OWLS: OverWhelmingly Large Simulations

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OWLS OverWhelmingly Large Simulations
The formation of galaxies and the evolution of
the intergalactic medium
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Outline

• Introduction to OWLS
• Radiative cooling
• Feedback from star formation
• Star formation histories
• Intragroup medium
• Gas accretion

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OWLS people
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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 z2
• L 100 Mpc/h to z0
• Runs repeated many times with varying
  physics/numerics

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Video of the evolution of a massive galaxy down
to z2
3 Mpc/h
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Zoom
CDV, OWLS project
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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.

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Radiative cooling (above 104 K)

• What is typically done
• H and He including optically thin
  photo-ionization
• Metal cooling ignored or assuming CIE and solar
  relative abundances

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Video of density dependence
Wiersma, JS Smith (2008)
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Radiative cooling above 104 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, arXiv0807.3748
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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

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1e12 M?, face-on, gas density
Dalla Vecchia JS (2008)
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1e12 M?, edge-on, gas density
Dalla Vecchia JS (2008)
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1e12 M?, edge-on, gas pressure
Dalla Vecchia JS (2008)
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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
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Lots of plots of SFR histories

• Most of these were flashed by

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Simulating galaxy statistics

• Cooling and feedback are crucial, SF law and
  structure of the ISM are not
• (Too) much freedom in implementation of galactic
  winds

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Groups at z0 Scaled entropy
McCarthy et al.
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Groups at z0 Scaled entropy
McCarthy et al.
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Groups at z0

• Massive galaxies reside in groups ? detailed
  information about gaseous environment from X-ray
  observations at z0
• 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

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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

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Hot and cold accretion
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Hot and cold accretion

• Did not get to these slides

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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

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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

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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!