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Surveying the Galaxy: classical methods applied to topical science and the role of the ING

Surveying the Galaxy: classical methods applied to topical science and the role of the ING. Gerry Gilmore Institute of Astronomy Cambridge University. Our requirement is really very simple. Stellar populations: 4.5 `types’. What stars we have available to study.

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Surveying the Galaxy: classical methods applied to topical science and the role of the ING

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  1. Surveying the Galaxy:classical methods applied to topical scienceand the role of the ING Gerry Gilmore Institute of Astronomy Cambridge University

  2. Our requirement is really very simple

  3. Stellar populations: 4.5 `types’ What stars we have available to study • Kinematically cold, high-J (angular momentum), wide age-range, narrow abundance range - dG-`problem’  late gas accretion? -- thin disk POP I • Probably discrete? intermediate PopII, thick disk I.5 • Hot, low-J, old?, metal-rich, related to SMBH – bulge • Hot, low-J(???), old(??) metal-poor(?), late accretion(?), perhaps itself 2-component – halo classical POPII • The first early stars POPIII? +POPIV +.... • PLUS, most important of all?: • All these in an evolving dark-matter potential: POP 0? • Justification is observed relation to physics

  4. Complexity, richness • All these “populations” means complexity, •  large samples •  no single “answer” •  no single approach is sufficient •  many types of survey are needed: • Imaging, kinematic, spectroscopic (various R), • and Gaia. • R~5000 most science, most critical, cf other talks

  5. A simple example of the power of large samples, with understood biasses Stellar orbit-abundance correlation: yellow band is ELS relation

  6. Wyse, Gilmore, Norris 2008: Thick disk is OLD Power of huge samples, low dispersion Young stars would be here   Old stars here  [Fe/H]   12Gyr turn-off points (g-r)o 8,600 faint F/G dwarfs, several kpc above the plane, spectroscopic metallicities from AAOmega/AAT data

  7. The OUTER halo is only 10% of the halo, perhaps 1% of the stellar Galaxy MOST of the halo POPII is old, and has very clearly defined chemical element ratios Not at all like the surviving dSph Local volume-complete sample Chemical evolution models allow x100 element ratio scatter – not seen The scatter is 2-3 orders less than the range. This implies efficient large-scale mixing, or uniform sub-units Element ratio data from Fuhrmann, see also Nissen.

  8. Current data show the power of chemistry to measure `history’, fig from Renzini Renzini 2008 Standard IMF (#1) Well-mixed (#2) Fast recycling (#3)

  9. Carretta etal 2009 A&A 505 117 There are very many complications, which need lots of data to “understand” – eg, why do giants show different element patterns/ratios in star clusters than in the field?? Yet again, this is suggesting our survivor structures are not the important building blocks. Why not??

  10. Plateau  universal IMF Plateau  efficient mixing Sharp break  narrow time Small scatter  good mixing ... .... ... Lots and lots of physics Blue=outer halo Red = inner halo How much of that scatter is real?? How were those stars selected for analysis?

  11. Majority of data sets suggest remarkably small scatter in low-abundance stars BUT: one recent survey provides a quite different result – two low-scatter relations And much increased richness/complexity for [m/h]-1 Our current samples are small, and very biased: there is obviously vastly more to learn before we are sure we are even asking the right questions. Nissen & Schuster 2010 : 1002.4514

  12. The thick disk/halo state of the art: many more metal-poor stars at bright magnitudes, high angular momentum extends to low metallicity (pace ELS). But standard IMF (#1) Well-mixed (#2) Fast recycling (#3) Ruchti, Fulbright, Wyse, GG, in prep, based on RAVE survey

  13. What role does ING have to play in these big challenges? • Very many exciting science cases are presented here. Very interesting, but • “all of the above” and “people want us” is not an intelligent reaction. • One needs to look at sharing, coordinating, off-loading • SDSS and RAVE are an excellent example of a practical way forward: • Focussed use of a cheap facility (UKST) to do a very few things very well, • while focussing on big science questions. • The Gaia-related follow-up projects are a superb example of optimal • science use of a wide-field 4m telescope, with data serving a huge range of • science and a huge science community. • Coordination inside the GREAT initiative (coordinated by Nic Walton and • the GAIA project DPAC community) is an obvious way forward. • Scale of people, scale of science, focus of technical demands. • And this is highly likely to be a non-negotiable requirement for • continuing financial support

  14. What role does ING have to play in these big challenges? • Very many exciting science cases are presented here. • Attempting all (or even many) of them is foolish, and will fail • We are an age of big statistics • We have many small telescopes: all of them doing everything is stupid • 2-4m telescopes are like clever students: • doing a very small number of things well is a smart future • Coordinated major Gaia-related science is smart, to be somewhere. • There is a wide-field spectroscopic AstroNet review panel underway • Likely outcome: share the 3 top priorities around the best facilities, • Each doing 1-2 things only, and optimally • Make a clear choice, then commit to do it well.

  15. dSphs vs. halo abundances Shetrone et al. (2001, 2003): 5 dSphs Frebel et al. (in prep.): Sculptor Shetrone et al. (2008): Leo II Sadakane et al. (2004): Ursa Minor Frebel et al. (2009): Coma Ber, Ursa Major Monaco et al. (2005): Sagittarius Aoki et al. (2009): Sextans Koch et al. (2007, 2008, 2009): Carina Tolstoy et al. (2009): Sculptor Letarte (2007): Fornax Cohen & Huang (2009): Draco Koch et al. (2008): Hercules Feltzing et al. (2009): Boo I

  16. Looking again near the Sun: the RAVE survey –UKST – 1million bright stars, to see what is really there. Kinematic `populations’ and chemistry follow-up

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