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The GHOST in CU8

The GHOST in CU8. Coralie Neiner Paris-Meudon Observatory Coralie.Neiner@obspm.fr GHOST website: http://www.ster.kuleuven.be/~coralie/gaiahot.html. GAIA lexicon….

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The GHOST in CU8

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  1. The GHOST in CU8 Coralie Neiner Paris-Meudon Observatory Coralie.Neiner@obspm.fr GHOST website: http://www.ster.kuleuven.be/~coralie/gaiahot.html

  2. GAIA lexicon… CU = Coordination Unit For CU8: manager=CBJ, deputy=Frederic Thevenin, scientific coordinator=CBJ, technical coordinator=Michel Nonon DU = Development Unit = a group of people contributing to a CU or a sub-part of a CU (with a DU coordinator) GHOST = Gaia Hot Stars Team = a DU (G)WP = (Gaia) Work Package = a group of tasks to be performed in a CU (with a WP manager and sub-WP managers) SSU = Specific Stars Unit

  3. The CUs of GAIA • CU1: System architecture (O’Mullan) • CU2: Data simulations (Luri) • CU3: Core processing (Bastian) • CU4: Object processing (Pourbaix, Tanga) • CU5: Photometric processing (van Leeuwen) • CU6: Spectroscopic processing (Katz) D. Katz this morning • CU7: Variability processing (Eyer)  C. Aerts this morning • CU8: Astrophysical parameters (Bailer-Jones)  now! • (CU9: Catalogue access)

  4. CU8 Astrophysical parameters Work Beakdown Structure • Top level WPs: • Common packages GWP-C-81xx • Support packages GWP-S-82xx • Algorithmic units GWP-S-83xx (all objects) GWP-S-84xx (SSU)

  5. Common WPs: GWP-C-8110 Coordination and management GWP-C-8120 Definition of system architecture GWP-C-8130 Simulations GWP-C-8140 Configuration management GWP-C-8150 Hardware/System administration

  6. Support WPs: • GWP-S-8210 Stellar models/spectra (Korn/Thevenin) • Provide synthetic spectra for single stars across the full AP space expected, at sufficient wavelength resolution and coverage to ensure accurate simulation in BBP, MBP and RVS. GHOST contribution: models for hot stars and emission line stars (contributors: Y.Frémat, R. Blomme, C. Martayan, J. Zorec, J.-C. Bouret, F. Martins,…)  Y. Frémat this afternoon

  7. GWP-S-8220 Calibrations and auxiliary data (Soubiran) • Provide the real data and parameters required to calibrate the classification and AP estimation methods. Perform new observations if necessary. GHOST contribution: • provide a list of object types than need new observations (contributors: the whole GHOST) • provide a list of typical targets for this object types (contributors: the whole GHOST) • help with the observations (contributors: I. Kolka with the Tartu Observatory, A.-M. Hubert, M. Floquet, C. Neiner with the Pic du Midi/TBL,…)

  8. GWP-S-8230 Interstellar extinction (Straizys) • Establish an optimal method for determining the line-of-sight interstellar extinction to individual stars, based on BBP, MBP and RVS. GHOST contribution: make sure the interstellar extinction is treated properly in emission line stars…

  9. Algorithmic units: • GWP-S-8310 Discrete Source Classifier (DSC) (Bailer-Jones) • Use photometry of unresolved ‘slow’ sources to determine the broad class of the object (single star, binary, QSO, …) GHOST contribution: provide typical criteria for hot stars and emission line stars?

  10. GWP-S-8320 Generalized Stellar Parametrizer – Photometry (GSP-phot) (Bailer-Jones) • Estimate APs for the full range of type of single stars based on photometry (and parallaxes in late-mission) GHOST contribution: provide typical photometric criteria for hot stars and emission line stars?

  11. GWP-S-8330 Initial Spectral Analyser (ISA) (Manteiga) • For single stars, from RVS spectra, find evidence for binarity, search for emission lines, estimate Av from the DIB GHOST contribution: provide typical spectral criteria for hot stars and emission line stars?

  12. GWP-S-8340 Generalized Stellar Parametrizer – Spectroscopy (GSP-spec) (Recio-Blanco) • Estimate APs for the full range of type of single stars based on RVS and GSP-Phot GHOST contribution: provide spectral criteria for hot stars and emission line stars?

  13. GWP-S-8350 Object Clustering Analysis (OCA) (Sarro) • Identify natural or intrinsic classes of objects (unsupervised classification) GHOST contribution: provide algorithms for unsupervised classification for hot stars and emission line stars?  Would the algorithm developed in Leuven be useful here?

