The Narrow Line Region Current Models and Future Questions Brent Groves Max Planck Institute for Astrophysics Brent Groves Max Planck Institute for Astrophysics.

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Presentation transcript:

The Narrow Line Region Current Models and Future Questions Brent Groves Max Planck Institute for Astrophysics Brent Groves Max Planck Institute for Astrophysics Invited Talk The Central Engine in AGN Xi’an, October 2006 Invited Talk The Central Engine in AGN Xi’an, October 2006

Brent Groves -NLR Models Model Aims Fit Emission Lines Flux Equivalent Width/ wrt AGN continuum Emission Line Ratios Line width Fit Continuum IR Provide descriptions/predictions of NLR ISM state and ionizing continuum Fit Emission Lines Flux Equivalent Width/ wrt AGN continuum Emission Line Ratios Line width Fit Continuum IR Provide descriptions/predictions of NLR ISM state and ionizing continuum

Brent Groves -NLR Models Ratio vs. Ratio Emission Line Ratio diagrams Visual tool for determining relationships & NLR parameters Useful for diagnosing exciting mechanisms AGN NLR occupy specific regions in each diagram Baldwin et al 1981 Vellieux & Osterbrock Many others... Emission Line Ratio diagrams Visual tool for determining relationships & NLR parameters Useful for diagnosing exciting mechanisms AGN NLR occupy specific regions in each diagram Baldwin et al 1981 Vellieux & Osterbrock Many others... Kewley et al 2006 : astro-ph/

Brent Groves -NLR Models Exciting Mechanisms Photoionization Excitation by UV & X-ray photons originating from the central source Shock Ionization Collisional Excitation from either a jet or winds arising from the central source Photoionization Excitation by UV & X-ray photons originating from the central source Shock Ionization Collisional Excitation from either a jet or winds arising from the central source

Brent Groves -NLR Models Hot on Photons Controlling parameters Gas Abundances, Z Gas density, n H Ionizing spectrum, L ν Column depth of model N H Incident flux/ radius from central source/ ionization parameter Controlling parameters Gas Abundances, Z Gas density, n H Ionizing spectrum, L ν Column depth of model N H Incident flux/ radius from central source/ ionization parameter

Brent Groves -NLR Models Hot on Photons Simple power-law ionizing spectrum, range of n H, and U Good: Can reproduce strong Ratios like [OIII]  5007/Hβ & [NII]  6583/H  Agrees with L bol ∝ L  Bad: Cannot reproduce both high- and low- ionization line strengths simultaneously simple models ruled out (Stasi ń ska 1984) Simple power-law ionizing spectrum, range of n H, and U Good: Can reproduce strong Ratios like [OIII]  5007/Hβ & [NII]  6583/H  Agrees with L bol ∝ L  Bad: Cannot reproduce both high- and low- ionization line strengths simultaneously simple models ruled out (Stasi ń ska 1984)

Brent Groves -NLR Models Shocking Results Controlling Parameters Gas Abundances, Z Pre-shock gas density, n H Shock Velocity, V s Magnetic Parameter, B/n 1/2 Bad: Does not produce strong ratios Good: In some specific objects however... Controlling Parameters Gas Abundances, Z Pre-shock gas density, n H Shock Velocity, V s Magnetic Parameter, B/n 1/2 Bad: Does not produce strong ratios Good: In some specific objects however...

Brent Groves -NLR Models Fitting Failures? Allen, Dopita, & Tsvetanov (1998)

Brent Groves -NLR Models Shockingly Fast? Fast shocks ( V s > 150 km s -1 ) produce ionizing photons (Dopita & Sutherland 1995,96) Post shock gas cools producing photons which diffuse upstream & downstream Upstream ionizes pre-shock gas Combination of collisional & photoionization Good: Correct Ratios Bad: Velocity signatures Fast shocks ( V s > 150 km s -1 ) produce ionizing photons (Dopita & Sutherland 1995,96) Post shock gas cools producing photons which diffuse upstream & downstream Upstream ionizes pre-shock gas Combination of collisional & photoionization Good: Correct Ratios Bad: Velocity signatures

