Related papers: Bayesian inference of solar and stellar magnetic f…
Magnetic fields are regarded as a crucial element for our understanding of stellar physics. They can be studied with a variety of methods which provide complementary - and sometimes contradictory - information about the structure, strength…
In astronomical and cosmological studies one often wishes to infer some properties of an infinite-dimensional field indexed within a finite-dimensional metric space given only a finite collection of noisy observational data. Bayesian…
We evaluate the three-photon vertex functions at order $B$ and $B^{2}$ in a weak constant magnetic field at finite temperature and density with on shell external lines. Their application to the study of the photon splitting process leads to…
Laser-based searches of the yet unobserved vacuum birefringence might be sensitive for very light hypothetical particles carrying a tiny fraction of the electron charge. We show that, with the help of contemporary techniques, polarimetric…
We consider the prediction of weak effects in a multiple-output regression setup, when covariates are expected to explain a small amount, less than $\approx 1%$, of the variance of the target variables. To facilitate the prediction of the…
An extremely weak circularly polarized signature was recently discovered in spectral lines of the chemically peculiar Am star Sirius A. A weak surface magnetic field was proposed to account for the observed polarized signal, but the shape…
In this paper, we explore the determination of a spectral emissivity profile that closely matches real data, intended for use as an initial guess and/or a-priori information in a retrieval code. Our approach employs a Bayesian method that…
Zeeman Doppler Imaging is a powerful tool for characterizing the strength and topology of stellar magnetic fields. In this research note, we present a new way to visualize the typical results from ZDI for an ensemble of stars, addressing…
The polarization of light is a critically under-utilized, rich source of information in astronomy. For stars in particular, surface magnetism polarization that can be detected and measured with spectro-polarimetry. Many questions about…
A Bayesian analysis of the probability of a signal in the presence of background is developed, and criteria are proposed for claiming evidence for, or the discovery of a signal. The method is general and in particular applicable to sparsely…
We study Bayesian inference methods for solving linear inverse problems, focusing on hierarchical formulations where the prior or the likelihood function depend on unspecified hyperparameters. In practice, these hyperparameters are often…
Characteristics of the depression contribution functions are studied for the Stokes line profiles formed in a magnetic field. The form of the depression functions depends mainly on the strength of splitting and the Zeeman component…
Solar flares are large-scale releases of energy in the solar atmosphere, which are characterised by rapid changes in the hydrodynamic properties of plasma from the photosphere to the corona. Solar physicists have typically attempted to…
Observational constraints on stellar magnetic fields are essential to both stellar and planetary physics. Recent studies revealed the diversity and evolution of large-scale magnetic fields in low-mass stars. These large-scale fields only…
Solar and stellar magnetic patches (i.e., magnetic fluxes that reach the surface from the interior) are believed to be the primary sources of a star's atmospheric conditions. Hence, detecting and identifying these features (also known as…
We consider Bayesian estimate of static magnetic field, characterized by a prior Gaussian probability distribution, in systems of a few electron quantum dot spins interacting with infinite temperature spin environment via hyperfine…
Recently, there has been a revival of interest in mechanisms for changing the spin polarization of an electron beam on transmission through, or reflection from, a magnetic surface. An understanding of these mechanisms would allow the use of…
Bayesian field theory denotes a nonparametric Bayesian approach for learning functions from observational data. Based on the principles of Bayesian statistics, a particular Bayesian field theory is defined by combining two models: a…
Stellar magnetic dynamos are driven by rotation, rapidly rotating stars produce stronger magnetic fields than slowly rotating stars do. The Zeeman effect is the most important indicator of magnetic fields, but Zeeman broadening must be…
We consider imaging of solar flares from NASA RHESSI data as a parametric imaging problem, where flares are represented as a finite collection of geometric shapes. We set up a Bayesian model in which the number of objects forming the image…