1. Characterizing activity in AGN with X-ray variability Rick Edelson

2. Snippets of history Optical discovery & study came first –Seyfert classification based on emission lines –First observations only possible in optical –Still most accessible, well-studied waveband Flat IR thru X-ray SEDs, e.g. Elvis (1987) Mushotzky (2004, astro/ph0405144) review –Concl: most effective AGN surveys in X-rays –Essentially all “Radiating Supermassive Black Holes” (AGN) show detectable hard X-ray activity

3. X-rays are best activity indicator: 1) Reach deepest into heart of the AGN –Rapid var → emission from inner lt-hrs –Natural probe of central engine 2) No confusing emission components –Other local components and external sources generally don’t emit strongly in X-rays Other s provide info on orientation, etc. –Produced lt-days to lt-years out

4. Principal Component Analysis “PCA” first applied to AGN by Boroson & Green (1992, ApJS, 80,109) –Optical data on 92 opt/UV-selected quasars –“Principal Eigenvector”: strong correlation of H  width and Fe II strength, other line params –Secondary strongly correlated with luminosity Principal eigenvector linked to X-ray slope –Boller, Brandt & Fink (1996, A&A, 305, 53) –X-ray softness correlated with H  width

5. Boller et al. (1996) correlation of H  FWHM and X-ray 

6. X-ray variability in Radiating Supermassive Black Holes Non-statistical indications of “extreme” variability in X-ray soft sources –IRS 13224: Boller et al. (1997, MN, 289, 393) –Akn 564: Edelson et al. (2002, ApJ, 568, 610) Statistical link w/X-ray var. amplitude (  xs ) –Turner et al. (1999, ApJ, 524, 667) and O’Neill et al. (2005, MNRAS, 358, 1405) Correlated “excess variance” w/ various properties for ~day-long ASCA light curves Found corr. w/ luminosity, optical params.

7. 35 days of X-ray coverage of Akn 564. Note strong X-ray variability; UV/optical varied 15% peak-peak in this period.

8. Sixteen single-orbit light curves (1 point on previous graph) in which Akn 564 varies by factor of 2 within 3000 sec.

9. Why X-ray Varibility Classification? AGN “stick out” the most in the X-rays X-rays give best access to nuclear region –Bulk of lower-energy from lt-weeks–years out –Optical emission lines formed lt-days out –X-rays come from inner lt-hours Variability indicates activity time/size scale Test this by correlating X-ray variability with traditional eigenvectors of activity

10. XMM and X-ray variability Rapid X-ray variability is a powerful tracer of activity in Radiating SMBHs XMM provides best opportunity to exploit it –LEO light curves (ASCA, Swift) are interrupted this destroys key info on 3-10 ks timescale –XMM can detect var. on <100 sec timescales –Chandra also uninterrupted, but lower sens. Sensitive, uninterrupted XMM light curves ideal probes of critical short timescales

11. XMM Variability Study w/ Simon Vaughan, Ken Pounds XMM Variability Sample –29 Sy1s w/ >30 ks obs, good bkgd, opt. data Measured Excess Variance (  xs ) –Measured 4 ks time scale: shortest ever –Errors on individual estimate of order unity –Averaged multiple (10-100) estimates to beat down errors –Confirmed that  xs stable in different periods

12. XMM light curves of sources w/ a range of variability levels. Note the tabulated quantity is F var = sqrt(  xs 2 ). F var = 41% F var = 19%F var = 11% F var < 1.7% F var = 22%

13. Variability Study Results Used ASURV to correlate 4 parameters: 1)X-ray excess variance (  xs ) 2)X-ray slope (  ) 3)H  FWHM 4)Luminosity (0.2-10 keV) Strongest correlations involved H  –  xs vs. H  FWHM (p < 0.01%) –  vs. H  FWHM (p = 0.26%) –  xs vs. L x weaker than expected (p = 1.6%)

14. Multi-parameter correlations. The strongest correlations are shown on the left. p < 0.01% p = 22%p = 6.7% p = 0.26% p = 1.6%p = 0.52%

15. Implications Short time scale X-ray variability better correlated w/ H  FWHM than luminosity X-ray variability most likely linked to mass of supermassive black hole → H  FWHM is a better mass indicator than luminosity → Efficiency is not constant Improved X-ray, optical data; censored PCA methods key to further progress

16. State of X-ray Astronomy Right now lots of X-ray satellites: XMM, Chandra, RXTE, Suzuki & Swift Con-X, XEUS mega-missions planned for the 2020s –Doubtful they will proceed fully as hoped No missions are planned for the interim We will lose the ability to see in the X-rays starting in about 10 years This would be a disaster for AGN studies

17. Conclusions Rapid X-ray variability most strongly correlated with H  FWHM (an indicator of SMBH mass) X-rays are allowing the deepest probes of the central environment Access to the X-rays will be lost in next ~10 years unless we act quickly