Evaluating kernels on Xeon Phi to accelerate Gysela application

This work describes the challenges presented by porting parts ofthe Gysela code to the Intel Xeon Phi coprocessor, as well as techniques used for optimization, vectorization and tuning that can be applied to other applications. We evaluate the performance of somegeneric micro-benchmark on Phi versus Intel Sandy Bridge. Several interpolation kernels useful for the Gysela application are analyzed and the performance are shown. Some memory-bound and compute-bound kernels are accelerated by a factor 2 on the Phi device compared to Sandy architecture. Nevertheless, it is hard, if not impossible, to reach a large fraction of the peek performance on the Phi device,especially for real-life applications as Gysela. A collateral benefit of this optimization and tuning work is that the execution time of Gysela (using 4D advections) has decreased on a standard architecture such as Intel Sandy Bridge.Comment: submitted to ESAIM proceedings for CEMRACS 2014 summer school version reviewe

Adaptive Covariance Estimation with model selection

We provide in this paper a fully adaptive penalized procedure to select a covariance among a collection of models observing i.i.d replications of the process at fixed observation points. For this we generalize previous results of Bigot and al. and propose to use a data driven penalty to obtain an oracle inequality for the estimator. We prove that this method is an extension to the matricial regression model of the work by Baraud

Asteroseismic Theory of Rapidly Oscillating Ap Stars

This paper reviews some of the important advances made over the last decade concerning theory of roAp stars.Comment: 9 pages, 5 figure

Contribution of the screened self-energy to the Lamb shift of quasidegenerate states

Expressions for the effective Quantum Electrodynamics (QED) Hamiltonian due to self-energy screening (self-energy correction to the electron-electron interaction) are presented. We use the method of the two-time Green's function, which handles quasidegenerate atomic states. From these expression one can evaluate energy corrections to, e.g., 1s2p 3P1 and 1s2p 1P1 in helium and two-electron ions, to all orders in Z\alph

A large sample of calibration stars for Gaia: log g from Kepler and CoRoT

Asteroseismic data can be used to determine surface gravities with precisions of < 0.05 dex by using the global seismic quantities Deltanu and nu_max along with Teff and [Fe/H]. Surface gravity is also one of the four stellar properties to be derived by automatic analyses for 1 billion stars from Gaia data (workpackage GSP_Phot). We explore seismic data from MS F, G, K stars (solar-like stars) observed by Kepler as a potential calibration source for methods that Gaia will use for object characterisation (log g). We calculate log g for bright nearby stars for which radii and masses are known, and using their global seismic quantities in a grid-based method, we determine an asteroseismic log g to within 0.01 dex of the direct calculation, thus validating the accuracy of our method. We find that errors in Teff and mainly [Fe/H] can cause systematic errors of 0.02 dex. We then apply our method to a list of 40 stars to deliver precise values of surface gravity, i.e. sigma < 0.02 dex, and we find agreement with recent literature values. Finally, we explore the precision we expect in a sample of 400+ Kepler stars which have their global seismic quantities measured. We find a mean uncertainty (precision) on the order of <0.02 dex in log g over the full explored range 3.8 < log g < 4.6, with the mean value varying only with stellar magnitude (0.01 - 0.02 dex). We study sources of systematic errors in log g and find possible biases on the order of 0.04 dex, independent of log g and magnitude, which accounts for errors in the Teff and [Fe/H] measurements, as well as from using a different grid-based method. We conclude that Kepler stars provide a wealth of reliable information that can help to calibrate methods that Gaia will use, in particular, for source characterisation with GSP_Phot where excellent precision (small uncertainties) and accuracy in log g is obtained from seismic data.Comment: Accepted MNRAS, 15 pages (10 figures and 3 tables), v2=some rewording of two sentence