Regions of rapid variation in the internal structure of a star are often referred to as acoustic glitches since they create a characteristic periodic signature in the frequencies of p modes. Here we examine the localized disturbance arising from the
helium second ionization zone in red giant branch and clump stars. More specifically, we determine how accurately and precisely the parameters of the ionization zone can be obtained from the oscillation frequencies of stellar models. We use models produced by three different generation codes that not only cover a wide range of stages of evolution along the red giant phase but also incorporate different initial helium abundances. We discuss the conditions under which such fits robustly and accurately determine the acoustic radius of the second ionization zone of helium. The determined radii of the ionization zones as inferred from the mode frequencies were found to be coincident with the local maximum in the first adiabatic exponent described by the models, which is associated with the outer edge of the second ionization zone of helium. Finally, we consider whether this method can be used to distinguish stars with different helium abundances. Although a definite trend in the amplitude of the signal is observed any distinction would be difficult unless the stars come from populations with vastly different helium abundances or the uncertainties associated with the fitted parameters can be reduced. However, application of our methodology could be useful for distinguishing between different populations of red giant stars in globular clusters, where distinct populations with very different helium abundances have been observed.
Unresolved Doppler velocity measurements are not homogenous across the solar disc (Brookes et al. 1978). We consider one cause of the inhomogeneity that originates from the BiSON instrumentation itself: the intensity of light observed from a region o
n the solar disc is dependent on the distance between that region on the image of the solar disc formed in the instrument and the detector. The non-uniform weighting affects the realization of the solar noise and the amplitudes of the solar oscillations observed by a detector. An offset velocity, which varies with time, is observed in BiSON data and has consequences for the long-term stability of observations. We have attempted to model, in terms of the inhomogeneous weighting, the average observed offset velocity.
The Birmingham Solar-Oscillations Network (BiSON) has been collecting data for over 30yrs and so observations span nearly three 11yr solar activity cycles. This allows us to address important questions concerning the solar cycle and its effect on sol
ar oscillations, such as: how consistent is the acoustic behaviour from one cycle to the next? We have used the p-mode frequencies observed in BiSON data from one solar activity cycle (cycle 22) to predict the mode frequencies that were observed in the next activity cycle (cycle 23). Some bias in the predicted frequencies was observed when short 108d time series were used to make the predictions. We also found that the accuracy of the predictions was dependent on which activity proxy was used to make the predictions and on the length of the relevant time series.
We make predictions of the detectability of low-frequency p modes. Estimates of the powers and damping times of these low-frequency modes are found by extrapolating the observed powers and widths of higher-frequency modes with large observed signal-t
o-noise ratios. The extrapolations predict that the low-frequency modes will have small signal-to-noise ratios and narrow widths in a frequency-power spectrum. Monte Carlo simulations were then performed where timeseries containing mode signals and normally distributed Gaussian noise were produced. The mode signals were simulated to have the powers and damping times predicted by the extrapolations. Various statistical tests were then performed on the frequency-amplitude spectra formed from these timeseries to investigate the fraction of spectra in which the modes could be detected. The results of these simulations were then compared to the number of p-modes candidates observed in real Sun-as-a-star data at low frequencies. The fraction of simulated spectra in which modes were detected decreases rapidly as the frequency of modes decreases and so the fraction of simulations in which the low-frequency modes were detected was very small. However, increasing the signal-to-noise (S/N) ratio of the low-frequency modes by a factor of 2 above the extrapolated values led to significantly more detections. Therefore efforts should continue to further improve the quality of solar data that is currently available.
