Brendon J. Brewer

Die Serie Communications in Asteroseismology (CoAst) stellt eine international gefragte Plattform f

The measured properties of stellar oscillations can provide powerful constraints on the internal structure and composition of stars. To begin this process, oscillation frequencies must be extracted from the observational data, typically time series of the star's brightness or radial velocity. In this paper, a probabilistic model is introduced for inferring the frequencies and amplitudes of stellar oscillation modes from data, assuming that there is some periodic character to the oscillations, but that they may not be exactly sinusoidal. Effectively we fit damped oscillations to the time series, and hence the mode lifetime is also recovered. While this approach is computationally demanding for large time series (> 1500 points), it should at least allow improved analysis of observations of solar-like oscillations in subgiant and red giant stars, as well as sparse observations of semiregular stars, where the number of points in the time series is often low. The method is demonstrated on simulated data and then applied to radial velocity measurements of the red giant star xi Hydrae, yielding a mode lifetime between 0.41 and 2.65 days with 95% posterior probability. The large frequency separation between modes is ambiguous, however we argue that the most plausible value is 6.3 microHz, based on the radial velocity data and the star's position in the HR diagram.

We have observed oscillations in the nearby G2 subgiant star beta Hyi using high-precision velocity observations obtained over more than a week with the HARPS and UCLES spectrographs. The oscillation frequencies show a regular comb structure, as expected for solar-like oscillations, but with several l=1 modes being strongly affected by avoided crossings. The data, combined with those we obtained five years earlier, allow us to identify 28 oscillation modes. By scaling the large frequency separation from the Sun, we measure the mean density of beta Hyi to an accuracy of 0.6%. The amplitudes of the oscillations are about 2.5 times solar and the mode lifetime is 2.3 d. A detailed comparison of the mixed l=1 modes with theoretical models should allow a precise estimate of the age of the star.

Convection in stars excites resonant acoustic waves which depend on the sound speed inside the star, which in turn depends on properties of the stellar interior. Therefore, asteroseismology is an unrivaled method to probe the internal structure of a star. We made a seismic study of the metal-poor subgiant star nu Indi with the goal of constraining its interior structure. Our study is based on a time series of 1201 radial velocity measurements spread over 14 nights obtained from two sites, Siding Spring Observatory in Australia and ESO La Silla Observatory in Chile. The power spectrum of the high precision velocity time series clearly presents several identifiable peaks between 200 and 500 uHz showing regularity with a large and small spacing of 25.14 +- 0.09 uHz and 2.96 +- 0.22 uHz at 330 uHz. Thirteen individual modes have been identified with amplitudes in the range 53 to 173 cm/s. The mode damping time is estimated to be about 16 days (1-sigma range between 9 and 50 days), substantially longer than in other stars like the Sun, the alpha Cen system or the giant xi Hya.

We have observed oscillations in the nearby G2 subgiant star beta Hyi using high-precision velocity observations obtained over more than a week with the HARPS and UCLES spectrographs. The oscillation frequencies show a regular comb structure, as expected for solar-like oscillations, but with several l=1 modes being strongly affected by avoided crossings. The data, combined with those we obtained five years earlier, allow us to identify 28 oscillation modes. By scaling the large frequency separation from the Sun, we measure the mean density of beta Hyi to an accuracy of 0.6%. The amplitudes of the oscillations are about 2.5 times solar and the mode lifetime is 2.3 d. A detailed comparison of the mixed l=1 modes with theoretical models should allow a precise estimate of the age of the star.

In a previous paper, we outlined a new Bayesian method for inferring the properties of extended gravitational lenses given data in the form of resolved images. This method holds the most promise for optimally extracting information from the observed image, while providing reliable uncertainties in all parameters. Here, we apply the method to the well studied optical Einstein ring 0047-2808. Our results are in broad agreement with previous studies, showing that the density profile of the lensing galaxy is aligned within a few degrees of the light profile, and suggesting that the source galaxy (at redshift 3.6) is a binary system, although its size is only of order 1-2 kpc. We also find that the mass of the elliptical lensing galaxy enclosed by the image is (2.91 ± 0.01) × 10¹¹ M_☉. Our method is able to achieve improved resolution for the source reconstructions, although we also find that some of the uncertainties are greater than has been found in previous analyses, due to the inclusion of extra pixels and a more general lens model.

Stellar oscillations can provide a wealth of information about a star, which can be extracted from observed time series of the star's brightness or radial velocity. In this paper we address the question of how to extract as much information as possible from such a dataset. We have developed a Markov Chain Monte Carlo (MCMC) code that is able to infer the number of oscillation frequencies present in the signal and their values (with corresponding uncertainties), without having to fit the amplitudes and phases. Gaps in the data do not have any serious consequences for this method; in cases where severe aliasing exists, any ambiguity in the frequency determinations will be reflected in the results. It also allows us to infer parameters of the frequency pattern, such as the large separation Delta nu. We have previously applied this method to the star nu Indi (Bedding et al 2006), and here we describe the method fully and apply it to simulated datasets, showing that the code is able to give correct results even when some of the model assumptions are violated. In particular, the non-sinusoidal nature of the individual oscillation modes due to stochastic excitation and damping has no major impact on the usefulness of our approach.