A systematic search for gamma Dor and gamma Dor - delta Scuti hybrid pulsators was conducted on the CoRoT LRa01 Exo-archive yielding a total of 418 gamma Dor and 274 hybrid candidates. After an automatic jump correction 194 and 167 respectively, show
no more obvious jumps and were investigated in more detail. For about 25% of these candidates classification spectra from the Anglo-Australian Observatory (AAO) are available. The detailed frequency analysis and a check for combination frequencies together with spectroscopic information allowed us to identify I) 34 gamma Dor stars which show very different pulsation spectra where mostly two modes dominate. Furthermore, a search for regularities in their oscillation spectra allowed to derive recurrent period spacings for 5 of these gamma Dor stars. II) 25 clear hybrid pulsators showing frequencies in the gamma Dor and delta Sct domain and are of A-F spectral type.
The current knowledge of the abundance pattern in delta Scuti stars is based on the analysis of just a few field stars. We aim to determine the general chemical properties of the atmospheres of delta Scuti stars based on a statistically relevant samp
le of stars and will investigate whether the abundance pattern is close to solar, an assumption generally made for pulsation models. We have analysed high-resolution, high signal-to-noise ratio spectra of seven field delta Scuti stars. We derived the fundamental parameters and the photospheric abundances and compared them to a similar sample of cluster delta Scuti stars. With the use of a t-test we demonstrated that there is no difference between the two samples, which allows us to merge them, resulting in a sample of fifteen delta Scuti stars. We did not find any substantial difference between the abundance pattern of our sample of delta Scuti stars and a sample of normal early A- and late F-type stars. One field star in our sample, HD 124953, is most likely a pulsating Am star.
The identification of increasingly smaller signal from objects observed with a non-perfect instrument in a noisy environment poses a challenge for a statistically clean data analysis. We want to compute the probability of frequencies determined in va
rious data sets to be related or not, which cannot be answered with a simple comparison of amplitudes. Our method provides a statistical estimator for a given signal with different strengths in a set of observations to be of instrumental origin or to be intrinsic. Based on the spectral significance as an unbiased statistical quantity in frequency analysis, Discrete Fourier Transforms (DFTs) of target and background light curves are comparatively examined. The individual False-Alarm Probabilities are used to deduce conditional probabilities for a peak in a target spectrum to be real in spite of a corresponding peak in the spectrum of a background or of comparison stars. Alternatively, we can compute joint probabilities of frequencies to occur in the DFT spectra of several data sets simultaneously but with different amplitude, which leads to composed spectral significances. These are useful to investigate a star observed in different filters or during several observing runs. The composed spectral significance is a measure for the probability that none of coinciding peaks in the DFT spectra under consideration are due to noise. Cinderella is a mathematical approach to a general statistical problem. Its potential reaches beyond photometry from ground or space: to all cases where a quantitative statistical comparison of periodicities in different data sets is desired. Examples for the composed and the conditional Cinderella mode for different observation setups are presented.
Context: Several approaches to estimate frequency, phase and amplitude errors in time series analyses were reported in the literature, but they are either time consuming to compute, grossly overestimating the error, or are based on empirically determ
ined criteria. Aims: A simple, but realistic estimate of the frequency uncertainty in time series analyses. Methods: Synthetic data sets with mono- and multi-periodic harmonic signals and with randomly distributed amplitude, frequency and phase were generated and white noise added. We tried to recover the input parameters with classical Fourier techniques and investigated the error as a function of the relative level of noise, signal and frequency difference. Results: We present simple formulas for the upper limit of the amplitude, frequency and phase uncertainties in time-series analyses. We also demonstrate the possibility to detect frequencies which are separated by less than the classical frequency resolution and that the realistic frequency error is at least 4 times smaller than the classical frequency resolution.
EE Cam is a previously little studied Delta Scuti pulsator with amplitudes between those of the HADS (High-Amplitude Delta Scuti stars) group and the average low-amplitude pulsators. Since the size of stellar rotation determines both which pulsation
modes are selected by the star as well as their amplitudes, the star offers a great opportunity to examine the astrophysical connections. Extensive photometric measurements covering several months were carried out. 15 significant pulsation frequencies were extracted. The dominant mode at 4.934 cd$^{-1}$ was identified as a radial mode by examining the phase shifts at different wavelengths. Medium-dispersion spectra yielded a $vsin i$ value of $40 pm 3$ km s$^{-1}$. This shows that EE Cam belongs to the important transition region between the HADS and normal Delta Scuti stars.
