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Register a new userBESTP -- An Automated Bayesian Modeling Tool for Asteroseismology
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Asteroseismic observations are crucial to constrain stellar models with precision. Bayesian Estimation of STellar Parameters (BESTP) is a tool that utilizes Bayesian statistics and nested sampling Monte Carlo algorithm to search for the stellar models that best match a given set of classical and asteroseismic constraints from observations. The computation and evaluation of models are efficiently performed in an automated and a multi-threaded way. To illustrate the capabilities of BESTP, we estimate fundamental stellar properties for the Sun and the red-giant star HD 222076. In both cases, we find models that are consistent with the observations. We also evaluate the improvement in the precision of stellar parameters when the oscillation frequencies of individual modes are included as constraints, compared to the case when only the the large frequency separation is included. For the solar case, the uncertainties of estimated masses, radii and ages are reduced by 0.7%, 0.3% and 8% respectively. For HD 222076, they are reduced even more noticeably by 2%, 0.5% and 4.7%. We also note an improvement of 10% for the age of HD 222076 when the Gaia parallax is included as a constraint compared to the case when only the large separation is included as constraint.
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An automated counterexample reproducibility tool based on MATLAB is presented, called DSValidator, with the goal of reproducing counterexamples that refute specific properties related to digital systems. We exploit counterexamples generated by the Digital System Verifier (DSVerifier), which is a model checking tool based on satisfiability modulo theories for digital systems. DSValidator reproduces the execution of a digital system, relating its input with the counterexample, in order to establish trust in a verification result. We show that DSValidator can validate a set of intricate counterexamples for digital controllers used in a real quadrotor attitude system within seconds and also expose incorrect verification results in DSVerifier. The resulting toolbox leverages the potential of combining different verification tools for validating digital systems via an exchangeable counterexample format.
The advent of the Web brought about major changes in the way people search for jobs and companies look for suitable candidates. As more employers and recruitment firms turn to the Web for job candidate search, an increasing number of people turn to the Web for uploading and creating their online resumes. Resumes are often the first source of information about candidates and also the first item of evaluation in candidate selection. Thus, it is imperative that resumes are complete, free of errors and well-organized. We present an automated resume evaluation tool called CareerMapper. Our tool is designed to conduct a thorough review of a users LinkedIn profile and provide best recommendations for improved online resumes by analyzing a large number of online user profiles.
The detection of solar-like oscillations in G and K giants with the CoRoT and Kepler space-based satellites allows robust constraints to be set on the mass and radius of such stars. The availability of these constraints for thousands of giants sampling different regions of the Galaxy promises to enrich our understanding on the Milky Ways constituents. In this contribution we briefly recall which are the relevant constraints that red-giant seismology can currently provide to the study of stellar populations. We then present, for a few nearby stars, the comparison between radius and mass determined using seismic scaling relations and those obtained by other methods.
We study 23 previously published Kepler targets to perform a consistent grid-based Bayesian asteroseismic analysis and compare our results to those obtained via the Asteroseismic Modelling Portal (AMP). We find differences in the derived stellar parameters of many targets and their uncertainties. While some of these differences can be attributed to systematic effects between stellar evolutionary models, we show that the different methodologies deliver incompatible uncertainties for some parameters. Using non-adiabatic models and our capability to measure surface effects, we also investigate the dependency of these surface effects on the stellar parameters. Our results suggest a dependence of the magnitude of the surface effect on the mixing length parameter which also, but only minimally, affects the determination of stellar parameters. While some stars in our sample show no surface effect at all, the most significant surface effects are found for stars that are close to the Suns position in the HR diagram.
Observations from the Kepler satellite were recently published for three bright G-type stars, which were monitored during the first 33.5d of science operations. One of these stars, KIC 11026764, exhibits a characteristic pattern of oscillation frequencies suggesting that the star has evolved significantly. We have derived initial estimates of the properties of KIC 11026764 from the oscillation frequencies observed by Kepler, combined with ground-based spectroscopic data. We present preliminary results from detailed modeling of this star, employing a variety of independent codes and analyses that attempt to match the asteroseismic and spectroscopic constraints simultaneously.
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