  14. GWP-S-8360 Luminosity, Age and Mass Estimator (LAME) (Lebreton) • Estimate the luminosity, age and mass of single stars based on their APs, parallax and apparent G-band magnitude GHOST contribution: help to determine the G-band magnitude and luminosity, which are crucial for the age and mass determination, for hot stars and emission line stars

  15. GWP-S-8410 SSU: QSOs (Claeskens) GWP-S-8420 SSU: Unresolved galaxies (Kontizas) GWP-S-8430 SSU: Solar system objects (Lagerkvist) GWP-S-8440 SSU: Non-single stars (?) GWP-S-8450 Extended stellar parametrizer (Frémat) 51 SSU: Hot stars (Neiner) 52 SSU: Cool stars (Lanzafame) 53 SSU: Ultra cool dwarfs (Barrado) 54 SSU: Abundance anomalous stars (Straizys) 55 SSU: Emission line stars (Neiner) GWP-S-8460 Outlier analysis (Manteiga) Study, develop and test algorithmswhich provideextended parameter estimates for the considered stars.

  16. GWP-S-8451 (hot stars)& GWP-S-8455 (emission line stars) •  Study, develop and test algorithmswhich provideextended parameter estimates • GHOST contribution:everything in these 2 WPs! • Tasks: • Develop, implement and test classification algorithms • Obtain synthetic data to operate and test algorithms • Obtain auxiliary data (via GWP-S-8210!) • Analyse test data and GAIA data • Participate in final catalogue

  17. Deliverables: • Project plan (March 2006) • Reports onperformance of various algorithms (2006- 2008) • Final version of algorithms (2010) • Documentation (2010) • Improved version from real GAIA data (2012-2016) • Progress reports

  18. What needs to be done (before launch in 2011) • Observations: • To converge on a list of objects types for which we need new observations, via the GHOST mailing list and website  in the coming months • To converge on a list of targets for these object types, via the GHOST mailing list and website  in the coming months • To organize, obtain and reduce observations, in collaboration with GWP-S-8210, in particular in Tartu and in France (and with belgian telecopes?)  for the semesters 2007A and 2007B

  19. Models: • Develop RVS synthetic spectra for OB stars (Frémat et al.)  2006-2007 • Develop RVS synthetic spectra with emission (Zorec et al.)  2006-2008 • Develop photometric models for OB stars with and without emission (Frémat et al.)  2006-2008

  20. Criteria: • Find suitable criteria to classify hot stars from RVS spectra (Fremat et al.)  2006 • Find suitable criteria to classify emission line stars from RVS spectra (Martayan et al.)  2006 • Find suitable criteria to classify hot stars from GAIA photometry (Fabregat et al.?)  2006-2007 • Find suitable criteria to classify emission line stars from GAIA photometry (Kolka et al.)  2006-2007

  21. Criteria in practice: • The ‘hot stars’ and ‘emission lines stars’ include: • O stars - Wolf-Rayet • B stars - Luminous Blue Variable (LBV) • Be stars - β Cep stars • B[e] stars - Slowly Pulsating B (SPB) stars • shell Be stars - T Tauri • Herbig Ae/Be stars - … • 2 millions hot stars in photometry + 400 000 RVS spectra! • 400 000 emission line stars + 80 000 RVS spectra!

  22. Algorithms: • Study, develop and test algorithms to classify hot stars and provide stellar parameters (Frémat et al.) 2006-2010 • Study, develop and test algorithms to classify emission line stars and provide stellar parameters (Martayan et al.)  2006-2010 - Help with study, development and test of algorithms to provide luminosity, mass and age estimates (GWP-S-8360) (Frémat et al.?)  2006-2010 • Help with study, development and test of algorithms for interstellar extinction (GWP-S-8230) (Who?)  2006-2010 •  Final versions in Java, with documentation

  23. Algorithms in practice: • We can study and test algorithms in any language • We then select the best algorithm for a certain task (efficiency is an important issue!) • We write it in Java, with the help of the data center (CNES) if needed • We test it thoroughly • We provide it to the data center at the latest in 2010 for integration in the GAIA algorithm

  24. Where/How can the belgian members of the GHOST contribute: • Y. Frémat in Brussels is already involved in many tasks. Needs help!? • Expertise of members from Liege for WR stars would be welcome (for example) • Will the members from Leuven concentrate on CU7? • Contributions to observations? •  Discussion open!...

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