1. The Stellar Assembly History of Massive Galaxies Decoding the fossil record Raul Jimenez www.physics.upenn.edu/~raulj Licia Verde UPenn Alan Heavens Ben Panter University of Edinburgh

2. Star Formation History – two complementary approaches Two general approaches: Two general approaches: Look for signs of recent SF in galaxies at high z (e.g. UV) (e.g. Lilly et al 1996, Madau et al 1996; Ouchi et al 2003) Look for signs of recent SF in galaxies at high z (e.g. UV) (e.g. Lilly et al 1996, Madau et al 1996; Ouchi et al 2003) Look at nearby galaxies and date the stars in them Look at nearby galaxies and date the stars in them If Copernican Principle holds, they should agree If Copernican Principle holds, they should agree Ouchi 2003

3. Advantages of fossil approach Decouples star formation from mass assembly Decouples star formation from mass assembly Not so sensitive to uncertain obscuration Not so sensitive to uncertain obscuration Get SFR for a wide range of cosmic time Get SFR for a wide range of cosmic time Small statistical errors Small statistical errors Large galaxy samples Large galaxy samples

4. Disadvantages of fossil approach Needs a good theoretical spectral synthesis model Needs a good theoretical spectral synthesis model Redshift-time relation is sensitive to cosmology (but so are volume elements at high z) Redshift-time relation is sensitive to cosmology (but so are volume elements at high z) Poor time- and z- resolution at high z Poor time- and z- resolution at high z

5. Determining Star Formation History from Galaxy Spectra Various indicators over spectral range Various indicators over spectral range Broad spectral shape also contains information Broad spectral shape also contains information Compare spectra from synthetic stellar population models with observed spectra Compare spectra from synthetic stellar population models with observed spectra

6. Characterising the SFH Current models and data allow the star formation rate and metallicity to be determined in around 8-12 time periods Current models and data allow the star formation rate and metallicity to be determined in around 8-12 time periods 10 x 2 + 1 dust parameter = 21 parameters – significant technical challenge 10 x 2 + 1 dust parameter = 21 parameters – significant technical challenge To analyse the SDSS data would take ~200 years To analyse the SDSS data would take ~200 years Needs some way to speed this up by a large factor Needs some way to speed this up by a large factor We use MOPED We use MOPED

7. Sloan Digital Sky Survey 135,000 spectra public in SDSS Data Release 1 (DR1) 135,000 spectra public in SDSS Data Release 1 (DR1) Final goal ~10 6 galaxy spectra Final goal ~10 6 galaxy spectra (Panter, Heavens & Jimenez (2003) analysed 37000 SDSS EDR galaxies)

8. Recovering Star Formation History from Sloan spectra Markov Chain Monte Carlo method used to find best solution and marginal errors

9. Sanity Checks: Stellar Population Models Stellar Population Models Dust model Dust model Stellar masses to SFR: Redshift; 1/V max weight, determined by selection criteria, with magnitudes and surface brightness computed from SFH of each galaxy.

10. More tests. This time systematics of SDSS have been included

11. SFR in galaxies of different stellar masses Split by mass Split by mass Stellar masses: >10 12 M ๏ … < 10 10 M ๏ Galaxies with more stellar mass now formed their stars earlier (Curves offset vertically for clarity)

12. Oldest bin Dark Matter Oldest bin Main progenitor Star formation and dark matter assembly do not track each other However, if only 6% of baryons in today’s dark halo are stars, then star formation efficiency at z~2 needs to be only 10% to account for the observed stellar mass from the fossil record. Even “slow” star formation from molecular clouds can do the job.

13. Conclusions SDSS + MOPED measure past star formation rate from fossil record SDSS + MOPED measure past star formation rate from fossil record Copernican Principle broadly supported Copernican Principle broadly supported Useful observational data on stellar mass function/SFR of different galaxy types Useful observational data on stellar mass function/SFR of different galaxy types Most of the stars in massive galaxies (M * >10 11 M ๏ ) already formed at z~2 Most of the stars in massive galaxies (M * >10 11 M ๏ ) already formed at z~2 The main progenitor of today’s dark matter halo contains enough gas to form the observed stars The main progenitor of today’s dark matter halo contains enough gas to form the observed stars Only 10% of available gas at high-z needs to be converted into stars Only 10% of available gas at high-z needs to be converted into stars Challenge then is to explain why so little gas is transformed into stars Challenge then is to explain why so little gas is transformed into stars www.physics.upenn.edu/~raulj www.physics.upenn.edu/~raulj

14. Illustration: High-resolution spectra MOPED estimates 17- 25 parameters describing star formation history in a few minutes NGC 3623 Sa NGC 3310 Sbc pec Reichardt, Jimenez, Heavens, 2000

15. MCMC errors MCMC errors

16. Results from Sloan Digital Sky Survey: SFR of Universe MOPED + parallelisation reduces time to about 3 weeks LMC dust model Jimenez stellar models Star formation rate Gallego et al 95, Tresse & Maddox 98, Glazebrook et al 99, Sullivan et al 00, Lilly et al 96, Connolly et al 99, Cowie et al 96, Steidel et al 99, Madau et al 96, Ouchi et al 03,Stanway et al 03 See also Baldry et al 2002; Glazebrook et al 2003; Brinchmann et al 2003