Quasar Clustering (A Dabbler’s Perspective) CCAPP AGN Workshop: Oct. 2, 2007

1. Quasar Clustering(A Dabbler’s Perspective)CCAPP AGN Workshop: Oct. 2, 2007 Adam Lidz (CfA) Thanks to: Phil Hopkins, Lars Hernquist, T.J. Cox, and others….

2. Outline • Motivation • Some observational results • Theoretical modeling • Synthesis between models and observations • Let’s discuss how to move forward!

3. $64K Questions • Quasar triggering/fueling mechanisms? Tests of the merger hypothesis. Importance of other fueling mechanisms? • Quasar lifetimes and lightcurves. Extended or light-bulbs? • Association with galaxy formation: how are quasar and galaxy populations related? • Which dark matter halos host quasars? Are there specific types of halos that host? Redshift evolution? • Is black hole growth self-regulated? Nature of regulation: momentum or energy driven feedback? Does this vary w/ z?

4. What can we measure? • Redshift dependence of clustering. • Luminosity dependence. • Compare quasar clustering and that of different galaxy populations. Compare z=0 galaxy populations to high-z quasar populations. • Small-scale quasar clustering. Osmer 81 da Angela et al. (2006)

5. Redshift Dependence • Bias is a strong function of z. • Measurements at all z consistent with M_halo ~ 4 x 10^12 M_sun/h. • Shen et al. (2007): roughly the same M_halo at z > 3. • Is this a clue? Hopkins et al. astro-ph/0611792

6. Luminosity Dependence • Observations indicate little luminosity dependence, athough not very strong statistically. • Different than e.g. SDSS red galaxy populations, naïve expectations? Top: Adelberger & Steidel 2005 Bottom: da Angela et al. 2006

7. Small-Scale Clustering • Observations show “excess” clustering on small-scales? • Green points from Hennawi et al. (2005), blue points from Myers et al. (2006), plot from Hopkins et al. arXiv:0706.1243

8. Is it “excess” power? • What is the right “null” model? • Z~4 LBG two-point function also shows strong two-point correlation function on small-scales. (Ouchi et al. 2005) [Thanks, Martin!] • Cooray model reproduces, but not with a merging population. Cooray & Ouchi 2006

9. Theoretical Models • Springel, Di Matteo, Hernquist, Cox, Hopkins, Li, Robertson, etc… simulations of major galaxy mergers including black hole growth. • Gas-rich major mergers --> large inflows of gas. • Black hole is sub-resolution sink particle that accretes gas according to Bondi-Hoyle/Eddington limited rate depending on local gas density.

10. Quasar Lifetimes and Lightcurves • Strong luminosity evolution with time -- extended dim periods, short duration peak phases. • Different than lightbulb, exponential growth models. Hopkins et al. astro-ph/0504252

11. Modeling Quasar Abundances • Simulations of individual mergers give t_life(L|L_peak). • Need rate of gas-rich major mergers to model abundances. Either try to predict rate of relevant mergers (Hopkins et al. 2007), or calibrate empirically off of one observation and make other predictions (Hopkins et al. 2005): dn/dt(L_peak, z).

12. Hopkins et al. interpretation of luminosity function • Extended period at low luminosities ---> bright and faint quasars are mostly similar sources seen at different stages of their lifetime. • Break is set by peak in dn/dt • Much different than light-bulb models. Hopkins et al. 2005

13. Modeling Quasar Clustering • Degeneracy from luminosity function alone: are quasars numerous yet short-lived or rare, yet long-lived? (Martini & Weinberg 2001, Haiman & Hui 2001). Distinguish with clustering! • In merger models, L_peak is correlated with halo mass, but instantaneous luminosity is not so correlated w/ M_h. Take into account simulated light curves, correlation + scatter with halo-mass, and empirical constraints or theoretical predictions for dn/dt (Lidz et al. 2005):

14. Luminosity Dependence • Luminosity dependence of quasar clustering may offer a test! • Dim sources are mostly similar to bright sources, but seen in a different phase of evolution. • Expect weak luminosity dependence although some at high L. • Scatter in L_p -- M_halo also washes out b(L). Lidz et al. astro-ph/0507361

15. Luminosity dependence: comparison w/ observations • Observations favor weak luminosity dependence and favor complex lightcurves, disfavor lightbulb models… • But not a very strong test so far. Hopkins et al. arXiv:0706.1243

16. Luminosity Dependence and Fueling Mechanisms • Future measurements might turn up signature of non-merger fueling at very low luminosity. • Black dashed show merger-triggering, black solid includes impact from non-merger events: stochastic accretion through collisions w/ molecular clouds, gas inflows through bars, etc.. Hopkins et al. astro-ph/0611792

17. Comparing with galaxy clustering • Quasars generally cluster less strongly than red, early-type L_star galaxies, and more strongly than blue, ~ L_star late-types. • Quasars do not directly trace late-type star-forming galaxies. “Intermediate” state between red and blue galaxies? • At z~2.5, like ULIRGs. Hopkins et al. astro-ph/0611792

18. Clustering of Quasar Descendents • b_Q(z_in) --> b(z=0) from linear theory. • There is a characteristic L_star and M_BH at each z. • M_bh (z=0) = 0.001 M_gal • Clustering of quasar “descendents” is consistent with early-type ellipticals but not late-types. Progenitors of early-types hosted quasars! Hopkins et al. astro-ph/0611792

19. Scale Dependent Bias • Linear biasing can be a bad approximation for rare quasar halos even on scales where dm is fairly linear. • Halos from an N-body simulation: M=10^12-10^13 M_sun at z=3.

20. Conclusions • Clustering can help address some of the $64K questions: host halos, light-curves, role in galaxy formation/connection with galaxy populations, and others. • Quasars appear to reside in halos of M~ 4 x 10^12 M_sun, relatively independent of redshift and luminosity. • Thanks!