Full Vector Inversion of Magnetic Microscopy Images Using Euler Deconvolution as Prior Information - Souza‐Junior, Gelson F.; Uieda, Leonardo; Trindade, Ricardo I. F.; Carmo, Janine; Fu, Roger (Geochemistry, geophysics, geosystems : G3, 2024)
Paleomagnetic data is collected from bulk samples, containing a mixture of stable and unstable magnetic particles. Recently, magnetic microscopy techniques have allowed the examination of individual magnetic grains. However, accurately determining the magnetic moments of these grains is difficult and time‐consuming due to the inherent ambiguity of the data and the large number of grains in each image. Here we introduce a fast and semi‐automated algorithm that estimates the position and magnetization of dipolar sources solely based on the magnetic microscopy data. The algorithm follows a three‐step process: (a) employ image processing techniques to identify and isolate data windows for each magnetic source; (b) use Euler Deconvolution to estimate the position of each source; (c) solve a linear inverse problem to estimate the dipole moment of each source. To validate the algorithm, we conducted synthetic data tests, including varying particle concentrations and non‐dipolarity. The tests show that our method is able to accurately recover the position and dipole moment of particles that are at least 15 μm apart for a source‐sensor separation of 5 μm. For grain concentrations of 6,250 grains/mm3, our method is able to detect over 60% of the particles present in the data. We applied the method to real data of a speleothem sample, where it accurately retrieved the expected directions induced in the sample. The semi‐automated nature of our algorithm, combined with its low processing cost and ability to determine the magnetic moments of numerous particles, represents a significant advancement in facilitating paleomagnetic applications of magnetic microscopy. Plain Language Summary 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. Key Points We present a fast algorithm to estimate the position and magnetization of individual sources using only magnetic microscopy data The algorithm was validated using synthetic samples that included both dipolar and non‐dipolar sources with varying depths and intensities The successful application of the algorithm on a speleothem sample represents an advancement of this methodology for paleomagnetic studies