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Studying AGN with high-resolution X-ray spectroscopy. Jelle Kaastra SRON

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Studying agn with high resolution x ray spectroscopy l.jpg

Studying AGN with high-resolution X-ray spectroscopy

Jelle Kaastra


Nahum Arav, Ehud Behar, Stefano Bianchi, Josh Bloom, Alex Blustin, Graziella Branduardi-Raymont, Massimo Cappi, Elisa Costantini, Mauro Dadina, Rob Detmers, Jacobo Ebrero, Peter Jonker, Chris Klein, Jerry Kriss, Piotr Lubinski, Julien Malzac, Missagh Mehdipour, Stéphane Paltani, Pierre-Olivier Petrucci, Ciro Pinto, Gabriele Ponti, Eva Ratti, Katrien Steenbrugge, Cor de Vries

Introduction the influence of agn outflows l.jpg
Introduction:The influence of AGN outflows

  • Dispersal heavy elements into IGM & ICM

  • Ionisation structure IGM

  • evolution host galaxy

  • How created? Structure? Mass & energy? Confinement?

  • Crucial to understanding central engine:

    • Accretion process

    • Energy budget

Agn outflows in a nutshell l.jpg
AGN outflows in a nutshell

  • Photo-ionised gas

  • v = -100 to -1000 km/s

  • Seen through line and continuum absorption

  • Spectrum ionic column densities ionization parameter ξ=L/nr²

Kaastra et al. 2000

Photoionisation modelling l.jpg
Photoionisation modelling

  • Radiation impacts a volume (layer) of gas

  • Different interactions of photons with atoms cause ionisation, recombination, heating & cooling

  • In equilibrium, ionisation state of the plasma determined by:

    • spectral energy distribution incoming radiation

    • chemical abundances

    • ionisation parameter ξ=L/nr2 with L ionising luminosity, n density and r distance from ionising source; ξ essentially ratio photon density / gas density

Question 1 structure outflow l.jpg
Question 1:Structure outflow

  • Is it more like rather uniform density clouds in pressure equilibrium?

  • Or is it more like coronal streamers, with lateral density stratification?

Absorption measure distribution l.jpg
Absorption measure distribution

Discrete components

Emission measure Column density



Ionisation parameter ξ


Separate components in pressure equilibrium l.jpg
Separate components in pressure equilibrium?

  • Not all components in press. eq. (same Ξ)

  • Division into ξ comps often poorly defined

  • Continuous NH(ξ) distribution?

  • Others fit discrete components

  • What's going on?

Steenbrugge et al. 2005

Question 2 where is the gas l.jpg
Question 2: Where is the gas?

  • Photo-ionization modeling ξ=L/nr²

  • L obtained from spectrum

  •  only the product nr² known, not r or n

  • Is gas accelerating, decelerating?

Density estimates line ratios l.jpg
Density estimates: line ratios

  • C III has absorption lines near 1175 Å from metastable level

  • Combined with absorption line from ground (977 Å) this yields n

  •  n = 3x104 cm-3 in NGC 3783 (Gabel et al. 2004)  r~1 pc

  • Only applies for some sources, low ξ gas

  • X-rays have similar lines, but sensitive to higher n (e.g. O V, Kaastra et al. 2004); no convincing case yet

Density estimates reverberation l.jpg
Density estimates: reverberation

  • If L increases for gas at fixed n and r, then ξ=L/nr² increases

  •  change in ionisation balance

  •  column density changes

  •  transmission changes

  • Gas has finite ionisation/recombination time tr (density dependent as ~1/n)

  •  measuring delayed response yields trnr

Reverberation ngc 3783 l.jpg
Reverberation: NGC 3783

  • RGS data (Behar et al. 2003): no change in

    Warm absorber  n<300 cm-3, r>10 pc.

  • EPIC data (Reeves et al. 2003): change in

    Warm absorber (larger columns)  n>108 cm-3, r<0.02 pc.

Observation campaign mrk 509 l.jpg
Observation campaign Mrk 509

  • Core: 10 x 60 ks XMM, spaced 4 days (RGS, EPIC & OM all used!)

  • Simultaneous Integral 10 x 120 ks

  • Followed by 180 ks Chandra LETGS, simultaneous with 10 orbits COS (HST)

  • Preceded with Swift (UVOT, XRT) monitoring

  • Supplemented with ground-based (WHT, Pairitel) photometry & grism

  • Period: 4 Sept – 13 Dec 2009 (100 days)

  • 7 papers submitted/accepted, 8 in progress

General data analysis issues l.jpg
General data analysis issues

  • Excellent quality many new steps developed

  • RGS: full usage multi-pointing mode, refinements combining spectra with variable hot pixels, λ-scale, effective area, reducing response 2Gb8 Mb, rebinning…) See Kaastra et al. 2011; see auxilary programs in SPEX distribution

  • PN: Triggered by our campaign improved gain cal

  • OM:extended wavelength range optical grism

  • HST/COS: extensive efforts to improve data analysis for this high-quality spectrum

  • SPEX: allows simultaneous fitting high-res UV & X-ray spectra

Broad band spectrum variability mehdipour et al petrucci et al talks this afternoon l.jpg
Broad-band spectrum & variability(Mehdipour et al., Petrucci et al., talks this afternoon)

Fe k line variability ponti et al talk petrucci et al l.jpg
Fe-K line & variability(Ponti et al.; talk Petrucci et al.)

