Automated extraction of oscillation parameters for Kepler observations of solar-type stars

The recent launch of the Kepler space telescope brings the opportunity to study oscillations systematically in large numbers of solar-like stars. In the framework of the asteroFLAG project, we have developed an automated pipeline to estimate global oscillation parameters, such as the frequency of maximum power (nu_max) and the large frequency spacing (Delta_nu), for a large number of time series. We present an effective method based on the autocorrelation function to find excess power and use a scaling relation to estimate granulation timescales as initial conditions for background modelling. We derive reliable uncertainties for nu_max and Delta_nu through extensive simulations. We have tested the pipeline on about 2000 simulated Kepler stars with magnitudes of V~7-12 and were able to correctly determine nu_max and Delta_nu for about half of the sample. For about 20%, the returned large frequency spacing is accurate enough to determine stellar radii to a 1% precision. We conclude that the methods presented here are a promising approach to process the large amount of data expected from Kepler.Comment: 14 pages, 9 figures, accepted for publication in Communications in Asteroseismolog

Seismic constraints on rotation of Sun-like star and mass of exoplanet

Rotation is thought to drive cyclic magnetic activity in the Sun and Sun-like stars. Stellar dynamos, however, are poorly understood owing to the scarcity of observations of rotation and magnetic fields in stars. Here, inferences are drawn on the internal rotation of a distant Sun-like star by studying its global modes of oscillation. We report asteroseismic constraints imposed on the rotation rate and the inclination of the spin axis of the Sun-like star HD 52265, a principal target observed by the CoRoT satellite that is known to host a planetary companion. These seismic inferences are remarkably consistent with an independent spectroscopic observation (rotational line broadening) and with the observed rotation period of star spots. Furthermore, asteroseismology constrains the mass of exoplanet HD 52265b. Under the standard assumption that the stellar spin axis and the axis of the planetary orbit coincide, the minimum spectroscopic mass of the planet can be converted into a true mass of 1.85 (+0.52,-0.42) M_Jupiter, which implies that it is a planet, not a brown dwarf.Comment: Published in Proceedings of the National Academy of Sciences (5 pages, 5 figures, 3 tables). Available at http://www.pnas.org/cgi/doi/10.1073/pnas.130329111

Kepler-21b: A 1.6REarth Planet Transiting the Bright Oscillating F Subgiant Star HD 179070

We present Kepler observations of the bright (V=8.3), oscillating star HD 179070. The observations show transit-like events which reveal that the star is orbited every 2.8 days by a small, 1.6 R_Earth object. Seismic studies of HD 179070 using short cadence Kepler observations show that HD 179070 has a frequencypower spectrum consistent with solar-like oscillations that are acoustic p-modes. Asteroseismic analysis provides robust values for the mass and radius of HD 179070, 1.34{\pm}0.06 M{\circ} and 1.86{\pm}0.04 R{\circ} respectively, as well as yielding an age of 2.84{\pm}0.34 Gyr for this F5 subgiant. Together with ground-based follow-up observations, analysis of the Kepler light curves and image data, and blend scenario models, we conservatively show at the >99.7% confidence level (3{\sigma}) that the transit event is caused by a 1.64{\pm}0.04 R_Earth exoplanet in a 2.785755{\pm}0.000032 day orbit. The exoplanet is only 0.04 AU away from the star and our spectroscopic observations provide an upper limit to its mass of ~10 M_Earth (2-{\sigma}). HD 179070 is the brightest exoplanet host star yet discovered by Kepler.Comment: Accepted to Ap

Brainhack: a collaborative workshop for the open neuroscience community

International audienceBrainhack events offer a novel workshop format with participant-generated content that caters to the rapidly growing open neuroscience community. Including components from hackathons and unconferences, as well as parallel educational sessions, Brainhack fosters novel collaborations around the interests of its attendees. Here we provide an overview of its structure, past events, and example projects. Additionally, we outline current innovations such as regional events and post-conference publications. Through introducing Brainhack to the wider neuroscience community, we hope to provide a unique conference format that promotes the features of collaborative, open science

Software architectures to integrate workflow engines in science gateways

International audienceScience gateways often rely on workflow engines to execute applications on distributed infrastructures. We investigate six software architectures commonly used to integrate workflow engines into science gateways. In tight integration, the workflow engine shares software components with the science gateway. In service invocation, the engine is isolated and invoked through a specific software interface. In task encapsulation, the engine is wrapped as a computing task executed on the infrastructure. In the pool model, the engine is bundled in an agent that connects to a central pool to fetch and execute workflows. In nested workflows, the engine is integrated as a child process of another engine. In workflow conversion, the engine is integrated through workflow language conversion. We describe and evaluate these architectures with metrics for assessment of integration complexity, robustness, extensibility, scalability and functionality. Tight integration and task encapsulation are the easiest to integrate and the most robust. Extensibility is equivalent in most architectures. The pool model is the most scalable one and meta-workflows are only available in nested workflows and workflow conversion. These results provide insights for science gateway architects and developers

Mutations associated with neuropsychiatric conditions delineate functional brain connectivity dimensions contributing to autism and schizophrenia.

16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) remains unclear. Here we report an analysis of resting-state FC using magnetic resonance imaging data from 101 CNV carriers, 755 individuals with idiopathic ASD, SZ, or ADHD and 1,072 controls. We characterize CNV FC-signatures and use them to identify dimensions contributing to complex idiopathic conditions. CNVs have large mirror effects on FC at the global and regional level. Thalamus, somatomotor, and posterior insula regions play a critical role in dysconnectivity shared across deletions, duplications, idiopathic ASD, SZ but not ADHD. Individuals with higher similarity to deletion FC-signatures exhibit worse cognitive and behavioral symptoms. Deletion similarities identified at the connectivity level could be related to the redundant associations observed genome-wide between gene expression spatial patterns and FC-signatures. Results may explain why many CNVs affect a similar range of neuropsychiatric symptoms