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Distant galaxies. Eelco van Kampen, Institute for Astrophysics, Innsbruck, and Institute for Astronomy, Edinburgh with Jim Dunlop, John Peacock, Will Percival, Miller Crawford, Susie Scott (Edinburgh), And Chris Rimes (Colorado). Semi-numerical galaxy formation. Ingredients:.
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Distant galaxies Eelco van Kampen, Institute for Astrophysics, Innsbruck, and Institute for Astronomy, Edinburgh with Jim Dunlop, John Peacock, Will Percival, Miller Crawford, Susie Scott (Edinburgh), And Chris Rimes (Colorado)
Semi-numerical galaxy formation Ingredients: • Cosmological model • Halo formation and merger history • Gas dynamics and radiative cooling • Star formation and feedback • Stellar population synthesis • Dust modelling CDM model of van Kampen, Rimes & Peacock (2004)
Model uniqueness Mostly quiescent star formation, z=3 Mostly bursting star formation, z=3 Bursting and quiescent star formation, z=3 z=0 z=0 z=0
SHADES Currently the largest (on-going) sub-mm survey (half a square degree) at 0.85 mm, complete to a flux limit of 8 mJy 240 useable shifts, which means 1/3 of the JCMT for 3 years (since Oct 2002) P.I. Jim Dunlop (Edinburgh)
SHADES: 0.5 sq. degrees, ~300 sources Will be finished before Herschel takes off, SCUBA-2 gets built, or the LMT starts taking data !
SHADES: done so far Lockman Hole Subaru Deep Field 133 sq. arcmin 82 sq. arcmin
Redshift information Combining SCUBA 850-micron data with BLAST data at 250, 350 and 500 micron ( + Spitzer + VLA ) Aretxaga et al. (2003)
Example star formation histories example 1 example 2 example 4 example 3
Simulating SHADES Mock SHADES map and redshift distribution
Predictions for SHADES: 4 models INAOEP Percival van Kampen Sussex
Predictions for SHADES: 4 models Fit to slope and amplitude for 25 mocks Redshift distribution for all 25 mocks (no redshift information used) van Kampen et al. (2004) angular clustering: w(θ) = (θ/A) -δ
Predictions for SHADES with redshifts Fit to slope and amplitude Fit to amplitude only (slope fixed to 0.8) van Kampen et al. (2004)
Clustering predictions for HSO Fit to slope and amplitude with no redshift information HSO: phenomenological SHADES (compare to the blue symbols in the right-hand panel)
Predictions for HSO with redshifts Fit to slope and amplitude HSO: phenomenological SHADES (compare to the blue symbols in the right-hand panel)
Predictions for HSO with redshifts Fit to amplitude only (slope fixed to 0.8) HSO: phenomenological SHADES (compare to the blue line in the right-hand panel)
Galaxy and halo merger trees An example of a simple halo/galaxy merger sequence
Can we resolve starburst haloes ? Large Sub-mm Dish (LSD): 2 arcsec resolution at 200 micron
Starburst halo size versus redshift SCUBA 850 micron resolution half-mass radius LSD 200 micron resolution
Final thoughts SHADES (with redshifts): first cut at models, constraints on the parameter space HSO + SCUBA-2 (+ … ): fine(r) cut at models, constraints on the actual parameters In order to beat cosmic variance, the survey does not need to be one large field, but can be many patches of a few degrees squared A 30m dish at 200 micron will resolve starburst haloes
Gas Dust Dust Dust SN Gas Star Formation IR UV IR IR UV IR UV H e- e- e- Radio e-
Sub-mm flux • The sub-mm flux mostly depends on the star formation rate, but also on: • the star formation and metallicity history • the temperature and geometry of the dust • the properties of the dust, including grain sizes We adopt 8mJy ~ 1000 Myr -1 (Scott et al. 2002, Fox et al. 2002), so , and the uncertainty in the dust physics is modelled by , with for 1. and 2.
SCUBA galaxies Elliptical at z=0 8 mJy Star formation history for a single galaxy
SCUBA galaxies Spiral galaxy at z=0 8 mJy Star formation history for a single galaxy
SCUBA galaxies 8 mJy Star formation history for a single galaxy