Jet Variability Under the Microscope

1. Jet Variability Under the Microscope Eric Perlman - Florida Institute of Technology Collaborators: Mihai Cara, Sayali Avachat, Raymond Simons, Matt Bourque (FIT) Markos Georganopoulos (UMBC) Cade Adams (Georgia and Clemson) Daniel E. Harris (Harvard/Smithsonian CfA) Eric Clausen-Brown, Maxim Lyutikov (Purdue) Juan P. Madrid (Swinburne) Lukasz Stawarz (Jagiellonian University and JAXA) C. C. “Teddy” Cheung (NRL) Bill Sparks, John Biretta (STScI) The HESS, VERITAS and MAGIC TeV Observatory teams

2. Outline • Introduction: What do we know about jets? Basic Properties Radiation Mechanisms Relativistic Effects Variability (and why it is important) • Putting Variability Under the Microscope M87: the first RESOLVED variable region! Multiwavelength lightcurves The nucleus & HST-1: two variability modes Spectral and polarimetric variations • Conclusions Timescales and Particle Acceleration Jet Structure and other physics

3. Examples of Relativistic Jets Stellar Mass NS/BH Binaries: Double star system, neutron star or black hole + main sequence or giant star. Matter accreting from normal star. Flow speeds 0.25-0.95 c. Centers of Galaxies: Matter accreting from interstellar medium onto supermassive black hole. Flow speeds 0.9-0.99c+. Part of “active galactic nucleus” phenomenon. Gamma-Ray Burst: Death throes of a very massive star (>30-50 solar masses); asymmetric explosion drives a relativistic outflow. Flow speeds >0.99c but probably very mass loaded.

4. The Unified AGN Model Supermassive (107-1010 M) black hole. M = 108MRG~2 AU Accretion disk – thermal UV/X-ray lines from highly ionized atoms (R~3-100 RG) High velocity (>1000 km/s) broad-line clouds (R~103-4 RG) Dusty torus, which orbits in/near plane of accretion disk (R~104-5 RG) Lower velocity (few hundred km/s) narrow-line clouds (R~105-7 RG) Relativistic jet (Γ ~ 5-30) – may be collimated on ~50 RG scales, can extend for many kiloparsecs Observed properties vary with viewing angle Urry & Padovani 1995

5. Radiation Processes in Jets e- B Jet “beam” Inverse-Compton – scattering interaction between photon and a relativistic particle that results in a higher-energy photon. Synchrotron radiation emitted by relativistic particles in magnetic field Radiation from jets emitted by two processes: synchrotron and inverse-Compton. For inverse-Compton, the ‘scattered’ photon can be either from within the jet (often called synchrotron self-Compton) or some external source (e.g, the cosmic microwave background or emission line regions).

6. Biretta et al. 1999

7. Superluminal motion in quasar jets: an optical illusion Positions of knot when two pictures were taken, one year apart. Speed of knot (close to the speed of light) Light paths: B Small angle: the knot’s motion is mostly along the line of sight. A Not drawn to scale! Light path B is shorter than path A. If the knot’s speed is close to the speed of light, B is almost a light-year shorter than A. This “head start” makes the light arrive sooner than expected, giving the appearance that the knot is moving faster than light. (Nothing actually needs to move that fast for the knot to appear to move that fast.)

8. θ Relativistic Effects v=βc Γ=(1-β2)-½ δ=[Γ(1 - β cos θ)]-1 Time dilation: tapp= δ-1t Blueshifting :νapp= δν “Superluminal” Motion: vapp= v sin θ/(1 - βcosθ) Curves for = 3,5,8,12 Geometrical distortion: dΩ=dΩ’/δ2 Beaming for Synchrotronand SSC: Lobs=δ4 Lem For EC: Lobs=δ6Lem/γ2

9. Variability in Jets • Jet emission is highly variable. • Usually in blazars -- jet seen at very small angles (our line of sight is nearly along beaming axis) Relativistic speed confirmed by apparent Superluminal motion • Typical example: 3C 454.3 (at right) Variable on all timescales Slow variability & Large flares Also intraday variability Broadband spectrum can change drastically. • However… in most sources the varying region is unresolved. Physics not well constrained.

10. Variability and Source Size Spherical blob in comoving frame Source size from direct observations: rb=r´b Γ Source size from temporal variability: Doppler Factor Variability timescale implies maximum emission region size scale

11. Variability and Source Location G 1/G x Variability timescale implies engine size scale, comoving size scale factor Γ larger and emission location Γ2 larger than values inferred for stationary region Rapid variability by energizing regions within the Doppler cone

12. Chandra and HST

14. The Best-Studied Jet: M87 Images at right show the M87 jet at radio (bottom) and then in optical and UV (wavelength decreasing as you go up) Jet is knottier at higher photon energies Narrowing trend continues all the way up through X-rays 140 nm 230 nm 340 nm 2 cm Sparks, Biretta & Macchetto 1996

15. http://www.aoc.nrao.edu/ ~fowen/M87_layout.html

16. The M87 Jet (Marshall et al. 2002)

17. Optical Polarization of the M87 Jet Perlman et al. 1999 • Jet can be very highly polarized -- up to 60%+ in spots • Natural for synchrotron emission • Position angle of polarization (pictured vectors, rotated 90 degrees to show B) direction of magnetic field in emitting region • High & low polarization regions correlated with the location of knots • Often different in different bands • Can give clues to some very interesting physics…

