Studying AGN with high-resolution X-ray spectroscopy

Jelle Kaastra

SRONNahum 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

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Introduction:The influence of AGN outflows

• Dispersal heavy elements into IGM & ICM• Ionisation structure IGMevolution host galaxy • How created? Structure? Mass & energy?

Confinement?• Crucial to understanding central engine:

– Accretion process– Energy budget

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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

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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

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

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

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Absorption measure distribution

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Ionisation parameter ξ

Em

issi

on m

easu

re

Col

umn

dens

ity Discrete components

Continuousdistribution

Temperature

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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

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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

• 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

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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

trnr

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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.

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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

• 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 2Gb8 Mb, rebinning…) See Kaastra et al. 2011; see auxilary programs in SPEX distribution www.sron.nl/spex

• 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

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Broad-band spectrum & variability(Mehdipour et al., Petrucci et al., talks

this afternoon)

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.

• 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

Fe-K line & variability(Ponti et al.; talk Petrucci et al.)

3-10 keV flux

Line

Int

ensi

ty

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OM Grism spectrum

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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)

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Abundances(Steenbrugge et al., poster G45)

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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

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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

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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

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No O I from host galaxy

O I host galaxy

(not detected,

NH<5x1018 cm-2)

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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

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Sample high-resolution spectra

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Example of broad emission lines

O VIII Lyα O VII triplet

Photoionisation modelling RGS spectrum(Detmers 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!

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Mehdipour et al. 2011

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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?

A B C

D

E

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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.

C

D

B

E

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

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Expected response absorbers for 0.1 dex luminosity increase

Time-dependent photo-ionisation

• Time evolution ion concentrations ni:

• dni/dt = Aij(t) nj

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

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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

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Mass loss through the wind

2cML acc

vLvnr )/(2

accloss MM

vnrmM ploss2

2

)/(

cm

v

p

v (km/s) -100 -1000

ξ=1 0.001 0.0001

ξ=1000 1.0 0.1

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Conclusions

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

• High quality spectra, not limited by statistics

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