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Towards Constraining the Physical Properties of High Redshift Galaxies

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Gadget-2 hydro sims with metal cooling: 8-64 Mpc/h volumes ... Star formation rate dist: Rest-UV LF. Stellar mass dist: Rest optical LF. ... – PowerPoint PPT presentation

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Title: Towards Constraining the Physical Properties of High Redshift Galaxies


1
Towards Constraining the Physical Properties of
High Redshift Galaxies
  • Romeel Davé
  • Kristian Finlator
  • Ben D. Oppenheimer
  • University of Arizona

2
What are the physical properties of
reionization-epoch galaxies?
  • Direct constraints from spectra Too faint.
  • Obtain from models that reproduce bulk
    properties Many parameters, few objects.
  • SED-fit photometry Many uncertainties.
  • Stellar populations
  • Extinction
  • Star formation history
  • Can we place constraints on galaxy formation
    models from photometry of individual galaxies?

3
Rest-UV Luminosity Fcn
  • Gadget-2 hydro sims with metal cooling 8-64
    Mpc/h volumes
  • UVLF seems to indicate some SF suppression
    required Outflows?
  • But constraints are weak Dust? Cosmology?
    (n0.95, s80.75)

4
Physical Properties Generic Predictions
  • SFR ? M Cold accretion.
  • Highly biased clustered Can reionize local
    infall region by z9.
  • Enriched to gt1/30 Z? M-Z slope in place ltlt1
    metal-free SF.
  • Can we test such predictions generically?

RD, Finlator, Oppenheimer 06
5
Photometry of Simulated Galaxies
  • Photometry from sims SFH (t,Z) ? BC03 w/Chabrier
    IMF.
  • Straightforward to find sim galaxies that
    reproduce Abell 2218 KESR photometry.
  • Turn this around What constraints on models from
    photometry?

RD, Finlator, Oppenheimer 06
6
Constraints from Photometry
  • Ability to match photometry is fairly generic
    Independent of outflow, cosmology.
  • Cant constrain total SF from this need UVLF.
  • BUT Matching photo-metry yields fairly robust
    physical properties!

Finlator, RD, Oppenheimer 06
7
SPOC Physical Properties from Observed Photometry
  • Use simulated galaxies SFH as a prior on SED
    fitting.
  • Obtain predicted probability distributions of
    AV, Z, Age, SFR, M, z.
  • Goal Test simulated SFHs.

Finlator, RD, Oppenheimer 06
8
Comparison with Traditional SED Fitting
  • Sims provide tighter constraints than simple
    assumed SFHs ? Non-trivial prediction!
  • Need spectra to test.
  • For now, can provide constraints from
    physically-motivated hierarchical galaxy
    formation model.

Finlator, RD, Oppenheimer 06
9
Simulated SFH Rising
  • Why are predicted properties robust?
  • Hydro simulations generically predict
    constantly-rising SFHs.
  • This is the basic prediction we can test with
    SPOC.

Finlator, RD, Oppenheimer 06
10
Simulations Work Mostly
  • Six zgt5.5 objects with IRAC data.
  • Good fits (?n2lt1) obtained for most objects.
  • Exceptions GLARE (bursting?), HCM6A (high
    Ha?).
  • Best-fit simulated galaxies are fairly massive,
    have older stars, always show a 4000Ã… break.

log M9.3
log M8.7
log M10.1
log M10.1
log M9.2
log M9.4
Finlator, RD, Oppenheimer 06
11
Summary
  • To understand high-z galaxy formation we need
  • Halo mass Clustering.
  • Star formation rate dist Rest-UV LF.
  • Stellar mass dist Rest optical LF.
  • Star formation history Photometry.
  • Generally, hydro simulations can reproduce
    current observations of both UVLF and SFH.
  • SPOC provides way to test simulated SFHs against
    individual galaxies with photometric data
    identifies deviating systems (bursts? AGN?).
  • Makes predictions that will be tested with JWST.
  • SPOC model libraries available upon request.

12
Bursty SFHs SFR-M
  • Tight SFR-M relation stringently tested.
  • Mostly, simulations pass test Can fit data,
    with tighter constraints than simple SFHs.
  • But for GLARE3001, high SFR/low M fits better
    Bursting?

Finlator, RD, Oppenheimer 06
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