The nature of p-modes and granulation in HD 49933 observed by CoRoT

Context: Recent observations of HD49933 by the space-photometric mission CoRoT provide photometric evidence of solar type oscillations in a star other than our Sun. The first published reduction, analysis, and interpretation of the CoRoT data yielded a spectrum of p-modes with l = 0, 1, and 2. Aims: We present our own analysis of the CoRoT data in an attempt to compare the detected pulsation modes with eigenfrequencies of models that are consistent with the observed luminosity and surface temperature. Methods: We used the Gruberbauer et al. frequency set derived based on a more conservative Bayesian analysis with ignorance priors and fit models from a dense grid of model spectra. We also introduce a Bayesian approach to searching and quantifying the best model fits to the observed oscillation spectra. Results: We identify 26 frequencies as radial and dipolar modes. Our best fitting model has solar composition and coincides within the error box with the spectroscopically determined position of HD49933 in the H-R diagram. We also show that lower-than-solar Z models have a lower probability of matching the observations than the solar metallicity models. To quantify the effect of the deficiencies in modeling the stellar surface layers in our analysis, we compare adiabatic and nonadiabatic model fits and find that the latter reproduces the observed frequencies better.Comment: accepted to be published in A&A, 9 pages, 5 figure

A low-mass stellar companion of the planet host star HD75289

We report on the detection of a new low-mass stellar companion of HD75289, a G0V star that harbors one known radial-velocity planet (Udry et al. 2000). Comparing an image of 2MASS with an image we obtained with SofI at the ESO 3.58m NTT three years later, we detected a co-moving companion located 21.465+-0.023arcsecs (621+-10AU at 29pc) east of HD75289. A second SofI image taken 10 months later confirmed the common proper motion of HD75289B with its host star. The infrared spectrum and colors of the companion are consistent with an M2 to M5 main-sequence star at the distance of HD75289. No further (sub)stellar companion down to H = 19mag could be detected. With the SofI detection limit we can rule out additional stellar companions beyond 140AU and substellar companions with masses m > 0.050Msun from 400AU up to 2000AU.Comment: accepted in A&

On the detection of Lorentzian profiles in a power spectrum: A Bayesian approach using ignorance priors

Aims. Deriving accurate frequencies, amplitudes, and mode lifetimes from stochastically driven pulsation is challenging, more so, if one demands that realistic error estimates be given for all model fitting parameters. As has been shown by other authors, the traditional method of fitting Lorentzian profiles to the power spectrum of time-resolved photometric or spectroscopic data via the Maximum Likelihood Estimation (MLE) procedure delivers good approximations for these quantities. We, however, show that a conservative Bayesian approach allows one to treat the detection of modes with minimal assumptions (i.e., about the existence and identity of the modes). Methods. We derive a conservative Bayesian treatment for the probability of Lorentzian profiles being present in a power spectrum and describe an efficient implementation that evaluates the probability density distribution of parameters by using a Markov-Chain Monte Carlo (MCMC) technique. Results. Potentially superior to "best-fit" procedure like MLE, which only provides formal uncertainties, our method samples and approximates the actual probability distributions for all parameters involved. Moreover, it avoids shortcomings that make the MLE treatment susceptible to the built-in assumptions of a model that is fitted to the data. This is especially relevant when analyzing solar-type pulsation in stars other than the Sun where the observations are of lower quality and can be over-interpreted. As an example, we apply our technique to CoRoT observations of the solar-type pulsator HD 49933.Comment: 12 pages, 11 figures, accepted for publication in Astronomy and Astrophysic

ROTSE observations of the young cluster IC 348

CCD observations of stars in the young cluster IC 348 were obtained from 2004 August to 2005 January with a 0.45 m ROTSEIIId robotic reflecting telescope at the Turkish National Observatory site, Bakirlitepe, Turkey. The timing analysis of selected stars whose X-Ray counterpart were detected by Chandra X-Ray Observatory were studied. The time series of stars were searched for rotational periodicity by using different period search methods. 35 stars were found to be periodic with periods ranging from 0.74 to 32.3 days. Eighteen of the 35 periodic stars were new detections. Four of the new detections were CTTSs and the others were WTTSs and G type (or unknown spectral class) stars. In this study, we confirmed the stability of rotation periods of TTauri stars. The periods obtained by Cohen et al. and us were different by 1%. We also confirmed the 3.24 h pulsation period of H254 which is a delta Scuti type star as noted by Ripepi et al. but the other periods detected by them were not found. We examined correlation between X-ray luminosity and rotational period of our sample of TTSs. There is a decline in the rotational period with X-ray luminosity for late type TTSs.Comment: 15 pages, 14 figures, accepted for publication in Astronomical Journa

