Sensitivity of the g-mode frequencies to pulsation codes and their parameters

From the recent work of the Evolution and Seismic Tools Activity (ESTA, Lebreton et al. 2006; Monteiro et al. 2008), whose Task 2 is devoted to compare pulsational frequencies computed using most of the pulsational codes available in the asteroseismic community, the dependence of the theoretical frequencies with non-physical choices is now quite well fixed. To ensure that the accuracy of the computed frequencies is of the same order of magnitude or better than the observational errors, some requirements in the equilibrium models and the numerical resolutions of the pulsational equations must be followed. In particular, we have verified the numerical accuracy obtained with the Saclay seismic model, which is used to study the solar g-mode region (60 to 140$\mu$Hz). We have compared the results coming from the Aarhus adiabatic pulsation code (ADIPLS), with the frequencies computed with the Granada Code (GraCo) taking into account several possible choices. We have concluded that the present equilibrium models and the use of the Richardson extrapolation ensure an accuracy of the order of $0.01 \mu Hz$ in the determination of the frequencies, which is quite enough for our purposes.Comment: 10 pages, 5 figures, accepted in Solar Physic

A test to detect association between autosomal and sex-linked loci in random mating populations: an example with Drosophila melanogaster

International audienc

Geospatial Big Data analytics to model the long-term sustainable transition of residential heating worldwide

Geospatial big data analytics has received much attention in recent years for the assessment of energy data. Globally, spatial datasets relevant to the energy field are growing rapidly every year. This research has analysed large gridded datasets of outdoor temperature, end-use energy demand, end-use energy density, population and Gros Domestic Product to end with usable inputs for energy models. These measures have been recognised as a means of informing infrastructure investment decisions with a view to reaching sustainable transition of the residential sector. However, existing assessments are currently limited by a lack of data clarifying the spatio-temporal variations within end-use energy demand. This paper presents a novel Geographical Information Systems (GIS)-based methodology that uses existing GIS data to spatially and temporally assess the global energy demands in the residential sector with an emphasis on space heating. Here, we have implemented an Unsupervised Machine Learning (UML)-based approach to assess large raster datasets of 165 countries, covering 99.6% of worldwide energy users. The UML approach defines lower and upper limits (thresholds) for each raster by applying GIS-based clustering techniques. This is done by binning global high-resolution maps into re-classified raster data according to the same characteristics defined by the thresholds to estimate intranational zones with a range of attributes. The spatial attributes arise from the spatial intersection of re-classified layers. In the new zones, the energy demand is estimated, so-called energy demand zones (EDZs), capturing complexity and heterogeneity of the residential sector. EDZs are then used in energy systems modelling to assess a sustainable scenario for the long-term transition of space heating technology and it is compared with a reference scenario. This long-term heating transition is spatially resolved in zones with a range of spatial characteristics to enhance the assessment of decarbonisation pathways for technology deployment in the residential sector so that global climate targets can be more realistic met

Recovering coherence from decoherence: a method of quantum state reconstruction

We present a feasible scheme for reconstructing the quantum state of a field prepared inside a lossy cavity. Quantum coherences are normally destroyed by dissipation, but we show that at zero temperature we are able to retrieve enough information about the initial state, making possible to recover its Wigner function as well as other quasiprobabilities. We provide a numerical simulation of a Schroedinger cat state reconstruction.Comment: 8 pages, in RevTeX, 4 figures, accepted for publication in Phys. Rev. A (november 1999