1. The document discusses semi-analytic modeling of galaxy formation using the GALFORM model. 2. It describes how the model tracks processes like gas cooling, star formation, feedback, black hole growth, and galaxy mergers. 3. The model is used to make predictions about far-IR galaxy populations, submillimeter galaxies, dust emission, and number counts that can be compared to observations.

1. Semi-analytic Modeling: Creation of the Far-IR Populations Andrew Benson, Caltech

3. GALFORM Model GALFORM Model Gravitational collapse Dark matter and gas distributions Gas cooling rates Star formation, feedback Dynamical friction Luminosities, colors Positions and velocities Star formtn. rate, ages, composition Structure & Dynamics Morphology State of the Art: Semi-analytic Models Collaborators Carlos Frenk, Shaun Cole, Cedric Lacey, Carlton Baugh, Richard Bower, John Helly, Rowena Malbon, Cesario Almeida ( ICC, Durham, U.K. ) Martin Stringer ( Oxford University, UK/Caltech ) Creation of the Far-IR Populations SPICA Workshop, November 2006

4. How Do We Model Galaxy Formation? Cole et al. 2000 Combination of simulations, analytic results and recipes with parameters Creation of the Far-IR Populations SPICA Workshop, November 2006

6. Fundamental Plane of Ellipticals Cesario Almeida et al. 2006 Comparison of predicted sizes of local bulge dominated galaxies with SDSS analysis by Bernardi et al. 2005 Creation of the Far-IR Populations SPICA Workshop, November 2006

7. Physical Model: Star Formation Gravitational collapse Dark matter and gas distributions Gas cooling rates Star formation, feedback Dynamical friction GALFORM Model GALFORM Model Supernovae energetics/dynamics Molecular cloud collisions Pressure-induced star formation Galactic fountain Multi-phase interstellar medium Creation of the Far-IR Populations SPICA Workshop, November 2006

8. Need for “Complicated” Models? Mass to light ratio Total group luminosity Variation of M/L with total group luminosity shows how the efficiency of galaxy formation should depend on halo mass. Galaxy formation most efficient Effectiveness of feedback processes and variation in gas cooling time within haloes of different mass drive change in M/L Eke et al. 2004, 2005 Creation of the Far-IR Populations SPICA Workshop, November 2006

9. The Challenge of (sub-)mm Galaxies Creation of the Far-IR Populations SPICA Workshop, November 2006

10. The Challenge of (sub-)mm Galaxies SCUBA image of HDF More star formation at high-z? Creation of the Far-IR Populations SPICA Workshop, November 2006

11. The Challenge of (sub-)mm Galaxies *Population of sources missed by Lyman-break dropout & UV imaging *Possibly more star formation at high redshift than previously thought *Inferred SFRs huge ~ 1000 Msun/yr! *Is all emission due to starburst or is some from an AGN? *Is a SCUBA source an elliptical galaxy in formation? *Massive galaxies in place at high-z? How can SCUBA sources be accommodated in hierarchical models? Creation of the Far-IR Populations SPICA Workshop, November 2006

12. Modeling Dust Extinction & Emission *Naïve model: assume dust temperature *Physically inconsistent! *Dust temperature should be determined by thermal equilibrium between heating and cooling of grains *With the bolometric luminosity and dust mass as parameters, and with the dust in thermal equilibrium, Which gives : Creation of the Far-IR Populations SPICA Workshop, November 2006

19. Examples of Predicted SF Rates Star formation rate GREEN: total RED: Starbursts BLUE: Quiescent Disks Creation of the Far-IR Populations SPICA Workshop, November 2006

20. Example SEDs from CDM Model Quiescent spiral Ongoing burst dust stars Creation of the Far-IR Populations SPICA Workshop, November 2006

23. Standard High-z Predictions 850 micron counts Lyman-break luminosity function at z=3 Creation of the Far-IR Populations SPICA Workshop, November 2006

27. Predictions with a Flat IMF in Starbursts 850 micron counts Lyman break LF z=3 Creation of the Far-IR Populations SPICA Workshop, November 2006

28. Which Changes Drive Agreement? Use standard IMF in bursts Switch off minor merger bursts Creation of the Far-IR Populations SPICA Workshop, November 2006

29. Predicted/Observed 850  N(z) Baugh et al. (2005) Chapman et al. (2003) Creation of the Far-IR Populations SPICA Workshop, November 2006

30. Predictions at Other Wavelengths 8 micron counts and N(z) : dust & PAHs start to dominate Creation of the Far-IR Populations SPICA Workshop, November 2006

31. Predictions at Other Wavelengths 160 micron number counts and redshift distribution Creation of the Far-IR Populations SPICA Workshop, November 2006

32. Predictions at Other Wavelengths 24 micron number counts and redshift distribution Accurate modelling of PAHs essential Creation of the Far-IR Populations SPICA Workshop, November 2006

33. Predictions at Other Wavelengths Discrepancy with inferred Photo-z n(z) at 24 microns Sources brighter than 83 micro Jy. Creation of the Far-IR Populations SPICA Workshop, November 2006

34. Evidence in Support of Top-Heavy IMF Model with top-heavy IMF matches metal abundances in ICM Nagashima et al. 2005 Type I & Type II SN Creation of the Far-IR Populations SPICA Workshop, November 2006

35. Number Counts at 24  m Accurate modelling of PAH emission is crucial Creation of the Far-IR Populations SPICA Workshop, November 2006

36. Number Counts in Far-IR 70  m 160  m Creation of the Far-IR Populations SPICA Workshop, November 2006

37. Predicted dN/dz at 3.6  m Creation of the Far-IR Populations SPICA Workshop, November 2006

38. Predicted dN/dz at 24  m Creation of the Far-IR Populations SPICA Workshop, November 2006

39. Predicted dN/dz at 70  m Creation of the Far-IR Populations SPICA Workshop, November 2006

47. Global star formation history Dynamical time scaling Fixed timescale Baugh et al. 2005