An Investigation of the Effects of Categorization and Discrimination Training on Auditory Perceptual Space

Psychophysical phenomena such as categorical perception and the perceptual magnet effect indicate that our auditory perceptual spaces are warped for some stimuli. This paper investigates the effects of two different kinds of training on auditory perceptual space. It is first shown that categorization training, in which subjects learn to identify stimuli within a particular frequency range as members of the same category, can lead to a decrease in sensitivity to stimuli in that category. This phenomenon is an example of acquired similarity and apparently has not been previously demonstrated for a category-relevant dimension. Discrimination training with the same set of stimuli was shown to have the opposite effect: subjects became more sensitive to differences in the stimuli presented during training. Further experiments investigated some of the conditions that are necessary to generate the acquired similarity found in the first experiment. The results of these experiments are used to evaluate two neural network models of the perceptual magnet effect. These models, in combination with our experimental results, are used to generate an experimentally testable hypothesis concerning changes in the brain's auditory maps under different training conditions.Alfred P. Sloan Foundation and the National institutes of Deafness and other Communication Disorders (R29 02852); Air Force Office of Scientific Research (F49620-98-1-0108

Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature)

Reactive gases and aerosols are produced by terrestrial ecosystems, processed within plant canopies, and can then be emitted into the above-canopy atmosphere. Estimates of the above-canopy fluxes are needed for quantitative earth system studies and assessments of past, present and future air quality and climate. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) is described and used to quantify net terrestrial biosphere emission of isoprene into the atmosphere. MEGAN is designed for both global and regional emission modeling and has global coverage with ~1 km² spatial resolution. Field and laboratory investigations of the processes controlling isoprene emission are described and data available for model development and evaluation are summarized. The factors controlling isoprene emissions include biological, physical and chemical driving variables. MEGAN driving variables are derived from models and satellite and ground observations. Tropical broadleaf trees contribute almost half of the estimated global annual isoprene emission due to their relatively high emission factors and because they are often exposed to conditions that are conducive for isoprene emission. The remaining flux is primarily from shrubs which have a widespread distribution. The annual global isoprene emission estimated with MEGAN ranges from about 500 to 750 Tg isoprene (440 to 660 Tg carbon) depending on the driving variables which include temperature, solar radiation, Leaf Area Index, and plant functional type. The global annual isoprene emission estimated using the standard driving variables is ~600 Tg isoprene. Differences in driving variables result in emission estimates that differ by more than a factor of three for specific times and locations. It is difficult to evaluate isoprene emission estimates using the concentration distributions simulated using chemistry and transport models, due to the substantial uncertainties in other model components, but at least some global models produce reasonable results when using isoprene emission distributions similar to MEGAN estimates. In addition, comparison with isoprene emissions estimated from satellite formaldehyde observations indicates reasonable agreement. The sensitivity of isoprene emissions to earth system changes (e.g., climate and land-use) demonstrates the potential for large future changes in emissions. Using temperature distributions simulated by global climate models for year 2100, MEGAN estimates that isoprene emissions increase by more than a factor of two. This is considerably greater than previous estimates and additional observations are needed to evaluate and improve the methods used to predict future isoprene emissions

Toward a New Kind of Asteroseismic Grid Fitting

Recent developments in instrumentation (e.g., in particular the Kepler and CoRoT satellites) provide a new opportunity to improve the models of stellar pulsations. Surface layers, rotation, and magnetic fields imprint erratic frequency shifts, trends, and other non-random behavior in the frequency spectra. As our observational uncertainties become smaller, these are increasingly important and difficult to deal with using standard fitting techniques. To improve the models, new ways to compare their predictions with observations need to be conceived. In this paper we present a completely probabilistic (Bayesian) approach to asteroseismic model fitting. It allows for varying degrees of prior mode identification, corrections for the discrete nature of the grid, and most importantly implements a treatment of systematic errors, such as the "surface effects." It removes the need to apply semi- empirical corrections to the observations prior to fitting them to the models and results in a consistent set of probabilities with which the model physics can be probed and compared. As an example, we show a detailed asteroseismic analysis of the Sun. We find a most probable solar age, including a 35 +- 5 million year pre-main sequence phase, of 4.591 billion years, and initial element mass fractions of X_0 = 0.72, Y_0 = 0.264, Z_0 = 0.016, consistent with recent asteroseismic and non-asteroseismic studies.Comment: 15 pages, 5 figures, accepted for publication in The Astrophysical Journal; v2 contains minor changes made in the proofs (updated references & corrected typos