Stellar Oscillations Network Group

Stellar Oscillations Network Group (SONG) is an initiative aimed at designing and building a network of 1m-class telescopes dedicated to asteroseismology and planet hunting. SONG will have 8 identical telescope nodes each equipped with a high-resolution spectrograph and an iodine cell for obtaining precision radial velocities and a CCD camera for guiding and imaging purposes. The main asteroseismology targets for the network are the brightest (V<6) stars. In order to improve performance and reduce maintenance costs the instrumentation will only have very few modes of operation. In this contribution we describe the motivations for establishing a network, the basic outline of SONG and the expected performance.Comment: Proc. Vienna Workshop on the Future of Asteroseismology, 20 - 22 September 2006. Comm. in Asteroseismology, Vol. 150, in the pres

Solar-like oscillations in the G8 V star tau Ceti

We used HARPS to measure oscillations in the low-mass star tau Cet. Although the data were compromised by instrumental noise, we have been able to extract the main features of the oscillations. We found tau Cet to oscillate with an amplitude that is about half that of the Sun, and with a mode lifetime that is slightly shorter than solar. The large frequency separation is 169 muHz, and we have identified modes with degrees 0, 1, 2, and 3. We used the frequencies to estimate the mean density of the star to an accuracy of 0.45% which, combined with the interferometric radius, gives a mass of 0.783 +/- 0.012 M_sun (1.6%).Comment: accepted for publication in A&

A Stellar Model-fitting Pipeline for Solar-like Oscillations

Over the past two decades, helioseismology has revolutionized our understanding of the interior structure and dynamics of the Sun. Asteroseismology will soon place this knowledge into a broader context by providing structural data for hundreds of Sun-like stars. Solar-like oscillations have already been detected from the ground in several stars, and NASA's Kepler mission is poised to unleash a flood of stellar pulsation data. Deriving reliable asteroseismic information from these observations demands a significant improvement in our analysis methods. We report the initial results of our efforts to develop an objective stellar model-fitting pipeline for asteroseismic data. The cornerstone of our automated approach is an optimization method using a parallel genetic algorithm. We describe the details of the pipeline and we present the initial application to Sun-as-a-star data, yielding an optimal model that accurately reproduces the known solar properties.Comment: 5 pages, 2 figs, Stellar Pulsation: Challenges for Theory and Observation (proceedings to be published by AIP

On detecting the large separation in the autocorrelation of stellar oscillation times series

The observations carried out by the space missions CoRoT and Kepler provide a large set of asteroseismic data. Their analysis requires an efficient procedure first to determine if the star is reliably showing solar-like oscillations, second to measure the so-called large separation, third to estimate the asteroseismic information that can be retrieved from the Fourier spectrum. We develop in this paper a procedure, based on the autocorrelation of the seismic Fourier spectrum. We have searched for criteria able to predict the output that one can expect from the analysis by autocorrelation of a seismic time series. First, the autocorrelation is properly scaled for taking into account the contribution of white noise. Then, we use the null hypothesis H0 test to assess the reliability of the autocorrelation analysis. Calculations based on solar and CoRoT times series are performed in order to quantify the performance as a function of the amplitude of the autocorrelation signal. We propose an automated determination of the large separation, whose reliability is quantified by the H0 test. We apply this method to analyze a large set of red giants observed by CoRoT. We estimate the expected performance for photometric time series of the Kepler mission. Finally, we demonstrate that the method makes it possible to distinguish l=0 from l=1 modes. The envelope autocorrelation function has proven to be very powerful for the determination of the large separation in noisy asteroseismic data, since it enables us to quantify the precision of the performance of different measurements: mean large separation, variation of the large separation with frequency, small separation and degree identification.Comment: A&A, in pres

Escherichia coli contamination and health aspects of soil and tomatoes (Solanum lycopersicum L.) subsurface drip irrigated with on-site treated domestic wastewater.

Faecal contamination of soil and tomatoes irrigated by sprinkler as well as surface and subsurface drip irrigation with treated domestic wastewater were compared in 2007 and 2008 at experimental sites in Crete and Italy. Wastewater was treated by Membrane Bio Reactor (MBR) technology, gravel filtration or UV-treatment before used for irrigation. Irrigation water, soil and tomato samples were collected during two cropping seasons and enumerated for the faecal indicator bacterium Escherichia coli and helminth eggs. The study found elevated levels of E. coli in irrigation water (mean: Italy 1753 cell forming unit (cfu) per 100 ml and Crete 488 cfu per 100 ml) and low concentrations of E. coli in soil (mean: Italy 95 cfu g(-1) and Crete 33 cfu g(-1)). Only two out of 84 tomato samples in Crete contained E. coli (mean: 2700 cfu g(-1)) while tomatoes from Italy were free of E. coli. No helminth eggs were found in the irrigation water or on the tomatoes from Crete. Two tomato samples out of 36 from Italy were contaminated by helminth eggs (mean: 0.18 eggs g(-1)) and had been irrigated with treated wastewater and tap water, respectively. Pulsed Field Gel Electrophoresis DNA fingerprints of E. coli collected during 2008 showed no identical pattern between water and soil isolates which indicates contribution from other environmental sources with E. coli, e.g. wildlife. A quantitative microbial risk assessment (QMRA) model with Monte Carlo simulations adopted by the World Health Organization (WHO) found the use of tap water and treated wastewater to be associated with risks that exceed permissible limits as proposed by the WHO (1.0 × 10(-3) disease risk per person per year) for the accidental ingestion of irrigated soil by farmers (Crete: 0.67 pppy and Italy: 1.0 pppy). The QMRA found that the consumption of tomatoes in Italy was deemed to be safe while permissible limits were exceeded in Crete (1.0 pppy). Overall the quality of tomatoes was safe for human consumption since the disease risk found on Crete was based on only two contaminated tomato samples. It is a fundamental limitation of the WHO QMRA model that it is not based on actual pathogen numbers, but rather on numbers of E. coli converted to estimated pathogen numbers, since it is widely accepted that there is poor correlation between E. coli and viral and parasite pathogens. Our findings also stress the importance of the external environment, typically wildlife, as sources of faecal contamination