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

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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)
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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 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 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 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 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 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 Properties of benchmark model Nick Higginbottom Modelling the spectra of (BAL)QSOs Properties of benchmark model Nick Higginbottom Modelling the spectra of (BAL)QSOs Properties of benchmark model Nick Higginbottom Modelling the spectra of (BAL)QSOs Properties of benchmark model Nick Higginbottom Modelling the spectra of (BAL)QSOs Properties of benchmark model 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 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 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 X-ray properties of benchmark model Figure from Saez+ 2011 40 85 75 Benchmark model Nick Higginbottom Modelling the spectra of (BAL)QSOs 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 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 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 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 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 Thanks! Nick Higginbottom Modelling the spectra of (BAL)QSOs Making CIV in the wind – lessons learnt
  • Photoionization absorption in the root of the wind attenuates UV
  • Making CIV in the wind – lessons learnt
  • Easier to make CIV with a larger BH:
  • 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
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