1. RVS First Look ( WP6200) J.-M. Désert, G. Hébrard, A. Lecavelier, R. Ferlet, A. Vidal-Madjar Institut d’astrophysique de Paris (IAP) Workshop RVS Calibration IAP-November 24 th, 2005

2. Plan 1.GAIA First Look 2.Overall RVS First Look 3.Details of each RVS First Look steps

3. Calibration: pixel level Structure of the coordination unit “C6 Spectroscopic reduction” in the framework of the Gaia Data Processing Consortium. (Katz et al. « SPE-CU-001 »)

4. GAIA First Look Problematic Problems: -Fast monitoring of the GAIA spacecraft -Check the raw telemetry dataflow as soon as it is downloaded -An instantaneous first quick calibration is required -Self calibrating instrument. However, GIS possible only after 6 months. -First analyses of data quality and consistency is required in a daily basis Solution: First Look, else risk of losing many months of data and mission time. Method: Monitoring of the satellite health and the data quality Remark for RVS: Advantage: numerous a priori calibration objects exist in the sky

5. What? –Instrumental follow up –Data sanity check –Quick calibration/analyses GAIA First Look Why? –Quick reaction to a problem on the satellite/data chain –Technical diagnostics and alerts –Data diagnostics and alerts Who? –Ground Segment (GS) –Data Processing Center (DPC) Data Analysis Consortium (=> Coordination Unit DU1000) How? –Different level of processing at different time executed under different responsabilities –Ground Algorithms applied on onboard processed data (RAW) –Close relations between the 3 instruments

6. Time: –Real time –Within ~24 hours Diagnostics: –Technical data: instruments (and bus?) control –Scientific data: sanity check and first spectral calibration Responsability: –Who makes diagnostics –Who reacts GAIA First Look Different FL tasks

7. Overall RVS First Look Quick LookScience Quick LookDetailed First Look Initial Data Treatment Input Pipeline Raw Telemetry Satellite Diagnostics: InstrumentdataScientific data Responsability: GSDPC Time: Real time~24h Further data reduction Input Pipeline Input: telemetry stream from Gaia. Output: image-type data

8. Input Pipeline Gaia-RVS Ground Processing (RVS-MSC-004) M. Cropper, D.Katz First On Ground processing steps Stripping of telemetry packaging Data reformatting Adding time information Adding spacecraft coarse attitude Adding instrument parameters and housekeeping data Automated Quick Look analysis Adding starmapper data Retrieval of relevant astrometric data from Astro database Ingestion into image products database (IPD) Science Quick Look

9. Overall RVS First Look Quick LookScience Quick LookDetailed First Look Initial Data Treatment Input Pipeline Raw Telemetry Satellite Diagnostics: InstrumentdataScientific data Responsability: GSDPC Time: Real time~24h Further data reduction IDT First part of the scientic data reduction chain performed Data ingestion Cross Matching Generation of elementary data QL All GS activities concerning satellite health (i.e. bus and instrument). Uses telemetry stream from GAIA (housekeeping (HK), attitude control system (ACS) data, etc…) ScQL All activities concerning scientific data health. Simple and not precise to safe observation time. Generates telecommanding or alerts the scientific. DFL In-depth scientific assessment of the quality of the Gaia observations About 24 hours after telemetry reception at the DPC. Produce diagnostics of the status of the satellite and instrument in a more sophisticated manner than can be performed within QL and ScQL.

10. QL, ScQL & DFL in more details…

11. QL: Telescope and Instrument follow up 1. Basic telescope informations –Effective area –Optic path –Telescope reflective index 2. Instrument monitoring Control of the instrumental stability: –Thermal –Mechanical –Optical –Global efficiency –PSF / Filter PSF –Wavelength contamination (Blue / Red) RVS => 100-150 10 6 sources at ~93 epoch. Subset of sources which will be bright and stable (astrometrically, photometrically and spectros). These sources will be monitored daily all along the mission. Use to self-calibrate the RVS  Trace the evolution of the characteristics of the instrument.

12. ScQL : data sanity check Analyses of the onboard processing outflow parameters Long and short term effects –Compare with outflow parameters of the previous day –Compare with outflow parameters of the previous month Check the quality of some scientific parameters on a subset of stars –Tests on ribbon of data (bias, bkckgd,etc …) –Xmatch –Quick calibration ->

13. ScQL : From Ribbons to spectra Radial velocity (V < 16-17): –principles: slitless spectroscopy using Ca triplet (848-874 nm) –applications: third component of space motion, perspective acceleration dynamics, population studies, binaries spectra: chemistry, rotation Examples of single transit RVS-like spectra of an F5V star for the apparent magnitudes: V=8, V=10, V=12 and V=14. GEPI/GAIA-RVS/TN/017.01, F. Crifo, D. Katz Calibrate detector image Quick spectral extraction Extract standard star spectrum ~ 2000°2/day ~ 1/20 of ~2000 Standard Stars Background Sky background + Zodiacal Background flux + Diffused light + Instrumental noise (Readout…) ) Crowding, star densities and faint stars Wavelength and flux calibrations => Quick Diagnostics (Rv)

14. QL & ScQL : Raw telemetry Product types The On-board Processing processing tasks in sequence are as follows: 1. CCD gain correction 2. Blemish reduction (Fabrication or radiation) 3. Scan law and Across Scan optical distortion correction 4. Along Scan optical distortion correction 5. Cosmic ray removal 6. Co-adding (Pixels? / Over 10 CCDs??) 7. Output data selection (Selected pixel on the detector using starmapper) 8. Lossless compression (Cropper et al. « RVS: Technical issues »)  QL & ScQL need to analyse the result of these steps

15. DFL : higher level of diagnostics and calibrations All the target or Subsets ( V limit ) Extract physical parameters –Extract R V (~1 km/s) –Stellar + interstellar parameters –Early science processing steps - Core processing Use all scientific data to assess data and instrument health –Quick Extraction of all physical parameters on all data (?) –Combine spectra from several scans. –Various levels of combined spectra, and derived parameters may exist, depending on the stage of the mission. Feed back with science alerts and object processing

16. Detailed First Look Initial Data Treatment Input Pipeline Raw Telemetry Satellite Calibration Pipeline (SGIS) Single transit pipeline Multiple transit pipeline  FL needed for the SGIS Especially at the beginning of the telescope lifetime and in between two nominal calibrations ? DFL : higher level of diagnostics and calibrations Gaia-RVS Ground Processing (RVS-MSC-004) M. Cropper, D.Katz A. Guerrier

17. Need to do Quantify: what? why? who? how? - Define which questions should be answered by the RVS-FL - Explicit relations with other instrument FL? (Heidelberg 2 Dec 2005) Define RVS FL in the GAIA FL framework? I/O flux in between FL of the 3 Instruments: -Astrometry => Attitude -Sky Mapper => Xmatch With Photometry and RVS - Define and quantify QL, ScQL and DFL I/O flux, routines and diagnostic parameters. - Quantify real time and subsets? Subsets for QL, SCQL and DFL? - Give a list of a priori calibrator - Auxilliary data? (same as the pipelines?) - Clarify who is in charge of the dvpt of QL, ScQL and DFL?

18. To be continued…