OWLS: OverWhelmingly Large Simulations

1. The formation of galaxies and the evolution of the intergalactic medium OWLS: OverWhelmingly Large Simulations

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

3. OWLS people Booth Dalla Vecchia Springel Theuns Tornatore Wiersma Bertone Crain Duffy Haas McCarthy Sales Van de Voort

4. 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

5. Video of the evolution of a massive galaxy down to z=2 3 Mpc/h

6. Zoom CDV, OWLS project

7. 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.

8. 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

9. Video of density dependence Wiersma, JS & Smith (2008)

10. 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

11. 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

12. 45 kpc/h 1e12 M, face-on, gas density Dalla Vecchia & JS (2008)

13. 45 kpc/h 1e12 M, edge-on, gas density Dalla Vecchia & JS (2008)

14. 45 kpc/h 1e12 M, edge-on, gas pressure Dalla Vecchia & JS (2008)

15. 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

16. Lots of plots of SFR histories • Most of these were flashed by…

17. 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

18. Groups at z=0: Scaled entropy 1 0.1 0.1 1 McCarthy et al.

19. Groups at z=0: Scaled entropy 1 0.1 0.1 1 McCarthy et al.

20. 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

21. 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

22. Hot and cold accretion

23. Hot and cold accretion • Did not get to these slides…

24. 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

25. 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

26. 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!