1. Extremely Large Telescopes and Surveys Mark Dickinson, NOAO

2. 17 January 2008M. Dickinson - GSMT Workshop Surveys are a matter of definition… Surveys address problems needing: large statistical datasets many different coordinated data sets uniform data quality Surveys produce data sets that: are calibrated, distributed, documented data products can be used for many purposes are likely to be used by many people, beyond the original team Surveys often (not always) involve big teams Surveys usually require substantial resources: telescope time people $$$

3. 17 January 2008M. Dickinson - GSMT Workshop GOODS as an example Builds off precursor data sets Hubble Deep Field Chandra Deep Fields Keck & VLT spectroscopy for the above An “anthology” of multiwavelength survey programs from the GOODS team(s) & broader community HST, Spitzer, Chandra, Herschel, VLT, Keck, NOAO, VLA, JCMT, LMT… Most datasets easily & widely available to the community 300+ refereed publications w/ 10000+ citations Significant majority now from the broader community

4. 17 January 2008M. Dickinson - GSMT Workshop HST/ACS Chandra Spitzer 24  m GALEX

5. 17 January 2008M. Dickinson - GSMT Workshop VLT spectroscopy (ESO Large Program + several other campaigns) VLT near-IR imaging (ESO Large Program) 5200+ redshifts: 2200 @ z > 1 830 @ z > 2 335 @ z > 3 142 @ z > 4 50 @ z > 5 5 @ z > 6 1450 w/ i 775 > 24 420 w/ i 775 > 25

6. 17 January 2008M. Dickinson - GSMT Workshop ELTs and Surveys TMT/GMT will be used to follow up objects from surveys carried out with other facilities E.g., IFU dissection of objects identified by LSST, JWST, SPICA, ALMA, etc. TMT/GMT will be used to carry out their own surveys E.g., optical MOS tomographic survey of large scale structure in galaxies and the IGM

7. 17 January 2008M. Dickinson - GSMT Workshop GN26 Daddi et al. 2007 Daddi et al. 2008, Frayer et al. 2008 Steady, ultraluminous star formation at z ~ 2? Not well understood!

8. 17 January 2008M. Dickinson - GSMT Workshop Calzetti et al. 2005: SINGS (z~0) Genzel et al. 2006: SINFONI (z~2) ELTs + ALMA, SKA, JWST will dissect kinematics, ionized & molecular gas content & properties, dust emission & extinction, stellar populations, etc. on sub-kpc scales at z~2 TMT IFU on high-z galaxy (simulation)

9. 17 January 2008M. Dickinson - GSMT Workshop ELT science cases include large surveys E.g., mapping galaxies and the IGM in 3D at high redshift

10. 17 January 2008M. Dickinson - GSMT Workshop ALMA SKA LSST JDEMSPICAJWSTCon-X

11. 17 January 2008M. Dickinson - GSMT Workshop The context of other facilities TMT/GMT will exist in an era where: We have many powerful, multiwavelength observatories We have survey facilities producing huge volumes of data We have observers who are increasingly comfortable with multiwavelength science Multi-facility time allocation (see Letizia’s talk): NOAO multi-telescope programs are a modest but steady fraction of proposals NOAO time extensively supports space observing programs: 2000B-2005A: >1100 nights allocated that support or complement space-based observations Small minority allocated via joint NASA/NOAO programs Double jeopardy vs. higher hurdles for higher rewards?

12. 17 January 2008M. Dickinson - GSMT Workshop Surveys and time allocation Surveys require substantial investments of observing time, which may be precious for the national community This takes away from time available for smaller, “individual investigator” programs NOAO allocations for 6.5-10m telescopes strongly skewed toward small programs Large telescopes excluded from NOAO Survey Programs Few long-term or multicycle allocations Large, multi-season time allocations are more common with VLT and at US private observatories Surveys should give something back to the community: Broad opportunities for community participation in survey teams Funding for community data analysis & archival research

13. 17 January 2008M. Dickinson - GSMT Workshop

14. 17 January 2008M. Dickinson - GSMT Workshop Surveys, archives & pipelines Surveys require archives to distribute data products Archives can enable ‘virtual surveys’ of their holdings via data-mining Surveys may be facilitated by pipelines for data processing This need not require that the observatory provide them Instrument teams may provide algorithms, software Survey teams can contribute to pipeline development & testing