Probing the properties of Be star discs with spectroastrometry and NLTE radiative transfer modelling: beta CMi

While the presence of discs around classical Be stars is well established, their origin is still uncertain. To understand what processes result in the creation of these discs and how angular momentum is transported within them, their physical properties must be constrained. This requires comparing high spatial and spectral resolution data with detailed radiative transfer modelling. We present a high spectral resolution, R similar to 80 000, sub-milliarcsecond precision, spectroastrometric study of the circumstellar disc around the Be star beta CMi. The data are confronted with 3D, non-local thermodynamic equilibrium radiative transfer calculations to directly constrain the properties of the disc. Furthermore, we compare the data to disc models featuring two velocity laws: Keplerian, the prediction of the viscous disc model, and angular momentum conserving rotation. It is shown that the observations of beta CMi can only be reproduced using Keplerian rotation. The agreement between the model and the observed spectral energy distribution, polarization and spectroastrometric signature of beta CMi confirms that the discs around Be stars are well modelled as viscous decretion discs.

Influence diagnostics in Gaussian spatial linear models

Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmental sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. The purpose of this paper is to use diagnostic techniques to assess the sensitivity of the maximum-likelihood estimators, covariance functions and linear predictor to small perturbations in the data and/or the spatial linear model assumptions. The methodology is illustrated with two real data sets. The results allowed us to conclude that the presence of atypical values in the sample data have a strong influence on thematic maps, changing the spatial dependence structure.