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The formation of galaxies and the evolution of the intergalactic medium OWLS: OverWhelmingly Large Simulations Outline Introduction to OWLS Radiative cooling Feedback from star formation Star formation histories Intragroup medium Gas accretion OWLS people Booth Dalla Vecchia Springel

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Presentation Transcript
outline
Outline
  • Introduction to OWLS
  • Radiative cooling
  • Feedback from star formation
  • Star formation histories
  • Intragroup medium
  • Gas accretion
owls people
OWLS people

Booth

Dalla Vecchia

Springel

Theuns

Tornatore

Wiersma

Bertone

Crain

Duffy

Haas

McCarthy

Sales

Van de Voort

owls features
OWLS features
  • LOFAR IBM Bluegene/L
  • Cosmological (WMAP3), hydro (SPH)
  • Modified Gadget III
  • 2xN3 particles, N = 512 for most
  • Two sets:
    • L = 25 Mpc/h to z=2
    • L = 100 Mpc/h to z=0
  • Runs repeated many times with varying physics/numerics
slide6
Zoom

CDV, OWLS project

owls new gastrophysics modules
OWLS: New gastrophysics modules
  • Star formation JS & Dalla Vecchia (2008)
  • Galactic winds Dalla Vecchia & JS (2008)
  • Radiative cooling Wiersma, JS, & Smith (2008)
  • Chemodynamics Wiersma et al.
  • AGN feedback Booth et al.
radiative cooling above 10 4 k
Radiative cooling (above 10^4 K)

What is typically done:

  • H and He including optically thin photo-ionization
  • Metal cooling ignored or assuming CIE and solar relative abundances
video of density dependence
Video of density dependence

Wiersma, JS & Smith (2008)

radiative cooling above 10 4 k10
Radiative cooling above 10^4 K
  • Photo-ionization suppresses metal cooling  cooling rates decrease by up to an order of magnitude
  • Relative abundance variations are important  cooling rates change by factors of a few
  • Tables of cooling rates, element-by-element, including photo-ionization available

Wiersma, Schaye & Smith, arXiv:0807.3748

galactic winds
Galactic winds
  • Thermal feedback is quickly radiated away due to lack of resolution
  • Solutions:
    • Kinetic feedback
    • Temporarily suppress cooling
  • Most cosmological simulations employ the SPH code Gadget, which uses kinetic feedback
  • Our kinetic feedback differs from that of Gadget:
    • Not hydrodynamically decoupled
    • Winds are local to the SF event
galactic winds15
Galactic winds
  • Hydro drag determines outcome,

gravity only indirectly important

  • Low mass galaxies:

wind drags lots of gas out to the IGM

  • High mass galaxies: drag quenches wind  fountain
  • Most popular existing prescription overestimates the energy in the outflow by orders of magnitude
  • The details of wind implementations have grave consequences

Dalla Vecchia & Schaye, 2008, MNRAS, 387, 1431

lots of plots of sfr histories
Lots of plots of SFR histories
  • Most of these were flashed by…
simulating galaxy statistics
Simulating galaxy statistics

 use other constraints, e.g.:

  • Metal distribution
  • Gas profiles

  • Cooling and feedback are crucial, SF law and structure of the ISM are not
  • (Too) much freedom in implementation of galactic winds
groups at z 0 scaled entropy
Groups at z=0: Scaled entropy

1

0.1

0.1

1

McCarthy et al.

groups at z 0 scaled entropy19
Groups at z=0: Scaled entropy

1

0.1

0.1

1

McCarthy et al.

groups at z 0
Groups at z=0
  • Massive galaxies reside in groups  detailed information about gaseous environment from X-ray observations at z=0
  • Highly sensitive to (metal) cooling and feedback
  • Simulations can match detailed entropy, temperature, density and abundance profiles surprisingly well
  • But it is a challenge to reproduce both the optical and X-ray properties of groups
how do galaxies get their gas
How do galaxies get their gas?
  • Classical picture: Gas-shock heated to the virial temperature, then cools onto disk
  • Recent modifications:
    • Much of the gas falls in cold through filaments, particularly in low-mass galaxies
    • Efficient AGN feedback requires a hot halo
    • Galaxy bi-modality may be caused by transition from cold to hot accretion
hot and cold accretion23
Hot and cold accretion
  • Did not get to these slides…
gas accretion conclusions
Gas accretion - Conclusions
  • Cold accretion fraction sensitive to definition
  • Halo accretion:
    • Independent of subgrid physics
    • Hot fraction increases with mass and with decreasing redshift
    • Smooth transition from cold to hot
  • Disk accretion:
    • Sensitive to subgrid physics
    • Cold accretion dominates at all masses unless it is stopped by feedback
conclusions 1 2
Conclusions – 1/2
  • Some predictions from hydro simulations suffer from subgrid uncertainties (e.g. SSFRs, LFs), others are robust (e.g. accretion onto halos)
  • Even when predictions are uncertain, hydro simulations can pinpoint the important physical processes, e.g.
    • Star formation laws are helpful but not constraining
    • Cooling can and must be done better
    • Freedom in feedback implementations is currently the bottleneck  need higher resolution and a better treatment of metal mixing
  • “Realistic” simulations of the formation of
    • Individual high-z dwarfs are within reach
    • Massive galaxies are still far beyond the horizon
  • Comparisons with galaxy surveys are too challenging and not always the most productive strategy
conclusions 2 2
Conclusions – 2/2
  • Progress is most likely to come from studies of gas properties:
    • intergalactic, intra-group and intra-cluster media Available: hard X-ray profiles
      • Needed: soft X-ray and UV at high (spectral) resolution
    • HI and CO structure of individual galaxies
    • QSO/GRB absorption spectra
  • DANGERS (rant):
    • Many groups use (nearly) the same subgrid recipes
    • Insufficient awareness of models ingredients
    • Much more discussion about numerical accuracy (e.g. resolution and SPH vs grid) than subgrid uncertainties
    • Pressure to reproduce observations
  • Subgrid variations are at least as important as convergence tests!