18. Perlman et al. 1999

19. Perlman & Wilson 2005

20. Madrid 2009

21. Variability in the M87 Jet? Yes – dramatic variability! Giant flare in HST-1 Seen in all bands Smaller variability in other regions Only opt/X-ray jet where varying region is isolated MUCH BETTER CONSTRAINTS ON PHYSICS Superluminal motion as well 6c in HST-1, decreasing to c at ~12” out Variability of opt spectrum & polarization will give clues to physics: Compression/shock/expansion Acceleration/cooling timescales Tracing motion of components Harris et al. 2009

22. A Tale of two components Two different regions, two different variability behaviors: • HST-1: Giant Flare Flux increased by >100X Dominant timescale ~1 year • Nucleus: Numerous smaller flares Largest variation is a factor 4 Timescales ~few months or less Not resolved

23. Optical Lightcurves Optical and X-ray Variability Closely track one another Madrid 2009

24. Where are the Flaring Regions? • Nucleus: innermost few parsecs or smaller Very smooth structure, no obvious “flaring” or motions • HST-1: 0.86” (62 parsecs projected) from nucleus Knotty structure, superluminal motions

25. Analyzing the lightcurve • Can look for many things, e.g., Does one band flare first? If so, is there a consistent lag? Does one band increase faster or slower? • However, the lightcurve contains interesting hints: X-rays increase, decrease more rapidly to main peak X-rays also contain more month-timescale variability Harris et al. 2009

26. Analyzing the lightcurve • Quantifying properties in the X-rays. Use first derivative – as fractional change per year This is 1/region size for light- travel time Constrain varying region to <45 light-days from largest derivative. Harris et al. 2009

27. Quasi-periodic behavior in HST-1 • Found during the increasing phase of the flare • No single period, but an increase and decrease was observed every 6-10 months • “Impulsive” acceleration? Harris et al. 2009

28. Close-up on the flare • Optical, X-ray behavior similar • Behavior not monolithic • First derivative changes sign ~2005.5 • Secondary flare in 2006 Harris et al. 2009

29. Velocity Structure of HST-1 • Four moving components, motions tracked for over three years • One knot – C – split in 2005, coinciding with main flare. Also location of flux peak Birth of a new component in jet during flare.

30. Velocity Structure of HST-1 • Four moving components, motions tracked for over three years • One knot – C – split in 2005, coinciding with main flare. Also location of flux peak Birth of a new component in jet during flare. • Fastest components moved at 4.3 c

31. Gamma-ray flaring Abramowski et al. 2012

32. Polarization, Spectral Variability in HST-1 • Strong correlation between flux, polarization • Very little change in PA • Only one region involved in variability -- fully resolved Perlman et al. 2011

33. Polarization & Spectral Behavior • Strong correlation of polarization with flux magnetic field involved in particle accel • Complicated relationship between flux and spectral index Epochs 4-9 – “hard lagging” Epochs 13-17 – “soft lagging” • The latter is more common; implies shorter acceleration timescales than cooling timescales. • The latter normally requires the opposite relationship … but X-ray is also synchrotron • Possibility: most energy losses are actually in inverse-Comptonizing external photons near Klein-Nishina limit. Perlman et al. 2011

34. Close-up on the flare • Optical, X-ray behavior similar • Behavior not monolithic • First derivative changes sign ~2005.5 • Secondary flare in 2006 • Switch in fpy, in both X-ray & optical, corresponded with switch in direction of “looping” Harris et al. 2009

35. Shocks Compression ratio k

36. Behavior of Polarization in shock • If shock is localized, planar and perpendicular to jet (as pictured in last plot), MHD predicts a polarization • Our data require a jet bulk Lorentz factor of ~4-5 – consistent with speeds observed in VLBI observations. • Beaming factor can range over a wider range of values Perlman et al. 2011

37. A Tale of two components Two different regions, two different variability behaviors: • HST-1: Giant Flare Flux increased by >100X Dominant timescale ~1 year • Nucleus: Numerous smaller flares Largest variation is a factor 4 Timescales ~few months or less Not resolved Harris et al. 2009

38. Analyzing the lightcurve • Larger values of fpy than HST-1 • Largest fpy~20 => region is smaller than ~20 light-days. • Goes along with faster variability in general Harris et al. 2009

39. Patterns in the nuclear variability? • None seen • But … are we sampling often enough to see them? Maybe not, given small region size. Harris et al. 2009

40. Gamma-ray flaring Abramowski et al. 2012

41. Polarization and Spectral Variability in M87 Jet: Nucleus • Faster Variability • Complex polarization behavior • No obvious correlation between flux, polarization … unless you look more carefully • No evidence for spectral index variability Perlman et al. 2011

42. Polarization behavior • “Loop” in I-P plane – very different from HST-1! • No correlation with EVPA (varies all over the place) or spectral index (near constant) Perlman et al. 2011

43. Perlman et al. 2011 Dynamics and helical jets • Helical jets introduce additional complexity into your jet model • Can introduce a helical distortion • Or velocity variations Not shown: Mag. Pitch angle ψ Shock compression (ratio k)

44. Nuclear X-ray also synchrotron but more complicated • No correlation with EVPA (varies all over the place) or spectral index (near constant) • Consistent with either: • a helical distortion • Shock compression in a helical jet • We favor the latter because of the morphology, known helical morphology of nuclear B field. • Neither one is 100% satisfactory for reproducing EVPA behavior. Perlman et al. 2011

45. Marshall et al. 2010

48. Conclusions • Variability can reveal unique information about jets • We have for the first time isolated a variable region in a jet • HST-1’s Variability was similar to that observed in blazars X-ray variability was fastest … but spectral behavior complex Quasi-periodic acceleration during increasing phase Complex flare shape Polarization characteristics consistent with a simple shock • Nucleus was also variable Faster variability timescale, smaller region size No pattern to variability (but are we observing often enough?) “Loop” in (I,P) plane suggests helical morphology to varying region.