Gelson F. Souza-Junior, Leonardo Uieda, Ricardo I. F. Trindade, Janine Carmo, Roger Fu
This repository contains the data and source code used to produce the results presented in:
Souza-Junior, G.F., Uieda, L., Trindade, R.I.F., Carmo, J., and Fu, R. (2023). Full vector inversion of magnetic microscopy images using Euler deconvolution as prior information. EarthArXiv. https://doi.org/10.31223/x5qd5z
| Info | |
|---|---|
| Version of record | https://doi.org/10.1029/2023GC011082 |
| Preprint on EarthArXiv | https://doi.org/10.31223/X5QD5Z |
| Archive of this repository | https://doi.org/10.6084/m9.figshare.22672978 |
| Reproducing our results | REPRODUCING.md |
This paper presents a new method to automatically identify the signal from individual magnetic particles in magnetic microscopy images and linearly invert the data in 2 steps to determine the position and dipole moment of each particle. The idea for this work came from combining the group's expertise in applied geophysics and paleomagnetism. This is the first contribution from Gelson F. Souza-Junior's PhD project.
The code that implements the method here is a proof-of-concept. A more user-friendly version will be implemented in the open-source library Magali.
Synthetic data test showing that our method is able to automatically identify and recover the dipole moments of a large number of magnetic particles.
Very small magnetic particles in rocks and other materials can store information about what the Earth’s magnetic field was like in the past. But not all particles are good recorders of this magnetic information, and some may have recorded different overlapping directions and strengths. So it is important to measure each particle separately in order to identify and separate the good recorders from the bad ones. A device called a "quantum diamond microscope" is able to measure the magnetic field near the surface of a rock sample at microscopic scale. We propose a new method for processing data from this microscope that is able to find out the individual magnetizations of large amounts of small magnetic particles automatically. We created a computer program to execute the method, which calculates the 3D position and magnetization of each particle using the simple model of a magnetic dipole. We tested the method on simulated data, using fake magnetic particles for which we know the correct magnetization and position, and real data, both of which showed good results in most cases. The method we created has the potential to enable the widespread study of the magnetism of natural materials with more detail than before.
All Python source code (including .py and .ipynb files) is made available
under the MIT license. You can freely use and modify the code, without
warranty, so long as you provide attribution to the authors. See
LICENSE-MIT.txt for the full license text.
The manuscript text (including all LaTeX files), figures, and data/models
produced as part of this research are available under the Creative Commons
Attribution 4.0 License (CC-BY). See LICENSE-CC-BY.txt for the full
license text.
This research was supported by grant 162704/2021-6 from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), grant 2021/08379-5 from the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), grant PRPI 22.1.09345.01.2 from Universidade de São Paulo, and grant IES\R3\213141 from the Royal Society. The opinions, hypotheses, and conclusions or recommendations expressed in this material are the responsibility of the authors and do not necessarily reflect the views of FAPESP.