Spectral modeling and diagnostics in various
astrophysical environmentsJelle Kaastra
SRON
Topics
• Multi-temperature structure
• Resonance scattering in groups of galaxies
• Foreground absorption
• Photoionised outflows from AGN
Several examples using SPEX
(www.sron.nl/spex)
2
I. Multi-temperature structure
A warning against over-simplification
3
4
The Fe bias
• 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)
Multi-T 1T
5
Complex temperature structure I(de Plaa et al. 2006)
• Sérsic 159-3, central 4 arcmin
• Better fits 1Twdemgdem
• Implication for Fe: 0.360.350.24
• Implication for O: 0.360.300.19
6
Inverse iron bias: how does it work?
• Simulation: 2 comp, T=2 & T=4 keV, equal emission measure
• Best fit 1-T gives T=2.68 keV
• Fitted Fe abundance 11 % too high
• Due to different emissivity for Fe-L, Fe-K
7
Complex temperature structure II(Simionescu et al. 2008)
• Example: Hydra A• Central 3 arcmin:• Full spectrum: Gaussian
in log T (σ=0.2)• 1T fits individual regions:
also Gaussian• Confirmed by DEM
analysis (blue & purple)
II Resonance scattering in groups of galaxies
The importance of accurate atomic data
(Fe XVII)
8
Resonance scattering & turbulence
9
Resonance scattering(NGC 5813, de Plaa et al. 2012)
10
Measured and predicted line ratios(de Plaa et al. 2012)
11
Results
• NGC 5813:
vturb = 140-540 km/s (15-45% of pressure)
• NGC 5044:
vturb >320 km/s (> 40% turbulence)
12
III Foreground absorption
Nasty correction factors are interesting!
13
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
14
Adding warm+hot gas, dust
15
Adding warm & hot gas
Adding dust
Oxygen complexity
16
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)
1722 Ang 23.7 Ang
Tra
nsm
issi
on
Absorption edges: more on dust• optimal view O & Fe• Fe 90%, O 20% in dust
(Mg-rich silicates rather than Fe-rich: Mg:Fe 2:1 in silicates)
• Metallic iron + traces oxydes
• Shown: 4U1820-30, (Costantini et al. 2012)
Are we detecting GEMS?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
Mg silicate Metallic iron
FeS
Crystal olivine, pyroxeneWith Mg
Glassy structure +FeS
Cosmic rays+radiation
Sulfur evaporation GEMS
IV Photoionised outflows from AGN
The need for complete models
and excellent data
20
Why study AGN outflows?
21
Accretion
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
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
22
23
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
Sample spectraRGS 600 ks, Detmers et al. 2011 (paper III)
24
Absorption Measure Distribution
25
Ionisation parameter ξ
Em
issi
on m
easu
re
Col
umn
dens
ity Discrete components
Continuousdistribution
Temperature
Discrete ionisation components?Detmers et al. 2011
• Fitting RGS spectrum with 5 discrete absorber components (A-E)
26
27
Continuous AMD model?Detmers et al. 2011
• Fit columns with continuous (spline) model
• C & D discrete components!
• FWHM <35% & <80%• B (& A) too poor statistics
to prove if continuous• E harder determined:
correlation ξ & NH
Discrete components
C
D
B
E
Pressure equilibrium? No!
28
Pressure Pressure
Tem
pera
ture
Differences photo-ionisation models
29
30
Density estimates: reverberation
• If L increases for gas at fixed n and r, then ξ=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
trnr
Time-dependent calculation
31
Hard X
Soft X
Total
Results: where is the outflow?(Kaastra et al. 2012)
32
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)
33