Long-term variability behaviour of AGN

1. Long-term variability behaviour of AGN The X Finnish-Russian Radioastronomy Symposium Orilampi, 1-5 September, 2008 Talvikki Hovatta Metsähovi Radio Observatory In collaboration with: M. Tornikoski, A. Lähteenmäki, E. Nieppola, I. Torniainen, M. Lainela, H.J. Lehto, E. Valtaoja, M.F. Aller, H.D. Aller

2. Outline • Introduction • Sample • Variability timescales • Different methods • Flare characteristics • Conclusions

3. Introduction • A sample of ~100 AGN has been monitored at Metsähovi Radio Observatory for nearly 30 years • The large dataset enables studies of long-term behaviour • Aim is to better understand the observed properties, radiation mechanisms and physics of the sources

4. Sample data • 22, 37 and 87 GHz data from Metsähovi • 4.8, 8 and 14.5 GHz from the University of Michigan (UMRAO) • 90 and 230 GHz data from the SEST • 90, 150, and 230 GHz data from the literature

5. Sample sources • 80 sources for timescale analysis • At least 10 years of monitoring data at 22 or 37 GHz • Bright sources with a flux density of at least 1 Jy in the active state • 55 sources for flare analysis • At least one well-monitored distinguishable flare at 2 of the frequencies (22, 37 or 90 GHz being one of the frequencies) • Altogether 90 sources • HPQs, LPQs, BLOs and Radio Galaxies

6. Timescale analyses: methods • Structure function (SF) • Discrete autocorrelation function (DCF) • Lomb-Scargle periodogram • Wavelets • Only 22, 37 and 90 GHz • Morelet wavelet

7. Timescale analyses: results • Large flares are seen on average every 4 to 6 years • Average at 37 GHz is 4.2 years (DCF, wavelets) • Redshift-corrected timescales are shorter • 2 years for quasars • 3-4 years for BL Lacertae objects (BLOs) -> shocks could be produced less frequently in BLOs • Rise and decay times of flares are between 1 to 2 years

8. Timescale analyses: results • No strict periodicities were found • Episodes of quasi-periodic behaviour are common • Multiple timescales are common • Timescales change, get weaker in power or disappear over long time periods

9. Timescale analyses: results • DCF and wavelets give similar results but wavelets also give information on the continuity of the timescales • Lomb-Scargle periodogram easily produces spurious timescales • Hovatta et al. 2007 (A&A, 469, 899-912), Hovatta et al. 2008b (A&A, in Press)

10. Example: 4C 29.45 at 22GHz ~3.4 years Flux curve 3.49 years DCF

11. Example… SF 3.29 years LS-periodogram 1.21 years

12. Example… 1.7 years 3.4 years

13. Example: results • Same timescale of ~3.4 years is obtained with all the methods • Only with wavelets it is possible to see that it is present only in the latter half of the flux curve • Comparison of new SF analysis to Lainela & Valtaoja (1993) also showed the difference • L&V 1993, SF timescale >6.68 years

14. Flare characteristics • Sample of 55 sources with 159 flares • 4.8 – 230 GHz • Flare amplitudes (peak, relative) • Duration of flares • Variability indices • Testing of the shock model • Hovatta et al. 2008 (A&A, 485, 51-61), Nieppola et al. in preparation

15. Example 4years • Times between flares • On average 4 years • Rise / decay times • 1-2 years • Duration • Median 2.5y @ 22 & 37GHz • Range between 0.3-13.2y • Peak flux • Median 4.5Jy @22 & 37GHz • Range between 0.7-57 Jy Peak 4.4Jy Dur 2.5 y 0.95 years

16. Testing of the shock model α=-0.24 α<-0.5 α=0.41 • Otherwise good general • correspondence with the • shock model

17. Conclusions • Variability behaviour is complex • Episodes of quasi-periodic behaviour are common • Flares are seen on average every 4 years • Median duration is 2.5 years => Long-term monitoring is essential!