1. Describing 3D Datasets Igor Chilingarian (CRAL Observatoire de Lyon/Sternberg Astronomical Institute of the Moscow State University) IVOA DM & DAL WG – VO France Spec WG – Euro3D

2. IVOA Interop, Kyoto, 2005 May 19 What is 3D spectroscopy? IFU Spectroscopy SCIENCE CASE 1: History of the stellar population in nearby galaxies Search for stellar population subcomponents and their connection with kinematical substructures by making analysis of spectra integrated along the line of sight (presentation by P. Prugniel in the Theory IG session) Usage of high-resolution synthetic spectra Precise description of the instrumental response (spectral resolution) of the spectrograph is essential: LSF(x,y, ) in case of 3D SCIENCE CASE 2: Stellar populations in AGNs Making 3D spatial-spectral decomposition of the active nucleus will allow to study stellar population and star formation in inner regions of active galaxies. In addition to the spectral resolution we need to know spatial PSF built by the telescope+spectrograph.

3. IVOA Interop, Kyoto, 2005 May 19 What is 3D spectroscopy? Scanning Fabry-Perot Interferometer Phase Surface Data Processing SCIENCE CASE 1: Studies of gas kinematics in disc galaxies From 2D velocity field it is possible to derive a rotation curve in the case of rotating disc galaxies by taking into account non-circular motions and perturbations caused by internal structures in the galaxies (spiral arms, bars) and then to study the distribution of dark and luminous matter. By comparing these results to the simulations one is able to understand the evolution of the galaxies’ dynamics in a given environment (credits: O. Garrido) SCIENCE CASE 2: Star-formation complexes and supernovae remnants in nearby galaxies: shells of ionized gas Studies of supernovae remnants and expanding shells around star- forming regions (stellar winds) in the nearby galaxies (e.g. dwarf irregulars) allows to study gas-removal mechanism and its rate, chemical composition variations and ISM distribution, that might shed light on the evolution of dwarf irregular galaxies. To study shell-like structures, one creates so-called position-velocity diagrams: planes slicing the IFP data cube (credits: T. Lozinskaya).

4. IVOA Interop, Kyoto, 2005 May 19 Storing 3D Data in FITS Key point: no information should be lost  one should avoid resampling Pure 3D data cube (for IFP data and for some IFU) Pure 3D data cube (for IFP data and for some IFU) 2D-image (one spectrum per row) + binary table  2D-image (one spectrum per row) + binary table  Euro3D Format FITS binary data table: one row per spectrum Binary table describing shape of spatial elements (“spaxels”) Some mandatory metadata, including: common spectral WCS for all spectra, common spatial WCS for all spatial elements, meteo parameters during the observations, etc.

5. IVOA Interop, Kyoto, 2005 May 19 What we propose Simple demo at the end of the year: VO access to two science-ready data archives: ESO (SINFONI) and SAO RAS (MPFS) VO access to two science-ready data archives: ESO (SINFONI) and SAO RAS (MPFS) Retrieving the data Retrieving the data Visualising them using Euro3D Visualisation Tool Visualising them using Euro3D Visualisation Tool What we need: DAL protocol: will SSA 1 be sufficient? DAL protocol: will SSA 1 be sufficient? Some modifications of the Euro3D Visualisation Tool Some modifications of the Euro3D Visualisation Tool Some “upgrade” of the Euro3D format (optional) Some “upgrade” of the Euro3D format (optional)

6. IVOA Interop, Kyoto, 2005 May 19 Describing 3D dataset Important 1. Atmosphere dispersion correction (if not made)  information about meteo conditions is required  characterisation is not sufficient: use observation DM 2. Spectral and spatial resolutions (LSF and PSF) depend both on spatial and spectral coordinates: LSF(x,y, ), PSF(x,y, ) 3. Principal question: How to characterise image slicing?