Welle on modeling the location and shape of the Earth’s bow shock with machine learning regression models. Ambre built on the work of Gautier Nguyen and Bayane Michotte de Welle to automatically detect bow shock crossings as transitions between the solar wind and the magnetosheath and used various machine learning algorithms to model the shape of the bow shock. This work has been presented at EGU 2022.
Citation
Ghisalberti, A., Aunai, N., and Michotte de Welle, B.: Magnetopause and bow shock models with machine learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5721, https://doi.org/10.5194/egusphere-egu22-5721, 2022
Analyzing the structure of the Magnetopause Boundary Layer
Ambre Ghisaleberti has started her PhD with Benoit Lavraud and me on the analysis of the structure of the Earth magnetopause boundary layer. The boundary layer is known from detailed crossings which are mostly investigated in case studies. In Ambre’s thesis we follow the legacy of Gautier Nguyen and Bayane Michotte de Welle and use machine learning to extract all data measured in the dayside boundary layer by several missions (MMS, THEMIS and Cluster). The structure of the boundary layer is then studied as a function of the solar wind, IMF and magnetosphere boundary conditions.
Funding
- CNES PhD half scholarship
- DIM-Origines half scholarship
After
TBD