Coronal seismology, AIA/HMI and image processing

(-: Best wishes :-)

JF Hochedez, E Robbrecht, O Podladchikova, A Zhukov, D Berghmans

SIDC @ ROBSolar Influences Data analysis Center

Royal Observatory of Belgium

AIA

CoronalSeismology

ImageProcessing

Mandate of this presentation

EUV imaging observations and seismology(1) in [simple] flux tube magnetic structures

Fast magneto-sonic modes Slow

Magneto-sonic (sausage) modeKink Sausage

StandingTRACE 1MK 1999

(Aschwanden et al., Nakariakov et al.)

AIA 2009?SUMER 6MK 2002

(Kliem et al.,Wang et al.)

PropagatingTRACE 20MK 2005

(Verwichte et al)AIA 2009?

EIT 1MK 1998

Deforest & Gurman

Berghmans & Clette 99, TRACE...

Optical Flow

Motion & brightness changetracking

Loop recognition andCactus-like approach•x-t diagrams,•Hough transform,•clustering

EUV imaging observations and seismology(2) in [other] coronal structures

Global EIT wavesEIT

Thompson et al 1998

Prominence oscillationsnot discussed in this talk

but not forgotten

Oscillations and waves during eruptions (CME or flares)

The future? But challenging!

Sympathetic flares

EIT wave detector

Flare detector and Podladchikova et al (submitted)

Presentation sections

1. When Optical Flow will detect fast modes in flux tubes

2. Loop recognition and Hough transform applied to slow waves

3. What EIT waves can tell us about the corona

4. [Prospective] sympathetic flares. How do they communicate?

5. Conclusions

Optical Flow

& its application to fast modes

Remaining problems with kink oscillations

• Damping– Test competing explanations

• phase mixing• resonant absorption (Goosens et al 2002)• leakage at footpoints, others…

– Too many parameters• stratification (estimated by Andries et al 2005)• Curvature• variable cross-section

More statistics needed

• Exciter(s)– Their nature? From below? From side?

• Why so few ?– Damping or lack of exciters?

Hopes from AIA-HMI (1/2)• 8 bandpasses

– Longitudinal density profile (DEM tools)– Heating profile

• Spatial resolution– Radial density profiles: concentric shells, threads?

• 0.6”probably still too low– Overtones (Verwichte et al 2004)– 3D geometry with Secchi

• Loop length• vertical vs swaying (Wang et Solanki 2004), etc.

• Full Sun FOV– 2 pressure scale heights

• long loops with good SNR– With temporal coverage: statistics

Hopes from AIA-HMI (2/2)

• 2s Cadence– time aliasing repressed– SNR Time rebinning– exposure time ~0.1s

• Less kinetic blurring• Stroboscopy

– Observe fast sausage waves, fast sausage oscillations, fast propagating kink waves!

• Effective area (44x TRACE@171, 61x @194)– See smaller disturbances.

• Presence of HMI– Independent estimate of B (cf. too many parameters)

• Compatible with seismology? (NLFF and dynamics)

AIA trade-off TBD

VELOCIRAPTOR

VELOCIty & bRightness vAriations maPs construcTOR

Quantify motion together with intrinsic brightness variation

in EIT image sequences

Gissot & Hochedez, 2006

Inputs & outputsVelocity

field

Image In(x,y)

Image In+1(x,y)

BrightnessVariation

field

1. Similarity fieldbetweenIn(x,y) (warped)and In+1(x,y)

2. Local “texture”3. Residuals

e.g. EIT “CME Watch”

Hochedez & Gissot

Differential rotation recovered from a couple of EIT images

(No BV estimation)

BV map of the May 12, 1997 event

Velocity map of the May 12, 1997 event

(No BV estimation)

14 July 1998 12:50:16

Differenced image

Velocity field

Presence of texture in at least one direction (zoom)

Average displacement ~0.2 pixel

→ LCT not appropriate (a posteriori justification)

Velocity field produced by Velociraptor

Question: What are the anticipated artifacts for AIA?

OF & fast magneto-sonic waves:Conclusions and outlook

• Velociraptor can measure sausage and kink waves– Precisely, all along the loops, systematically, Outliers? – Challenging development – Being fully calibrated– 2 main problems understood and being corrected:

• Strong BV fictive motion• Some spurious sliding remains along loops

• Post-processing of the fields needed in order to identify waves autonomously (1D wavelets?)

