Lessons from other wavelengths
A picture may be worth a thousand words, but a spectrum is worth a thousand pictures
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
A distribution of clouds u CIV 1549 emission line visibility vs cloud density and distance to continuum source
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 W (C IV) collisionally suppressed constant U
Collisionally excited lines Low Ionization Mg II Density => Flux => High Ionization O VI Density => Distance =>
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
AGN SED Sanders, D.E., & Mirabel, I.E., 1996, ARA&A, 34, 749
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/ Mean Grain Temperature Mean Gas Temperature
Full spectrum of 1 micron emitter
UV emission from X-ray gas X-ray UV, FUV
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
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