In contrast to the situation in a laboratory, the study of the solar atmosphere has to be pursued without direct access to the physical conditions of interest...
Bayesian cosmic density field inference from redshift space dark matter maps
We present a self-consistent Bayesian formalism to sample the primordial density fields compatible with a set of dark matter density tracers after a cosmic...
Bayesian deep learning for cosmic volumes with modified gravity
Context. The new generation of galaxy surveys will provide unprecedented data that will allow us to test gravity deviations at cosmological scales at a much...
Bayesian distances and extinctions for giants observed by Kepler and APOGEE
We present a first determination of distances and extinctions for individual stars in the first release of the APOKASC catalogue, built from the joint efforts...
Bayesian Evidence for a Nonlinear Damping Model for Coronal Loop Oscillations
Recent observational and theoretical studies indicate that the damping of solar coronal loop oscillations depends on the oscillation amplitude. We consider two...
Bayesian evidence for two slow-wave damping models in hot coronal loops
We computed the evidence in favour of two models, one based on field-aligned thermal conduction alone and another that includes thermal misbalance as well, to...
Bayesian inference methodology to characterize the dust emissivity at far-infrared and submillimeter frequencies
We present a Bayesian inference method to characterize the dust emission properties using the well-known dust-${\rm H\,{\small I}}$ correlation in the diffuse...
Bayesian Inference of Solar and Stellar Magnetic Fields in the Weak-field Approximation
The weak-field approximation is one of the simplest models that allows us to relate the observed polarization induced by the Zeeman effect with the magnetic...
Context: Inversion techniques are the most powerful methods to obtain information about the thermodynamical and magnetic properties of solar and stellar...