AGN Diagnostic Diagrams

Image: Artist rendition of an accretion disk surrounding a supermassive black hole. Credits: NASA/Dana Berry/ SkyWorks Digital.

Introduction

Active Galactic Nuclei (AGN) are challenging to identify as any one indicator of black hole accretion suffers from limitations. In general, a more complete census of AGN can only be achieved with a multiwavelength analysis. This website focuses on optical and infrared diagnostics, but will be expanded to consider other wavebands such as hard X-rays and radio emission. Note that X-ray AGN classifications are compared directly to optical AGN diagnostics at 0.3<z<1 and 0.3<z<0.8 in Juneau et al. (2011) and Yan et al. (2011), respectively. There are many other references comparing various AGN tracers (e.g., Hickox et al 2009).


You can read an overview of the general methods below, and use the left-hand menu to navigate to pages providing equations and recipes collected from the literature.

AGN Optical Line Diagnostics

This website started with a focus on optical nebular line diagnostics, which are designed to identify ionized gas surrounding active supermassive black holes. The general idea is that the relative strengths of various emission lines are dictated by a combination of ionizing spectrum characteristics (hardness, intensity, etc.), and gas properties (gas-phase metallicity, density, temperature, etc.).

We include the Mass-Excitation (MEx) diagram (Juneau et al. 2011; 2014), Color-Excitation diagram (Yan et al. 2011), and TBT diagram (Trouille, Barger & Tremonti 2011). Some of the traditional BPT diagrams (Baldwin, Phillips, and Terlevich 1981, Veilleux & Osterbrock 1987) and modern revisions (e.g., Kewley et al. 2006, Stasinska et al. 2006, Kewley et al. 2013a,b) are included, as well as other alternative diagrams such as the Blue diagram (Lamareille 2010, Lamareille et al. 2004) and the DEW diagram (Stasinska et al. 2006). The diagrams are introduced in their respective section (see the list in the website menu) and IDL code is provided to compute AGN probabilities from the MEx or CEx diagnostic diagrams.

Note: Click here for a high-resolution version of Juneau et al. (2011) or for figures suitable for powerpoint slides.


AGN Mid-IR Diagnostics

In the mid-infrared regime, one can use either thermal emission or access a different set of emission lines. In the former case, the main source of emission is heated dust grains, and diagnostics aim to differentiate between dust heated by young stars and dust predominantly heated by an active supermassive black hole. In the latter, emission lines are also tracing ionized gas spanning a range of spectral and gas conditions. Relative to rest-frame UV and optical signatures, the benefit of the IR is that emitted photons are much less subject to dust obscuration and therefore have a longer mean free path and can more readily be detected even if the AGN is buried in significant amounts of dusty material. Various example diagnostics are listed in the website menu.


AGN Optical Color Diagnostics

Optical photometry can be used to identify the presence of bright point sources originating from a direct view of the AGN accretion disk (in Type 1 AGNs and QSOs) and/or to probe the resulting colors from a dominant AGN contribution, which tend to be bluer than stellar light (especially when the host galaxies have older/redder stellar populations). The latter includes traditional color cuts as well as machine-learning applications.


AGN Radio Diagnostics

A fraction of AGN also include a radio jet in addition to the accretion disk and torus components. Radio-loud galaxies may be the most extreme examples, but even radio-quiet galaxies can have a small (sometimes unresolved) radio jet component. Radio AGNs are identified either via a radio power criterion or a radio excess relative to another regime of emission (e.g., radio-to-infrared excess).


AGN X-ray Diagnostics

X-rays originate in a high energy plasma surrounding the accretion disk. The main mechanism is that UV photons emitted from the accretion disk gain energy by interacting with the fast moving electrons from the plasma via inverse Compton scattering. As a result, there is a copious amount of hard-energy X-ray photons surpassing what is produced by other sources in the host galaxy (such as X-ray binaries). Thus, the most common diagnostic is a simple X-ray luminosity threshold. However, it can also be advantageous to use additional information such as X-ray hardness (relative amounts of hard to soft X-ray photons), and X-ray excess relative to another waveband such as optical or infrared.

Bibliography

Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5 (on ADS)

Cid Fernandes, R.; Stasinska, G.; Mateus, A. & Vale Asari, N. 2011, MNRAS, 413, 1687 (on ADS)

Del Moro, A. et al 2013, A&A, 549, 59 (on ADS)

Hickox, R. et al 2009, ApJ, 696, 891 (on ADS)

Juneau, S., Dickinson, M., Alexander, D. M. & Salim, S. 2011, ApJ, 736, 104 (on ADS)

Juneau, S., Bournaud, F., Charlot, S., Daddi, E. et al, 2014, ApJ, 788, 88 (on ADS)

Kewley, L. J., Groves, B., Kauffmann, G., & Heckman, T. 2006, MNRAS, 372, 961 (on ADS)

Lamareille, F. 2010, A&A, 509, A53 (on ADS)

Lamareille, F., Mouhcine, M., Contini, T., Lewis, I., & Maddox,S. 2004, MNRAS, 350, 396 (on ADS)

Stasinska, G., Cid Fernandes, R., Mateus, A., Sodré, L., & Asari, N. V. 2006, MNRAS, 371, 972 (on ADS)

Smolcic, V. et al. 2006, MNRAS, 371, 121 (on ADS)

Smolcic, V. et al. 2008, ApJS, 177, 14 (on ADS)

Stern, D., et al. 2005, ApJ, 631, 163 (on ADS)

Teimoorinia, H, & Ellison, S, 2014, MNRAS 439, 3526 (on ADS)

Trouille, L., Barger, A., & Tremonti, C. A. 2011, ApJ, 742, 46 (on ADS)

Veilleux & Osterbrock 1987, ApJS, 63, 295 (on ADS)

Vogt, F. P. A., Dopita, M. A., Kewley, L. J. et al 2014, arXiv 1406.5186 (on ADS)

Yan, R., Ho, L. C., Newman et al. 2011, ApJ, 728, 38 (on ADS)

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