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