• AIA + OF great prospect– Sausage modes by EUV imaging?– Flows from steady reconnections?– Mode coupling?

Slow waves

Good overall understandingbut …

• Wave or plasma motion? (no Doppler measurements)• Sound speed if pattern seen in several BPs• cf. Robbrecht et al. 2001 EIT vs TRACE

• Klimchuk et al 2004:– Their study validates classical thermal conduction damping

– But “TRACE loops are inconsistent with static equilibrium and steady flow”

– “Observed damping times of slow mode oscillations might be a lower limit to effective damping times, which can only be corrected if the cooling time is known from multi-filter data.”

• Seismology is complementary to DEM

Useful image processingfor slow waves (1)

• Loop extraction (ridge detection)

Useful image processingfor slow waves (2)

• Analysis of X-T diagrams– Hough Transform– Clustering

– Cf “CACTUS” applied to [faint] CME detection • in LASCO C2 & C3

15h18 15h54 17h06

11 November 2003

Computer Aided CME Tracking -CACTus

tr

t0Δt

EIT waves

EIT waves for coronal seismology• EIT waves: bright fronts propagating from eruption sites

observed in EUV (SOHO/EIT, TRACE, CORONAS-F/SPIRIT, 195 Å, 171 Å, 284 Å bandpasses).

• Sometimes EIT waves propagate nearly isotropically and often – globally.

• EIT wave speeds are usually about 150–400 km/s, typically around 250 km/s.

• Association with chromospheric Moreton waves, waves in He I and waves in SXR?

If EIT waves are fast magnetosonic waves…

Fast magnetosonic wave speed around 250 km/s means ~ 1 or > 1 in the “quiet Sun” corona

Force-free approximation is not valid!

* *

Wang (2000)Wu et al. (2001)

Courtesy A Zhukov 2006

a quantitative investigation

DIMMING & EIT wave extraction from EUV image

EIT wave radial and polar analysis

Brightness distribution (histogram) analysis

study of higher moments

Ring Analysis

radial velocities in the EIT wave

Angular-Ring Analysis

potential angular features

Podladchikova & Berghmans, 2005

Skewness & Kurtosis of PDF of difference image versus time

Simultaneous peaks+ dimming area criteria

→ EIT Waves!

Courtesy of Podladchikova & Berghmans

12 May 1997

Distances vs Time Integrated signals vs TimeCourtesy of Podladchikova & Berghmans

Both quadratic

Widthm3-m2

mmax

Results

1. Anisotropy even without obstacles. Correlation with associated dimming;

2. Dimming contiguous to wave front in all directions

3. Width of the front grows ~quadratically in time;

4. Integrated intensity of wave front grows during > 1/2 hrThe front intensity of linear magnetosonic waves would decrease

5. Integrated intensity of front balances integrated intensity of the dimmings (in early life of wave)

EIT wave = MHD wave?

Sympathetic flaring

Consecutive occurrence of flares in different AR

3225 flares registered with coordinates since 01/01/2004. Statistically complete series.

Result does not depend on time interval

Velocity [km/s]

Perturbation velocity from flare to flare “to set the fire”

Vchar ~ 110 km/s

t < 5h.

Conclusion

significant number of events where one flare

“sets fire” triggering another distant flare in a separate active region.

Propagation velocities for such perturbations around 110 km/s.

B2X flare detector

Just before the flare begins

At flare peak

log(scale)

½ log(μ

(sca

le))

Method: Wavelet spectrum (scale measure) analysis Hochedez et al ’02 Solspa2 Proc., Delouille et al SoPh ’05

Result: Small flares automatic detection

Relevance: Sympathetic flaring studies

Beauty spotterMethod: Extraction in scale space by Lipschitz coefficientHochedez et al 2002, Soho11 WS Proc., Hochedez et al 2003 Soho13 WS

Result: BPs, brightenings and Cosmic Ray Hits extracted

Relevance: Oscillations in point-like structures

Conclusions• The easy things about waves have been found.

Intelligent techniques can invigorate future research– Prospect for eruption precursors?

• Image processing = binding agent between theory and observation– Like an additional "telescope" for small scale physics

• improve resolution• separate different processes (mutually and from noise)• extract waves or reconnection events• part intensity from velocity variations

– Like a new "microscope" for large scale physics• Describe of important events• "in situ sensor“, identifying the nature of events• Uncover unexpected regularities

• For all these reasons, all detected waves should go in the SDO catalogs