Line Intensity

  • Broad and neutral Fe K emission well correlated with continuum emission on few days time-scales.

  • No relativistic profile

  • Origin outer disc or inner BLR

3-10 keV flux


Uv optical variability om swift l.jpg
UV-optical variability(OM, Swift)

  • Source was in outburst (0.1 dex in UV) right in the middle of ourt campaign!

Ism absorption talk pinto et al on monday l.jpg
ISM absorption(talk Pinto et al. on Monday)

Abundances steenbrugge et al poster g45 l.jpg
Abundances(Steenbrugge et al., poster G45)

Cos fuse uv absorption lines in mrk 509 kriss et al talk this afternoon l.jpg
COS & FUSE UV Absorption lines in Mrk 509(Kriss et al., talk this afternoon)

  • O VI,Lyβ, & Lyγ from FUSE (Kriss et al. 2000)

  • 14 velocity components seen in COS UV spectrum

  • C IV doublet split by only 500 km/s, so grey regions can’t be used for optical-depth

  • Red lines: velocities X-ray absorbers XMM-Newton/RGS

  • Blue lines: velocities X-ray absorbers Chandra/LETGS

Letgs cos data ebrero et al poster g14 l.jpg
LETGS + COS data(Ebrero et al., poster G14)

  • X-rays: outflow with 3 distinct ionization phases in form of multi-velocity wind. UV spectra: absorption system with 13 kinematic components

  • Analysis kinematic properties & column densities absorbers  UV-absorbing gas co-located with & embedded in lower density high-ionization X-ray absorbing gas

Stacked rgs spectrum l.jpg
Stacked RGS spectrum

  • Galactic O I edge

  • Several narrow absorption lines

  • Detection 31 individual ions

  • Tight upper limits column densities 18 other ions

  • Two main velocity components (+40 and -300 km/s)

  • Highly ionised ions in general higher velocity

No o i from host galaxy l.jpg
No O I from host galaxy

O I host galaxy

(not detected,

NH<5x1018 cm-2)

X ray analysis in more detail l.jpg
X-ray analysis in more detail

  • Fit spectra using a power law + modified blackbody (or even a spline) continuum

  • Where needed, add emission lines: BLR or NLR X-ray lines (no relativistic lines needed)

  • Fit warm absorber using a model  ionic or total column densities

  • Using photo-ionisation model, derive absorption measure distribution NH(ξ)

  • Spectral fits done with SPEX, global fits

Example of broad emission lines l.jpg
Example of broad emission lines


O VII triplet

Photoionisation modelling rgs spectrum detmers et al 2011 l.jpg
Photoionisationmodelling RGS spectrum(Detmers et al. 2011)


et al. 2011

  • Use time-averaged SED

  • Test dependence on SED

  • Proto-solar abundances

  • Multiple ionisation, 3 velocity components

  • Same ion may be present in more than one velocity/ionisation component!

Discrete versus continuous absorption measure distribution l.jpg
Discrete versus continuous absorption measure distribution?

  • Column densities well approximated by sum of 5 components (see table)

  • Higher column for higher ionisation parameter

  • But what about a continuous model?






Continuous model l.jpg
Continuous model

  • Fitted columns with continuous (spline) model

  • Surprise: comps C & D pop-up as discrete components!

  • Upper limits FWHM 35 & 80 %

  • Component B (& A) too poor statistics to prove if continuous

  • Component E also poorer determined: correlation ξ and NH.





Where is the gas l.jpg
Where is the gas?

  • Needs t-dependent model

  • For each of the 5 components: if L increases, ξ must increase (as ξ=L/nr2)

  • From 10 continuum model fits  predicted ξ change for each of 10 observations, compared to average spectrum

  • If gas responds immediately, transmission outflow changes immediately

Time dependent photo ionisation l.jpg
Time-dependent photo-ionisation

  • Time evolution ion concentrations ni:

  • dni/dt = Aij(t) nj

  • Aij(t) contains t-dependent ionisation & recombination rates

Location photoionised gas work in progress l.jpg
Location photoionised gas(work in progress)

  • Component A: Rotating, low ionisation disk + high velocity outflow, 3 kpc (direct imaging [O III] 5007, Philips 1986)

  • Component C: >10 pc (lack of response)

  • Component E: > 1 pc? (lack of response?)

  • See also Kriss (talk this afternoon) and poster Ebrero

Conclusions l.jpg

  • Deep, multi-wavelength monitoring campaigns (AGN) are rewarding:

  • High quality spectra, not limited by statistics

  • “Continuous” light curves, allowing to monitor the variations