Automated Determination of Stellar Parameters from Simulated Dispersed Images for DIVA

We have assessed how well stellar parameters (T_eff, logg and [Fe/H]) can be retrieved from low-resolution dispersed images to be obtained by the DIVA satellite. Although DIVA is primarily an all-sky astrometric mission, it will also obtain spectrophotometric information for about 13 million stars (operational limiting magnitude V ~ 13.5 mag). Constructional studies foresee a grating system yielding a dispersion of ~200nm/mm on the focal plane (first spectral order). For astrometric reasons there will be no cross dispersion which results in the overlapping of the first to third diffraction orders. The one-dimensional, position related intensity function is called a DISPI (DISPersed Intensity). We simulated DISPIS from synthetic spectra (...) for a limited range of metallicites i.e. our results are for [Fe/H] in the range -0.3 to 1 dex. We show that there is no need to deconvolve these low resolution signals in order to obtain basic stellar parameters. Using neural network methods and by including simulated data of DIVA's UV telescope, we can determine T_eff to an average accuracy of about 2% for DISPIS from stars with 2000 K < T_eff < 20000 K and visual magnitudes of V=13 mag (end of mission data). logg can be determined for all temperatures with an accuracy better than 0.25 dex for magnitudes brighter than V=12 mag. For low temperature stars with 2000 K < T_eff < 5000 K and for metallicities in the range -0.3 to +1 dex a determination of [Fe/H] is possible (to better than 0.2 dex) for these magnitudes. Additionally we examined the effects of extinction E(B-V) on DISPIS and found that it can be determined to better than 0.07 mag for magnitudes brighter than V=14 mag if the UV information is included.Comment: 12 pages, 8 figures, Accepted for publication in A&

Decentralization as an incentive scheme when regional differences are large

It has been suggested that large regional differences could be an obstacle to that part of the political accountability of office-holders which is based on yardstick competition among governments. The paper addresses that question and concludes that the obstacle is not too serious in general. The second part of the paper is devoted to the persistent economic underperformance of some regions in countries such as Germany, Italy and (with regard to regions overseas) France. How is it that the mechanism of yardstick competition induces a convergence of economic performance among European Union member countries, even those particularly poor initially, but fails to induce all the underperforming regions of these countries to catch up? A small model is used to explore that question. In the case of the persistently underperforming regions, it turns out that the degree of regional differentiation is not sufficient for yardstick competition to work and bring about an improvement in performance. The yardstick competition framework remains useful if it helps to understand more clearly why this is so.yardstick competition;political competition;regional development