science team de muse
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
Toulouse – 18 mars 2009
Science Team Science Team de MUSEde MUSE
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Toulouse, 18 mars 2009
Update of science team organization and work packages tasks since last MUSE workshop
Lyon, november 2007
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MUSE Science Organization
Principal InvestigatorR. Bacon (Lyon)
Executive BoardT. Contini (Toulouse)S. Dreizler (Göttingen)B. Guiderdoni (Lyon)S. Lilly (Zurich)J. Schaye (Leiden)M. Steinmetz (Potsdam)
Instrument ScientistsL. Wisotzki (Potsdam) & T. Contini (Toulouse)
Science Team
Science TeamAssociates
Toulouse, 18 mars 2009
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Composition
Göttingen S. Dreizler (CoI), W. Kollatschny
LeidenJ. Brinchmann, M. Franx, J. Schaye (CoI)
LyonR. Bacon (PI), J. Blaizot, E. Emsellem, B. Guiderdoni (CoI), E. Slezak (OCA-Nice), H. Wozniak
PotsdamM. Roth, M. Steinmetz (CoI), P. Weilbacher, L. Wisotzki (IS)
ToulouseT. Contini (CoI, Deputy IS), R. Pello, G. Soucail
ZurichM. Carollo, S. Lilly (CoI)
Toulouse, 18 mars 2009
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Work packages
Science ActivitiesL. Wisotski & T. Contini
Preparatory Observations
M. Carollo
Simulations& Theory
E. Emsellem
DASTE. Slezak
DatabaseG. Soucail
Analysis ofsimulated datacubes
P. Weilbacher
OutreachR. Bacon
Lyon, 21 octobre 2008Toulouse, 18 mars 2009
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Toulouse, 18 mars 2009
Work packages
Science ActivitiesL. Wisotski & T. Contini
Preparatory Observations
M. Carollo
Simulations& Theory
E. Emsellem
DASTE. Slezak
DatabaseG. Soucail
Analysis ofsimulated datacubes
P. Weilbacher
OutreachR. Bacon
• 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
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Work packages
Science ActivitiesL. Wisotski & T. Contini
Preparatory Observations
M. Carollo
Simulations& Theory
E. Emsellem
DASTE. Slezak
DatabaseG. Soucail
Analysis ofsimulated datacubes
P. Weilbacher
OutreachR. Bacon
• 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
Lyon, 21 octobre 2008Toulouse, 18 mars 2009
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Work packages
Science ActivitiesL. Wisotski & T. Contini
Preparatory Observations
M. Carollo
Simulations& Theory
E. Emsellem
DASTE. Slezak
DatabaseG. Soucail
Analysis ofsimulated datacubes
P. Weilbacher
OutreachR. Bacon
• 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:
o Dense stellar fieldo Intermediate-z galaxieso Deep field o Lensing cluster o Galaxy nucleus + BH o Extended Ly emissoion
Lyon, 21 octobre 2008Toulouse, 18 mars 2009
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Work packages
Science ActivitiesL. Wisotski & T. Contini
Preparatory Observations
M. Carollo
Simulations& Theory
E. Emsellem
DASTE. Slezak
DatabaseG. Soucail
Analysis ofsimulated datacubes
P. Weilbacher
OutreachR. Bacon
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
Lyon, 21 octobre 2008Toulouse, 18 mars 2009
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Work packages
Science ActivitiesL. Wisotski & T. Contini
Preparatory Observations
M. Carollo
Simulations& Theory
E. Emsellem
DASTE. Slezak
DatabaseG. Soucail
Analysis ofsimulated datacubes
P. Weilbacher
OutreachR. Bacon
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
Lyon, 21 octobre 2008Toulouse, 18 mars 2009
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Work packages
Science ActivitiesL. Wisotski & T. Contini
Preparatory Observations
M. Carollo
Simulations& Theory
E. Emsellem
DASTE. Slezak
DatabaseG. Soucail
Analysis ofsimulated datacubes
P. Weilbacher
OutreachR. Bacon
• 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- data Data analysis tools & docs• As soon as GTO starts: Reduced datacubes Catalogs & derived/processed data Publications etc …
Definition of scientific requirementsPrototype for next summer
Lyon, 21 octobre 2008Toulouse, 18 mars 2009
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MUSE GTOdefinition process
Phase Timeline
1. Inputa) Brainstromingb) Detailed proposals
June 2008
2. Merging, priorities June 2009
3. Review January 2011
4. Finetuning 2011 2012
MUSE will operate in seeing-limited mode the first year of GTO
Lyon, 21 octobre 2008Toulouse, 18 mars 2009
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GTO guideline
• 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)
Lyon, 21 octobre 2008Toulouse, 18 mars 2009