Welcome to MTE’s documentation!

MTE is a Python library crafted to compute the magnetic field above (\(> 0.1\) m) various topographies. Topographies can be simulated using either an analytical equation or a Digital Elevation Model (DEM). The code is available for download GitHub. The primary purpose is to compute magnetic anomalies in the ambient magnetic field above topographies for investigating their effect on the paleomagnetic records.

This documentation is designed to serve as a comprehensive guide to both theoretical and practical applications of the MTE library.

Contents Usage Installation General outline (hierarchy) of code Reproducing results Governing equations Computational approach Benchmarks Benchmark 1: a single dipole Benchmark 2: internal cancellation Benchmark 3: a magnetized sphere Benchmark 4: a prismatic body Parameters Resolution Size Bottom boundary Conclusions Synthetic topopography: flank simulations Model setup Reproduce Global flank simulations Reproduce Artificial DEM Computational approach Model setup Results Reproduce Adding noise to DEM Adding another DEM Case study: Mount Etna Functions Support Visualization Magnetostatics Set measurement parameters Artificial DEM References Complete derivation of the equations Uniformly magnetized sphere

For a thorough understanding of the MTE library, begin with the Usage section which provides essential details on installation. Dive into the Governing equations to grasp the theoretical underpinnings of the code. Proceed to the Computational approach for insight into the numerical framework that drives our simulations. Discover the validation process through four comprehensive Benchmarks, where the methodology for accurate reproduction of computed values is also outlined. Insights into optimizing model Parameters such as mesh resolution and domain extent are shared, showing the process of refinement for enhanced simulation accuracy. The flank simulations section presents a case study on applying synthetic topography, again offering a walkthrough of the setup process. Next, uncover the process of integrating a DEM into the model, from generating an artificial DEM using pseudo-fractals to incorporating real-world terrain and field paths. Finally, the Etna section illustrates the replication of field values from the study of [Meyer and de Groot, 2024].

Reproduction

For most sections, a stepwise method to reproduce the presented results is given. These are located in collapsible sections at the end of each subsection. Please make sure to read the Usage section beforehand.

Contact

For any bugs or questions, please contact: a.e.hendrickx@uu.nl