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Brownian models for geomagnetic reversals

The study of the Earth's magnetic field can be approached from the study of data obtained through direct measurements (ground-based observatories, satellites, etc.) and indirect measurements (paleomagnetic and archaeomagnetic studies) or through the analysis of models.
On the one hand, there are experimental models, consisting of complex equipment in which the behaviour of the outer core is simulated by means of metallic fluids at high temperatures inside a rotating spherical receptacle. On the other hand, magnetohydrodynamic models are also available, which numerically simulate the evolution of the core based on the equations of thermodynamics, fluid dynamics and electromagnetism using powerful computers. The latter allow a detailed analysis of the dynamics of the system. However, the computational power required makes it necessary to use, for some physical characteristics, values that are very different from the real ones.
An alternative to magnetohydrodynamic models is to use simplified or conceptual models, in which, instead of simulating the fluid dynamics in detail, general features of the system are described using simpler mathematical expressions. An example of such an approach is stochastic or 'Brownian' models, in which the evolution of the magnetic field is simulated by random fluctuations subject to certain constraints. The results of these models are statistically comparable with observations and allow the mechanisms responsible for this behaviour to be investigated.
Researchers in the group have developed a simple model capable of reproducing the temporal asymmetry in the behaviour of the dipole moment of the Earth's magnetic field in the inversion environment (Molina-Cardín et al., 2021).

A. Molina-Cardín, L. Dinis, M.L. Osete. Simple stochastic model for geomagnetic excursions and reversals reproduces the temporal asymmetry of the axial dipole moment. Proceedings of the National Academy of Sciences of the United States of America. https://doi.org/10.1073/pnas.2017696118




























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