Spectral modeling and diagnostics in various astrophysical environments

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Spectral modeling and diagnostics in various
astrophysical environments

• Jelle Kaastra
• SRON

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Topics

• Multi-temperature structure
• Resonance scattering in groups of galaxies
• Foreground absorption
• Photoionised outflows from AGN
• Several examples using SPEX
• (www.sron.nl/spex)

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I. Multi-temperature structure

• A warning against over-simplification

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The Fe bias
Multi-T
1T

• 1T models sometimes too simple e.g. in cool
  cores
• Using 1T gives biased abundances (Fe-bias, Buote
  2000)
• Example core M87 (Molendi Gastaldello 2001)

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Complex temperature structure I(de Plaa et al.
2006)

• Sérsic 159-3, central 4 arcmin
• Better fits 1T?wdem?gdem
• Implication for Fe 0.36?0.35?0.24
• Implication for O 0.36?0.30?0.19

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Inverse iron bias how does it work?

• Simulation 2 comp, T2 T4 keV, equal emission
  measure
• Best fit 1-T gives T2.68 keV
• Fitted Fe abundance 11 too high
• Due to different emissivity for Fe-L, Fe-K

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Complex temperature structure II(Simionescu et
al. 2008)

• Example Hydra A
• Central 3 arcmin
• Full spectrum Gaussian in log T (s0.2)
• 1T fits individual regions also Gaussian
• Confirmed by DEM analysis (blue purple)

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II Resonance scattering in groups of galaxies

• The importance of accurate atomic data
• (Fe XVII)

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Resonance scattering turbulence
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Resonance scattering(NGC 5813, de Plaa et al.
2012)
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Measured and predicted line ratios(de Plaa et
al. 2012)
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Results

• NGC 5813
• vturb 140-540 km/s (15-45 of pressure)
• NGC 5044
• vturb gt320 km/s (gt 40 turbulence)

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III Foreground absorption

• Nasty correction factors are interesting!

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Interstellar X-ray absorption

• High-quality RGS spectrum X-ray binary GS1826-238
  (Pinto et al. 2010)
• ISM modeled here with pure cold gas
• Poor fit

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Adding warmhot gas, dust
Adding warm hot gas
Adding dust
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Oxygen complexity
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Interstellar dust

• SPEX (www.sron.nl/spex) currently has 51
  molecules with fine structure near K- L-edges
• Database still growing (literature, experiments
  Costantini De Vries)
• Example near O-edge (Costantini et al. 2012)

Transmission
23.7 Ang
22 Ang
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Absorption edges more on dust

• optimal view O Fe
• Fe 90, O 20 in dust (Mg-rich silicates rather
  than Fe-rich MgFe 21 in silicates)
• Metallic iron traces oxydes
• Shown 4U1820-30, (Costantini et al. 2012)

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Are we detecting GEMS?
FeS

• GEMS glass with embedded metal sulphides
• (e.g. Bradley et al. 2004)
• interplanetary origin, but some have ISM origin
• ? invoked as prototype of a classical silicate

Crystal olivine, pyroxene With Mg
Cosmic raysradiation
Metallic iron
Mg silicate
Glassy structure FeS
Sulfur evaporation
GEMS
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IV Photoionised outflows from AGN

• The need for complete models
• and excellent data

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Why study AGN outflows?

• Feeding the monster delicate balance between
  inflow outflow onto supermassive black hole
• Co-evolution of black hole host galaxy
• Key to understand galaxy formation

Accretion
Outflows
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Main questions outflows

• What is the physical state of the gas?
• Uniform density clouds in pressure equilibrium?
• Or like coronal streamers, lateral density
  stratification?
• Where is the gas?
• Where is it launched? Disk, torus?
• Mass loss, Lkin depend on r
• Important for feedback

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Observation campaign Mrk 509(Kaastra et al. 2011)

• Monitoring campaign covering 100 days
• Excellent 600 ks time-averaged spectrum
• Observatories involved
• XMM-Newton (UV, X-ray)
• INTEGRAL (hard X-ray)
• HST/COS (UV)
• Swift (monitoring)
• Chandra (softest X-rays)
• 2 ground-based telescopes

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Sample spectraRGS 600 ks, Detmers et al. 2011
(paper III)
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Absorption Measure Distribution
Discrete components
Emission measure Column density
Continuous distribution
Ionisation parameter ?
Temperature
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Discrete ionisation components?Detmers et al.
2011

• Fitting RGS spectrum with 5 discrete absorber
  components (A-E)

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Continuous AMD model?Detmers et al. 2011

• Fit columns with continuous (spline) model
• C D discrete components!
• FWHM lt35 lt80
• B ( A) too poor statistics to prove if
  continuous
• E harder determined correlation ? NH
• ? Discrete components

D
E
C
B
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Pressure equilibrium? No!
Temperature
Pressure
Pressure
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Differences photo-ionisation models
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Density estimates reverberation

• If L increases for gas at fixed n and r, then
  ?L/nr² increases
• ? change in ionisation balance
• ? ionic column density changes
• ? transmission changes
• Gas has finite ionisation/recombination time tr
  (density dependent as 1/n)
• ? measuring delayed response yields tr?n?r

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Time-dependent calculation
Total
Soft X
Hard X
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Results where is the outflow?(Kaastra et al.
2012)
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Conclusions

• We showed 4 examples of different challenging
  astrophysical modeling
• All depend on availability reliable atomic data
• The SPEX code (www.sron.nl/spex) allows to do
  this spectral modeling fitting
• Code its applications continuing development
  (since start 1970 by Mewe)