From Individual Magnetic Carriers to Global Magnetic Models
Authors:   , Out Frenk 
Published: January 2025

The Earth’s magnetic field is dynamic, as evidenced by phenomena such as geomagnetic pole reversals and local anomalies like the South Atlantic Anomaly. To investigate the ancient (paleomagnetic) field, we primarily rely on iron-oxide minerals, such as magnetite, found in rocks. When volcanic rocks cool below the Curie temperature, these minerals lock in the Earth's magnetic field present at that time. By studying oriented rock samples in paleomagnetic laboratories and determining the age of the rock, we can reconstruct both the intensity and configuration of the magnetic field at the time these minerals formed.
However, not all iron-oxides are reliable recorders of the magnetic field. Larger minerals, typically those greater than ~1 µm, tend to distort the original magnetic signal due to their volume, rendering the recorded field inaccurate. In contrast, iron-oxides between 40 nm and 1 µm are generally better at retaining the magnetic field, though this does not imply accuracy. Natural rock samples contain a mix of both good and poor recorders, often resulting in the loss of up to 90% of data when trying to retrieve paleointensity information from bulk rock samples.
Recent advancements in Micromagnetic Tomography (MMT) allow for the measurement of the magnetic contributions from individual iron-oxide minerals within rock samples. By focusing on those particles with the most stable magnetic signals, MMT provides a more reliable means of extracting paleomagnetic data from challenging samples. This technique involves high-resolution magnetic field measurements of a rock thin section combined with NanoCT data. Through a least-squares inversion, the magnetic moments of individual iron-oxides can be calculated.
In my dissertation, I present the mathematical framework underlying this least-squares technique and develop a statistical method for interpreting the results. Since not all magnetic moments solved by MMT are stable, this framework helps identify and address such instances. I also address the gap between the magnetic carriers detectable by CT (typically particles larger than ~0.75 µm) and those small enough to meaningfully retain magnetic signals. This investigation led to the creation of an iron-oxide grain-size distribution ranging from 40 nm to 10 µm, allowing me to assess the sensitivity of both MMT and traditional bulk measurements to different iron-oxide mineral sizes. To further enhance the number of stable magnetic moments, I introduce a new scanning protocol for MMT—double-sided scanning; by scanning both sides of the thin-section, I significantly increased the number of stable magnetic moments retrieved.
Lastly, I describe a model that uses paleomagnetic data to create a global representation of the Earth’s magnetic field. This model interpolates geomagnetic data both spatially and temporally and is based on a well-established Fortran algorithm that has been in use since the 1980s. I have translated this algorithm into Python to enhance readability and accessibility, thereby enabling a broader audience to integrate paleomagnetic data from different time periods and locations around the globe. This approach will allow more users to obtain a deeper insight of their paleomagnetic data, and how these contribute to the origin and evolution of Earth’s magnetic field.