We introduce PHI, a fully Bayesian Markov chain Monte Carlo algorithm designed for the structural decomposition of galaxy images. PHI uses a triple layer...

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...

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...

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...

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...

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...

Aims: We develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar...

We perform a Bayesian parameter inference in the context of resonantly damped transverse coronal loop oscillations. The forward problem is solved in terms of...

Context. Non-radial oscillations, observed in thousands of red giants by the space missions CoRoT and Kepler, allow us to greatly improve our understanding of...