Brent Groves -NLR Models Fitting Failures? Allen, Dopita, & Tsvetanov (1998)

Brent Groves -NLR Models Multi-Component Uses the combination of two or more photoionization models to reproduce both high and low ionization lines Morganti et al. (1981) - Cen. A Kraemer & Crenshaw (2000) Komossa & Schulz (1997) Uses the combination of two or more photoionization models to reproduce both high and low ionization lines Morganti et al. (1981) - Cen. A Kraemer & Crenshaw (2000) Komossa & Schulz (1997) Komossa & Schulz (1997) Komossa & Schulz (1997)

Brent Groves -NLR Models Multi-Component Uses the combination of two or more photoionization models to reproduce both high and low ionization lines Morganti et al. (1981) - Cen. A Kraemer & Crenshaw (2000) Komossa & Schulz (1997) Murayama & Taniguchi (1998); Nagao et al (2001) - HINER Baskin & Laor (2005) - OIII strength Uses the combination of two or more photoionization models to reproduce both high and low ionization lines Morganti et al. (1981) - Cen. A Kraemer & Crenshaw (2000) Komossa & Schulz (1997) Murayama & Taniguchi (1998); Nagao et al (2001) - HINER Baskin & Laor (2005) - OIII strength Murayama & Taniguchi (1998)

Brent Groves -NLR Models Multi-Component Uses the combination of two or more photoionization models to reproduce both high and low ionization lines Problem: Too many free variables More Physically Constrained combinations Combination of Matter bounded and Ionization bounded clouds (Binette, Wilson & Storchi-Bergmann) Local Optimally-emitting Clouds (Ferguson et al.) Uses the combination of two or more photoionization models to reproduce both high and low ionization lines Problem: Too many free variables More Physically Constrained combinations Combination of Matter bounded and Ionization bounded clouds (Binette, Wilson & Storchi-Bergmann) Local Optimally-emitting Clouds (Ferguson et al.)

Brent Groves -NLR Models A Matter of Bounding Uses a set ionization parameter IB clouds see absorbed ionizing spectrum IB clouds also different pressure to MB clouds Spectrum controlled by ratio of components, A M/I Uses a set ionization parameter IB clouds see absorbed ionizing spectrum IB clouds also different pressure to MB clouds Spectrum controlled by ratio of components, A M/I A M/I models use a varying contribution of Matter bounded and Ionization bounded clouds

Brent Groves -NLR Models A Matter of Bounding A M/I models use a varying contribution of Matter bounded and Ionization bounded clouds Allen, Dopita, & Tsvetanov (1998)Binette, Wilson & Storchi-Bergmann (1996)

Brent Groves -NLR Models LOC, stock & barrel... Spectra dominated by selection effects - we see the strongest emitting clouds for each line Each line emits strongest near critical density recreates linewidth-n e critical relation Spectra dominated by selection effects - we see the strongest emitting clouds for each line Each line emits strongest near critical density recreates linewidth-n e critical relation Ferguson et al (1997)

Brent Groves -NLR Models LOC, stock & barrel... Determine emission line flux over range of parameters (U,n) The total line flux is integral of cloud distribution function ψ(r,n) Determine emission line flux over range of parameters (U,n) The total line flux is integral of cloud distribution function ψ(r,n) Spectra dominated by selection effects - we see the strongest emitting clouds for each line Ferguson et al (1997)

Brent Groves -NLR Models Dusty, P rad Dominated Clouds At high U 0 ( U 0  ), dust dominates the opacity Hence, dust dominates radiation pressure In an isobaric system P gas gradient ≈ P rad gradient Radiation pressure on dust dominates NLR cloud structure! At high U 0 ( U 0  ), dust dominates the opacity Hence, dust dominates radiation pressure In an isobaric system P gas gradient ≈ P rad gradient Radiation pressure on dust dominates NLR cloud structure!

