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Lessons from other wavelengths. A picture may be worth a thousand words, but a spectrum is worth a thousand pictures.

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Presentation on theme: "Lessons from other wavelengths. A picture may be worth a thousand words, but a spectrum is worth a thousand pictures."— Presentation transcript:

1 Lessons from other wavelengths

2 A picture may be worth a thousand words, but a spectrum is worth a thousand pictures

3 Emission from a Single Cloud  spectrum mainly determined by cloud density n, flux of ionizing photons  –or “ionization parameter”, a combination of these u spectra similar so parameters thought to be “fine-tuned” ionization parameter log line ratios

4 A distribution of clouds u CIV 1549 emission line visibility vs cloud density and distance to continuum source

5 A Distribution of Clouds... u line equivalent width set by density, distance log Density => log Photon Flux => distance => gas at Compton temperature too low ionization 714 17 24 W (C IV) collisionally suppressed constant U

6 Collisionally excited lines Low Ionization Mg II Density => Flux => High Ionization O VI Density => Distance =>

7 Locally Optimally-emitting Clouds u Spectrum originates in highly chaotic environment, with clouds at all densities and distances from the central source u Observed spectrum is result of atomic physics and radiation transport selection effects u This reproduces observed spectrum, emission line profiles, and line-continuum variability lags u Details of individual clouds don’t matter, we can worry about global properties

8 AGN SED Sanders, D.E., & Mirabel, I.E., 1996, ARA&A, 34, 749

9 Other wavelengths u Hot (10 3 K) dust seen in IR, modeled following AGB envelopes u Likely associated with hot phase –Ferland et al. astro-ph/0311520 Mean Grain Temperature Mean Gas Temperature

10 Full spectrum of 1 micron emitter

11 UV emission from X-ray gas X-ray UV, FUV

12 UV emission from X-ray gas u The O VII 1693 to 22.1 intensity ratio for BLR conditions u A sequence of such lines should (& may) be present –C V 2349 –N VI 1982 –O VII 1698 –Ne IX 1289 –Mg XI 1011

13 Conclusions u Spectroscopy is subject to selection effects, u Inhomogeneities introduce selection effects, u But these can be quantified –And go over to simple limits (fractals, self- organized criticality) u Consider the full spectrum produced by a component


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