Simulating the spectra of Quasars: A simple disk-wind model for BALQSOs

1. Simulating the spectra of Quasars:A simple disk-wind model for BALQSOs Nick Higginbottom (Southampton University) Christian Knigge (Southampton University) Knox Long (STScI) Stuart Sim (Queens University - Belfast) James Matthews (Southampton University) Naples 21st May 2013

2. Overview • The problem – BALQSOs, outflows and QSO unification • A benchmark disk-wind model • Physical state and synthetic spectra for benchmark model • X-ray results and sensitivity • Summary and the future Nick Higginbottom Modelling the spectra of (BAL)QSOs

3. BALQSOs • Blue shifted absorption features imply outflows at velocities of ≥ 0.1c (Weymann+ 1981) • Continuum / emission features similar to other QSO types • Common underlying structure? • Disk-winds? • BALQSO clearest indicator Elvis (2000) Gibson+ (2009) • Reichard+(2003) Nick Higginbottom Modelling the spectra of (BAL)QSOs

4. BALQSOs – Evolution vs Orientation • About 20% of the population of QSOs exhibit BAL properties (e.g. Knigge+[2008] and Hewett & Foltz [2003]) • Evolution: • All QSOs spend 20% of the time as BALs • Orientation • BAL Outflows cover 20% of viewing angles • Our Aims: • Turn qualitative models into quantitative predictions using Monte Carlo radiative transfer code - python(Long & Knigge [2003], Higginbottom et al. [2013 in prep]) • Produce something that looks like a BALQSO from some directions • Can such models look like other types of QSO from other directions? • Can the X-ray properties of such models be made to agree with observations? Nick Higginbottom Modelling the spectra of (BAL)QSOs

5. Python – a 3D ionization and radiative transfer code. • Arbitrary 3D wind geometry • Kinematic models • Hydrodynamic simulations • Monte Carlo radiative transfer • Fast ionization calculations • Modified Saha approximation • Thermal / Radiative equilibrium • heating/cooling: free free, line, Compton • photoionzation, recombination Validation of python (dots) vscloudy (lines) Nick Higginbottom Modelling the spectra of (BAL)QSOs

6. A benchmark wind model • INPUT SPECTRUM • MBH = 109M • Macc= 5Myr-1 • Lx = 1043ergs s-1 • WIND PARAMETERS • Rmin= 300RG • Rmax= 600RG • θmin= 70° • θmax= 82° • Mwind= 5Myr-1 • V∞ = Vescape Geometry based on Shlosman and Vitello (1993) Nick Higginbottom Modelling the spectra of (BAL)QSOs

7. Properties of benchmark model Nick Higginbottom Modelling the spectra of (BAL)QSOs

8. Properties of benchmark model Nick Higginbottom Modelling the spectra of (BAL)QSOs

9. Properties of benchmark model Nick Higginbottom Modelling the spectra of (BAL)QSOs

10. Properties of benchmark model Nick Higginbottom Modelling the spectra of (BAL)QSOs

11. Properties of benchmark model

12. Predicted Spectra – 40° • (Weak) thermal / scattering emission lines • Slight continuum enhancement due to electron scattering Continuum without wind Disk-wind spectrum Nick Higginbottom Modelling the spectra of (BAL)QSOs

13. Predicted Spectra – 75° • Sightline into wind cone • Strong BAL features Continuum without wind Disk-wind spectrum Attenuated continuum Nick Higginbottom Modelling the spectra of (BAL)QSOs

14. Predicted Spectra – 85° • Sightline through base of wind • Emission lines appear brighter due to attenuated continuum Continuum without wind Disk-wind spectrum Attenuated continuum Nick Higginbottom Modelling the spectra of (BAL)QSOs

15. X-ray properties of benchmark model Figure from Saez+ 2011 40 85 75 Benchmark model Nick Higginbottom Modelling the spectra of (BAL)QSOs

16. Increasing LX Increasing X-ray luminosity destroys the BAL X-ray luminosity Subplot scales flux Mass loss rate through wind -3x109 velocity (cms-1) +3x109 Nick Higginbottom Modelling the spectra of (BAL)QSOs

17. Increasing LX and Mwind Increasing X-ray luminosity destroys the BAL Increasing the mass loss rate gets it back! X-ray luminosity Subplot scales flux Mass loss rate through wind -3x109 velocity (cms-1) +3x109 Nick Higginbottom Modelling the spectra of (BAL)QSOs

18. Increasing LX and Mwind Increasing X-ray luminosity destroys the BAL Increasing the mass loss rate gets it back! For Lx= 2x1044ergs s-1 need Mwind=20Myr -1 Mwind=4Macc OK?? X-ray luminosity . . . Subplot scales flux Mass loss rate through wind -3x109 velocity (cms-1) +3x109 Nick Higginbottom Modelling the spectra of (BAL)QSOs

19. X-ray properties of high LxMwind model Figure from Saez+ 2011 40 85 75 40 85 75 Benchmark model Observable values for L2-10keV=2e44ergs s-1, 25 solar mass per year mass loss Nick Higginbottom Modelling the spectra of (BAL)QSOs

20. Summary and plans for the future • We have produced a simple disk-wind BAL model Higginbottom et al. (2013 in prep) • Correct ionization state • Strong BAL features • X-ray weak • Weak line emission • The next steps • Explore parameter space • Uniqueness? X-rays? Emission? • Investigate hydro-models - Higginbottom, Proga et al. (2013 in prep) Data from Proga&Kallman 04 Nick Higginbottom Modelling the spectra of (BAL)QSOs

21. Thanks! Nick Higginbottom Modelling the spectra of (BAL)QSOs

22. Making CIV in the wind – lessons learnt • Photoionization absorption in the root of the wind attenuates UV

23. Making CIV in the wind – lessons learnt • Easier to make CIV with a larger BH:

24. Varying X-rays • Fiducial model is X-ray weak • Input αOX varies from -2.4 (pole on) to -1.8 (edge on) • Emergent αOX much lower due to X-ray absorption in the wind for BAL sightlines