Brent Groves -NLR Models A Bit of Self Control Ionisation Front For U  , density near IF dependent on incident U 0 U ∝  U 0, but U ∝  1/n H For U  , density near IF dependent on incident U 0 U ∝  U 0, but U ∝  1/n H

Brent Groves -NLR Models A Bit of Self Control For U  , density near IF dependent on incident U 0 U ∝  U 0, but U ∝  1/n H Local U becomes independent of U 0 !! Self regulatory mechanism for constant emission lines !! For U  , density near IF dependent on incident U 0 U ∝  U 0, but U ∝  1/n H Local U becomes independent of U 0 !! Self regulatory mechanism for constant emission lines !!

Brent Groves -NLR Models Dusty Work Dust also: Hardens the radiation field (cf A M/I models) Competes with Hydrogen for ionizing photons Dust also: Hardens the radiation field (cf A M/I models) Competes with Hydrogen for ionizing photons

Brent Groves -NLR Models Dusty Work Dust also: Hardens the radiation field (cf A M/I models) Competes with Hydrogen for ionizing photons Increased Temperature through Photoelectric heating (ie R OIII increased) Depletes Refractory Elements (Good and Bad) Corresponding IR emission Dust also: Hardens the radiation field (cf A M/I models) Competes with Hydrogen for ionizing photons Increased Temperature through Photoelectric heating (ie R OIII increased) Depletes Refractory Elements (Good and Bad) Corresponding IR emission Bock et al. (2000)

Brent Groves -NLR Models Collapsing Curves Models cluster in the region of observations Groves, Dopita & Sutherland (2004) Models fail with high ionization coronal lines Iron lines like FeVII overdepleted Models fail with high ionization coronal lines Iron lines like FeVII overdepleted

Brent Groves -NLR Models Big Picture? Cecil et al. (2002) Dopita et al. (2002)

Brent Groves -NLR Models Big Picture Individual NLR consist of many clouds range of densities & pressure possible abundance & dust variations range of absorbing columns & variation of incident spectra Best - Multi component clouds? Individual NLR consist of many clouds range of densities & pressure possible abundance & dust variations range of absorbing columns & variation of incident spectra Best - Multi component clouds?

Brent Groves -NLR Models Big Picture Individual NLR consist of many clouds range of densities & pressure possible abundance & dust variations range of absorbing columns & variation of incident spectra Best - Multi component clouds? AGN surveys (ie SDSS) Wider range of parameters possible variation in incident spectra Simpler one or tow component cloud determine average properties and relationships Contribution of Shocks... (Contini, Viegas & Prieto (2002, 04) Individual NLR consist of many clouds range of densities & pressure possible abundance & dust variations range of absorbing columns & variation of incident spectra Best - Multi component clouds? AGN surveys (ie SDSS) Wider range of parameters possible variation in incident spectra Simpler one or tow component cloud determine average properties and relationships Contribution of Shocks... (Contini, Viegas & Prieto (2002, 04)

Brent Groves -NLR Models Sweet Separation Groves, Heckman & Kauffmann (2006) Kewley, Groves et al. (2006)

Brent Groves -NLR Models Sweet Separation

Brent Groves -NLR Models Sweet Separation Groves et al 2004 NLR 2Z o model Dopita et al 2006 SB M cl /P o =1 model

Brent Groves -NLR Models Sweet Separation

Brent Groves -NLR Models Heavy Metal Groves, Heckman & Kauffmann (2004)

Brent Groves -NLR Models Seeing the Unseen The Obscured EUV Continuum NGC 1068: Alexander et al (2000) NGC 4151: Alexander et al (1999) Martins, Viegas & Grünwald (1999)

Brent Groves -NLR Models When does it End?

Brent Groves -NLR Models A Model Ending With the current NLR models we have a good physical Understanding of NLR and its appearance & emission lines The models can be used to determine properties of the NLR and AGN (but Caution needed!) Models are still limited... but heading towards a full 3D, dynamical picture of the NLR... One step at a time! With the current NLR models we have a good physical Understanding of NLR and its appearance & emission lines The models can be used to determine properties of the NLR and AGN (but Caution needed!) Models are still limited... but heading towards a full 3D, dynamical picture of the NLR... One step at a time!