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Science Team de MUSE

Science Team de MUSE. Toulouse, 18 mars 2009. Update of science team organization and work packages tasks since last MUSE workshop Lyon, november 2007. Principal Investigator R. Bacon (Lyon). Instrument Scientists L. Wisotzki (Potsdam) & T. Contini (Toulouse). Science Team

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Science Team de MUSE

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  1. Science Team de MUSE Toulouse – 18 mars 2009

  2. Toulouse, 18 mars 2009 Update of science team organization and work packages tasks since last MUSE workshop Lyon, november 2007

  3. Principal Investigator R. Bacon (Lyon) Instrument Scientists L. Wisotzki (Potsdam) & T. Contini (Toulouse) Science Team Associates Executive Board T. Contini (Toulouse) S. Dreizler (Göttingen) B. Guiderdoni (Lyon) S. Lilly (Zurich) J. Schaye (Leiden) M. Steinmetz (Potsdam) Science Team MUSE Science Organization Toulouse, 18 mars 2009

  4. Composition Toulouse, 18 mars 2009 Göttingen S. Dreizler (CoI), W. Kollatschny Leiden J. Brinchmann, M. Franx, J. Schaye (CoI) Lyon R. Bacon (PI), J. Blaizot, E. Emsellem, B. Guiderdoni (CoI), E. Slezak (OCA-Nice), H. Wozniak Potsdam M. Roth, M. Steinmetz (CoI), P. Weilbacher, L. Wisotzki (IS) Toulouse T. Contini (CoI, Deputy IS), R. Pello, G. Soucail Zurich M. Carollo, S. Lilly (CoI)

  5. Science Activities L. Wisotski & T. Contini Preparatory Observations M. Carollo DAST E. Slezak Analysis of simulated datacubes P. Weilbacher Simulations & Theory E. Emsellem Database G. Soucail Outreach R. Bacon Work packages Lyon, 21 octobre 2008 Toulouse, 18 mars 2009

  6. Science Activities L. Wisotski & T. Contini Preparatory Observations M. Carollo DAST E. Slezak Analysis of simulated datacubes P. Weilbacher Simulations & Theory E. Emsellem Database G. Soucail Outreach R. Bacon Work packages Toulouse, 18 mars 2009 • Overall supervision of science activities • Follow instrument development • Keep science goals up to date • Develop credible & optimized • plan for GTO • Optimize survey strategy • Organize the scientific exploitation • of GTO data

  7. Science Activities L. Wisotski & T. Contini Preparatory Observations M. Carollo DAST E. Slezak Analysis of simulated datacubes P. Weilbacher Simulations & Theory E. Emsellem Database G. Soucail Outreach R. Bacon Work packages Lyon, 21 octobre 2008 Toulouse, 18 mars 2009 • Fields selection • Calibrations • Coordination w/ other facilities • (ALMA, JWST, etc) • Validation of DAST with • real data •  plan for preparatory • observations •  get observing time •  observe, reduce, analyse •  make data available to the project • through the science database

  8. Science Activities L. Wisotski & T. Contini Preparatory Observations M. Carollo DAST E. Slezak Analysis of simulated datacubes P. Weilbacher Simulations & Theory E. Emsellem Database G. Soucail Outreach R. Bacon Work packages Lyon, 21 octobre 2008 Toulouse, 18 mars 2009 • Develop new models/simulations • related to MUSE science cases • Produce relevant simulated datacubes • Needed for: •  MUSE performances (INM) •  inputs for DRS & DAST •  optimize survey strategies • Simulated astrophysical scenes: • Dense stellar field • Intermediate-z galaxies • Deep field • Lensing cluster • Galaxy nucleus + BH • Extended Lya emissoion

  9. Science Activities L. Wisotski & T. Contini Preparatory Observations M. Carollo DAST E. Slezak Analysis of simulated datacubes P. Weilbacher Simulations & Theory E. Emsellem Database G. Soucail Outreach R. Bacon Work packages Lyon, 21 octobre 2008 Toulouse, 18 mars 2009 • Make use of simulated datacubes • to test DRS & DAST •  Generate simulated raw data • using ATMOS and INM •  Run DRS, compare outputs with • ideal input datacubes •  Apply DAST and give feedback • First version of DRS & INM should • be available by spring 09 • -> A. Jarno talk

  10. Science Activities L. Wisotski & T. Contini Preparatory Observations M. Carollo DAST E. Slezak Analysis of simulated datacubes P. Weilbacher Simulations & Theory E. Emsellem Database G. Soucail Outreach R. Bacon Work packages Lyon, 21 octobre 2008 Toulouse, 18 mars 2009 • Develop Data Analysis Tools • specific to MUSE data • Optimal stacking & mosaicing • PSF characterization & deconvolution • Source separation & optimal extraction • in crowded fields • Blind detection of sources • etc …. • ANR Dahlia (2009-12, PI: E. Slezak) • Nice, Strasbourg, Toulouse, Lyon • -> E. Slezak talk

  11. Science Activities L. Wisotski & T. Contini Preparatory Observations M. Carollo DAST E. Slezak Analysis of simulated datacubes P. Weilbacher Simulations & Theory E. Emsellem Database G. Soucail Outreach R. Bacon Work packages Lyon, 21 octobre 2008 Toulouse, 18 mars 2009 • Creation & maintenance of an • interactive science database • Minimal content should include: •  Preparatory observational data •  Mock data •  Catalogues of GTO fields/targets • w/ link to multi-l data •  Data analysis tools & docs • As soon as GTO starts: • Reduced datacubes • Catalogs & derived/processed data • Publications • etc … Definition of scientific requirements Prototype for next summer

  12. MUSE GTOdefinition process Lyon, 21 octobre 2008 Toulouse, 18 mars 2009 MUSE will operate in seeing-limited mode the first year of GTO

  13. GTO guideline Lyon, 21 octobre 2008 Toulouse, 18 mars 2009 • GTO = 250 nights – maximum 20 per semester • Used in a collaborative effort on a limited number of projects • Does not exclude dedicated projects using a small fraction of GTO • Inputs phase on-going • Merging/priorities at next ST meeting (Lyon, 4-5 June)

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