Robust Predictions for High-z Galaxies: What will we learn with JWST? Andrew Benson California Institute of Technology

6 June 2011 Robust Predictions for High-z Galaxies2 ● How will JWST advance understanding of galaxy formation theory – What physical processes will it constrain? ● A well established “standard model” exists – Is it correct? – Can it make robust predictions? ● Need a coherent framework for calculating expectations Motivation Motivation | Requirements | Stellar Mass Functions | Robustness | Physics Solvers | Summary

6 June 2011 Robust Predictions for High-z Galaxies3 ● A Galaxy Formation Toolkit – Modular – Comprehensive – Well documented – Open Source – Aims to include current best understandings and calibrations Motivation | Requirements | Stellar Mass Functions | Robustness | Physics Solvers | Summary

6 June 2011 Robust Predictions for High-z Galaxies4 Motivation | Requirements | Stellar Mass Functions | Robustness | Physics Solvers | Summary What's Needed from Theory? ● Many advances in physics modeling – Reionization – Star formation – Cooling ● Less attention to: – Generating insights – Robustness AJB (2000)

6 June 2011 Robust Predictions for High-z Galaxies5 Requirements JWST DWS GIMIC Simulation G ALACTICUS Motivation | Requirements | Stellar Mass Functions | Robustness | Physics Solvers | Summary ● Volume + resolution: – JWST z~4 ● Hydro simulation – Future expectation ● G ALACTICUS model ● Cosmic variance study ● Modest parameter variation

6 June 2011 Robust Predictions for High-z Galaxies6 Comparing Physics Solvers Motivation | Requirements | Stellar Mass Functions | Robustness | Physics Solvers | Summary Bower, Crain, AJB + (2011) GIMIC hydrodynamical simulation Semi-analytic code with same physics model

6 June 2011 Robust Predictions for High-z Galaxies7 Motivation | Requirements | Stellar Mass Functions | Robustness | Physics Solvers | Summary A (Far Too) Simple Model IGM sta r Ω b Ω 0 ˙ M Stars Galaxy hal o Foreboding something much more complicated...

6 June 2011 Robust Predictions for High-z Galaxies8 Assessing Robustness of Models Motivation | Requirements | Stellar Mass Functions | Robustness | Physics Solvers | Summary WMAP-7 parameter covariance Can't fit shape of observed star formation history ε star =1

6 June 2011 Robust Predictions for High-z Galaxies9 Motivation | Requirements | Stellar Mass Functions | Robustness | Physics Solvers | Summary Black Hole IGM Cooling Gas Ω b Ω 0 ˙ M hal o Cold Gas Stars Outflow- ed Gas Cold Gas Stars Gas Lost From Halos Dark Matter Halo Halo Gas Galaxy Disk Spheroid A More Complete Model IGM sta r Ω b Ω 0 ˙ M hal o Stars Galaxy

6 June 2011 Robust Predictions for High-z Galaxies10 Stellar Mass Functions Motivation | Requirements | Stellar Mass Functions | Robustness | Physics Solvers | Summary

6 June 2011 Robust Predictions for High-z Galaxies11 Bayesian Parameter Constraints α reheat V hot,disk α cool V hot,burst ε * f stab α hot p yield α * f df Motivation | Requirements | Stellar Mass Functions | Robustness | Physics Solvers | Summary Bower, Vernon, AJB + (2010) “Optical depth” through plausible regions Maximal plausibility over projected parameters ● Parameter space search – 10 parameters – 2 datasets ● Time consuming

6 June 2011 Robust Predictions for High-z Galaxies12 Summary ● JWST has potential to provide unique insight into galaxy formation ● Theoretical modeling required to develop this understanding – Physics is established (if not perfectly understood) – Understanding robustness/uncertainties is crucial – Techniques exist but need refining if they're to be used in real-world applications Motivation | Requirements | Stellar Mass Functions | Robustness | Physics Solvers | Summary