Long term multi-wavelength variability studies of the blazar PKS

Transcription

1 52nd Rencontres de Moriond 2017 Very High Energy Phenomena in the Universe Long term multi-wavelength variability studies of the blazar PKS Jill Chevalier D. Sanchez, P. Serpico, J-P. Lenain, G. Maurin

2 Centaurus A Active Galactic Nuclei

3 Nowadays challenges in AGN 1995: unification model from Urry & Padovani 1999: blazar sequence of Fossati Blazars Open questions: Links between the black hole, jet & accretion disk Acceleration & emission processes

4 Nowadays challenges in AGN Non-thermal spectrum with 2 broad bumps Low energy bump = synchrotron Still a lot of unknown in the high energy bump? Inverse Compton External Compton Photo-pion production Jill Chevalier Rencontres de Moriond - VHE session - March 2017

5 Leptonic or hadronic model? In many cases, leptonic and hadronic models can produce equally good fits to the SEDs

6 Variability in blazars Blazars are variable in all wavelengths and at all time scales: - flares minute scale - long term month/year scale BL Lacertae (Fermi) H.E.S.S. Variability is a key towards a better understanding of AGN ROTSE radio

7 Long term γ-ray monitoring of blazars 2008: Fermi-LAT 2004: H.E.S.S. 2005: MAGIC 2007: VERITAS More and more monitored VHE sources: - Mkn Mkn PG PG PKS

8 γ-ray light curves of PKS H.E.S.S. and Fermi-LAT long term light curves from the H.E.S.S. Collaboration paper arxiv: v1

9 Going further: The MWL dataset of PKS H.E.S.S. E > 200 GeV Fermi-LAT 0.1 < E < 300 GeV + 2 sub-bins X-ray 2 < E < 10 kev + 4 sub-bins SMARTS J, R, V & B bands

10 Variability profile F var (E) Fvar = normalised excess variance from Vaughan et al. (2003) F var = q S 2 2 err Strong variability with F var increasing through SED components

11 Variability profile F var (E) Fvar = normalised excess variance from Vaughan et al. (2003) F var = q S 2 2 err Strong variability with F var increasing through SED components Synchrotron Inverse Compton Same electron population?

12 Similar result in Mkn 421 ~2-3 years MWL light curves Ahnen et al. (2016) arxiv: MWL variability characterisation variability increases with the energy

13 Similar result in Mkn 421 Fermi-LAT

14 Cross-correlation Method: discrete correlation function (DCF) computation of the correlation for each time lag Maximum at t = 0 days DCF between Fermi-LAT and SMARTS (R) light curves Same electron population?

15 Cross-correlation Method: discrete correlation function (DCF) computation of the correlation for each time lag Maximum at t = 0 days DCF between Fermi-LAT and SMARTS (R) light curves Same electron population? Presence of two local maximum at t = ± 700 days Signature of periodic signal?

16 Periodicity in PKS ? Method: Lomb-Scargle Periodogram (LSP) tool to test the significance of a periodic signal (even in un-evenly spaced data) T Fermi = ± 10 days T SMARTS = ± 4.7 days

17 Periodicity in PKS ? Method: Lomb-Scargle Periodogram (LSP) tool to test the significance of a periodic signal (even in un-evenly spaced data) T Fermi = ± 10 days T SMARTS = ± 4.7 days

18 Other periodic signal in blazars OJ 287 (T~12 years) or Mkn 421 (T~400 days) PG T = 2.18 ± 0.08 years in optical and GeV light curves (arxiv: ) Why? 1. Supermassive binary BH system 2. Jet precession 3.

19 Log-normal behaviour Flux log Flux The log of the flux is described by a Gaussian Occurence per bin Occurence per bin log(φ) N(μ,σ) multiplicative processes Excess variance: XS = q S 2 2 err Φ (10 cm -2.s -1 ) log Φ (cm -2.s -1 ) from arxiv: v1

20 Log-normal behaviour Flux log Flux The log of the flux is described by a Gaussian Occurence per bin Occurence per bin log(φ) N(μ,σ) multiplicative processes Excess variance: XS = q S 2 2 err Φ (10 cm -2.s -1 ) log Φ (cm -2.s -1 ) from arxiv: v1 Public Optical and X-ray results New Probe of the accretion process?

21 Log-normal behaviour history First time seen in X-ray binaries and Seyfert galaxies (AGN) and related to the accretion disk (Uttley & McHardy 2001, McHardy 2008) propagation of fluctuations in the disk? (accretion rate?) Natural outcome from power law noise variability PSD ω -β Giebels & Degrange 2009 Note : this variability can not originates from the emission mechanism. No mechanism in synchrotron or IC to produce this BL Lacertae

22 Towards a variability modelling Can we model the variability observed with a simple model?

23 Towards a variability modelling with the SSC One zone time dependent SSC modelling with the electrons density described as a PowerLaw with exponential cut off Q(E,t)=N 0 E exp E cut(t) Steady state of PKS Electrons: - normalisation - index - cut off energy N 0 = 0.01 α = 2.3 log(γ cut ) = 5.3 Zone: - magnetic field - size - doppler factor B = 0.1 G R = 2 x cm δ = 35

24 Why γ cut (t)? Low impact on the electrons producing the optical and GeV photons High impact on the electrons production the X-ray and TeV photons

25 Evolution of log γ cut (t) Evolution following a power law noise PSD ω -β stochastic process method of Timmer & Koenig (1995) 2 parameters: - power index β - time series variance σ the simulated time series is re-normalisazed to the mean value with variance σ Which [β,σ] configuration?

26 Preliminary results Best configuration: Time = 2.2 years log(γ cut ) = 5.3 β = 1 σ = 20 % of log(γ cut ) Flux optic X-ray GeV TeV Time (days)

27 Preliminary results Best configuration: Time = 2.2 years log(γ cut ) = 5.3 β = 1 σ = 20 % of log(γ cut ) Flux optic X-ray GeV TeV Time (days)

28 Outlook Long term multi-wavelength variability studies of the blazar PKS Similar behaviour in the optical-gev and Xray-TeV bands with F var (E) Perfect optical-gev correlation Hints towards a leptonic SSC emission model days periodicity + lognormal behaviour binary SMBH system? imprint of the accretion disk?

29 Outlook Long term multi-wavelength variability studies of the blazar PKS Similar behaviour in the optical-gev and Xray-TeV bands with F var (E) Perfect optical-gev correlation Hints towards a leptonic SSC emission model days periodicity + lognormal behaviour binary SMBH system? imprint of the accretion disk? Long term (~10 years) SSC modelling ongoing Application of the variability tests Periodicity tests: can we reproduce a similar periodic behaviour? (injection, doppler factor ) More time-dependent parameters?

30