1. Statistical analysis of model-fitted inner-jets of the MOJAVE blazars Xiang Liu, Ligong Mi, et al. Xinjiang Astronomical Observatory (Former Urumqi Observatory), CAS In JD6 “Connection between radio and high energy emission in AGNs”, IAU GA

3. Jet model Marscher et al. 2008

4. Two-zone inner-jet models We propose the two-zone inner-jet models Zone-1: Poloidal beam Zone-2: Envelop fluid Helical jet Beam jet Two-zone model 1 two-zone model 2

5. The two-fluid model 1, the outflow consists of an e−p plasma (the jet), moving at mildly relativistic speed 2, An e± plasma (the beam) moving at highly relativistic speed 3, the magnetic field lines are parallel to the flow in the beam and the mixing layer, and are toroidal in the jet Roland et al. 2009, see the two-zone, spine-sheath models (Karouzos talk in this morning)‏

6. The model-fit to the MOJAVE blazars cores The sample defined by: 1, blazars with more than 10 years VLBA monitoring, 2, observed at >=15 epochs, good distribution in time. It consists of 104 sources, inclunding 77 quasars and 27 BL Lacs, in which 82 are Fermi LAT detected, 22 non- detected, 9 are also TeV sources. This research has made use of data from the MOJAVE database that is maintained by the MOJAVE team (Lister et al., 2009, AJ, 137, 3718)‏ http://www.physics.purdue.edu/MOJAVE/

7. Example: IBL 0716+714 Mojave image at 15 GHz Model-fitted inner-jet PA vs restoring beam

8. The model-fit method and result Almost all blazars of our sample are core-dominated, can use an elliptical two-dimension Gaussian fit, also see Kovalev et al. (2005); Marti-Vidal et al. (2011, 2012) for more discussions. The model-fit gives peak flux density (per beam), PF, Position Angle of major axis, major axis and minor axis. We consider that the `core' in the 15 GHz VLBA image is the `inner-jet' rather than the true core. Therefore, the inner-jet can be modeled with an elliptic Gaussian component which its major axis is along with the inner-jet orientation or the inner-jet ridge-line on average, thus reflecting the inner-jet position angle. Major axis of the Gaussian can be as the inner-jet length scale (kovalev, et al. 2005).

9. Statistics of correlations +3 (11%)‏ -5 (19%)‏-13 (48%)‏ +4 (15%)‏ -3 (11%)‏ 27BL +12 (16%)‏ -13 (17%)‏-54 (70%)‏ +11 (14%)‏ -10 (13%)‏ 77Q +15 (14%)‏ -18 (17%)‏-67 (64%)‏ +15 (14%)‏ -13 (13%)‏ 104blazars PA & majPF & majPF & PANtype We define coefficient >0.4, with significance of <0.05, as a linear correlation.

10. Two-zone inner-jet models For beam component in zone-1, Only correlation between PF & maj is expected. Refered to the “zone-1” dominated Zone-1: Poloidal beam Zone-2: Envelop fluid Helical jet Beam jet Two-zone model 1 two-zone model 2 For helical component in zone-2, other correlations (PF&PA, PA&maj) may be expected, refered to the “zone- 2” dominated

11. 64% blazars in the sample have PF&maj negative correlation They could be dominated by the precession/ swing Ballistic jet in the zone-1: A geometric beaming effect, or Outbursts with precession/ swing

12. IBL 0716+714 This could be Explained with the helical non-ballistic jet in the zone-2 A ballistic precession/swing Beam emission Cannot explain This correlation Liu et al. 2012 Michgan data: Vari period 5.7 yr Fan et al. 2007 Positive correlation (PF & PA)‏

13. Ballistic jet Non-ballistic helical jet

14. The dPA (max dPA here) Is similar to that jet ridge-line width from CJF sample Karouzos et al. (2012), except in small dPA regiuon LAT detected peak at higher dPA than LAT non detected blazars, similar to Pushkarev et al.(2012) result, with different method. Quasars peak at smaller dPA?

15. This result is generally consistent with that the LAT detected are more variable blazars, see Lister et al. (2009), But the quasars show no significant different from BL Lacs in the distribution of variabilities in PF and maj. It has been suggested that Doppler factor is not the sole factor that determines whether a particular AGN is bright at γ-ray energies (Lister 2012)‏

16. Gamma-ray detection rate 6 (2,4)‏3 (1,2)‏09 (3,6)‏TeV 76%(69 %,93%)‏ 82%(73 %,100%)‏ 82%(81 %, 86%)‏ 79%(74%,93%)‏ Y/(Y+N)‏ 13 (12,1)‏3 (3,0)‏6 (5,1)‏22 (20,2)‏LAT-N 41(27,14 )‏ 14 (8,6)‏27 (21,6)‏82(56,26)‏LAT-Y Others (Q,BL)‏ “Zone-2 dominate” (Q,BL)‏ “Zone-1 dominate” (Q,BL)‏ Total (Q,BL)‏ Gamma ray

17. Mean / median value of long-term variations of parameters for different groups

18. No strong variability evolution in PF, maj and dPA with redshift. For quasars, there seems to be stronger variability around redshift 2.1 and a marginal hint of wiggling variability. For BL Lacs, because of less data and relatively low redshift, there is a marginal peak in variability around redshift 0.3. But these are marginal.

19. Summary The model-fit result of the `core‘s of 104 blazars from the MOJAVE monitoring data, suggests that Fermi LAT-detected blazars have a wider position angle changes of inner-jet than LAT non-detected blazars, and are preferentially associated with higher variable blazars. We propose a two-zone jet model to explain the correlations in the model-fitted parameters, that the blazars in our sample are predominated by the beam of the inner than the jet in the outer. Fermi GeV gamma-ray detection rate show equally similar fraction for the innermost jet (zone-1) dominated and the outer jet (zone-2) blazars. But importantly: TeV gamma-ray sources associate mostly with the outer part of inner-jet (zone-2).

20. Thank you For your attention!