Related papers: Neural Differential Equations for the Solar Dynamo
The magnetic cycle of the Sun, as manifested in the cyclic appearance of sunspots, significantly influences our space environment and space-based technologies by generating what is now termed as space weather. Long-term variation in the…
Many low-mass stars like the Sun host periodic, oscillatory magnetic fields that lead to variable levels of stellar activity, driving space weather that affects the habitability and detection of exoplanets. Owing to the intrinsic difficulty…
A core challenge in the interpretation of deep neural networks is identifying commonalities between the underlying algorithms implemented by distinct networks trained for the same task. Motivated by this problem, we introduce DYNAMO, an…
Context. Two candidate mechanisms have recently been considered for the nonlinear modulation of solar cycle amplitudes. Tilt quenching (TQ) is a negative feedback between cycle amplitude and the mean tilt angle of bipolar active regions…
After summarizing the relevant observational data, we discuss how a study of flux tube dynamics in the solar convection zone helps us to understand the formation of sunspots. Then we introduce the flux transport dynamo model and assess its…
Neural mass models are used to simulate cortical dynamics and to explain the electrical and magnetic fields measured using electro- and magnetoencephalography. Simulations evince a complex phase-space structure for these kinds of models;…
The Sun exhibits an 11-year cyclic variation, maintained by dynamo action in the solar interior. Mean-field flux transport dynamo models have successfully reproduced most of the features observed in solar cycles, while the model includes…
We analyse the role of a fluctuating alpha-effect in alpha-omega dynamo models, and show that there is a mechanism for magnetic field generation, valid at large scale separation, deriving from the interaction of mean shear and a fluctuating…
Nowadays, neural networks are widely used in many applications as artificial intelligence models for learning tasks. Since typically neural networks process a very large amount of data, it is convenient to formulate them within the…
We investigate a disordered multi-dimensional linear system in which the interaction parameters vary stochastically in time with defined temporal correlations. We refer to this type of disorder as "annealed", in contrast to quenched…
In this thesis, various studies are performed leading to better understanding of the 11-year solar cycle and its theoretical modeling with the flux transport dynamo model. Although this is primarily a theoretical thesis, there is a part…
Prediction of the Sun's magnetic activity is important because of its effect on space environment and climate. However, recent efforts to predict the amplitude of the solar cycle have resulted in diverging forecasts with no consensus.…
We present a novel numerical approach aiming at computing equilibria and dynamics structures of magnetized plasmas in coronal environments. A technique based on the use of neural networks that integrates the partial differential equations…
The computational capabilities of a neural network are widely assumed to be determined by its static architecture. Here we challenge this view by establishing that a fixed neural structure can operate in fundamentally different…
Global and semi-global convective dynamo simulations of solar-like stars are known to show a transition from an anti-solar (fast poles, slow equator) to solar-like (fast equator, slow poles) differential rotation (DR) for increasing…
Using a rotating flat layer heated from below as an example, we consider effects which lead to stabilizing an exponentially growing magnetic field in magnetostrophic convection in transition from the kinematic dynamo to the full non-linear…
The backreaction of the Lorentz force on the alpha-effect is studied in the limit of small magnetic and fluid Reynolds numbers, using the first order smoothing approximation (FOSA) to solve both the induction and momentum equations. Both…
The changing magnetic fields of the Sun are generated and maintained by a solar dynamo, the exact nature of which remains an unsolved fundamental problem in solar physics. Our objective in this paper is to investigate the role and impact of…
We present a three-dimensional numerical model for the generation and evolution of the magnetic field in the solar convection zone, in which sunspots are produced and contribute to the cyclic reversal of the large-scale magnetic field. We…
In this work we study the phenomenological consequences of the dependence of mass varying neutrinos on the neutrino density in the Sun, which we precisely compute in each point along the neutrino trajectory. We find that a generic…