Spectral modeling and diagnostics in various astrophysical environments

1. Spectral modeling and diagnostics in various astrophysical environments Jelle Kaastra SRON

2. Topics • Multi-temperaturestructure • Resonance scattering in groups of galaxies • Foregroundabsorption • Photoionisedoutflowsfrom AGN Severalexamplesusing SPEX (www.sron.nl/spex)

3. I. Multi-temperature structure A warning against over-simplification

4. 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)

5. 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

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)

8. II Resonance scattering in groups of galaxies The importance of accurate atomic data (Fe XVII)

9. Resonance scattering & turbulence

10. Resonance scattering(NGC 5813, de Plaa et al. 2012)

11. Measured and predicted line ratios(de Plaa et al. 2012)

12. Results • NGC 5813: vturb = 140-540 km/s (15-45% of pressure) • NGC 5044: vturb >320 km/s (> 40% turbulence)

13. III Foreground absorption Nasty correction factors are interesting!

14. 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

15. Adding warm+hot gas, dust Adding warm & hot gas Adding dust

16. Oxygen complexity

17. 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

18. 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)

19. 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 rays+radiation Metallic iron Mg silicate Glassy structure + FeS Sulfur evaporation GEMS

20. IV Photoionised outflows from AGN The need for complete models and excellent data

21. 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

22. 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

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

24. Sample spectraRGS 600 ks, Detmers et al. 2011 (paper III)

25. Absorption Measure Distribution Discrete components Emission measure Column density Continuous distribution Ionisation parameter ξ Temperature

26. Discrete ionisation components?Detmers et al. 2011 • Fitting RGS spectrum with 5 discrete absorber components (A-E)

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 D E C B

28. Pressure equilibrium? No! Temperature Pressure Pressure

29. Differences photo-ionisation models

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 trnr

31. Time-dependent calculation Total Soft X Hard X

32. Results: where is the outflow?(Kaastra et al. 2012)

33. 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)