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Coronal seismology, AIA/HMI and image processing (-: Best wishes :-). JF Hochedez, E Robbrecht, O Podladchikova, A Zhukov, D Berghmans SIDC @ ROB Solar Influences Data analysis Center Royal Observatory of Belgium. Mandate of this presentation. AIA. Coronal Seismology. Image Processing.
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Coronal seismology, AIA/HMI and image processing(-: Best wishes :-) JF Hochedez, E Robbrecht, O Podladchikova, A Zhukov, D Berghmans SIDC @ ROB Solar Influences Data analysis Center Royal Observatory of Belgium
Mandate of this presentation AIA Coronal Seismology Image Processing
EUV imaging observations and seismology(1) in [simple] flux tube magnetic structures 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 EIT wave detector Flare detector and Podladchikova et al (submitted)
Presentation sections • When Optical Flow will detect fast modes in flux tubes • Loop recognition and Hough transform applied to slow waves • What EIT waves can tell us about the corona • [Prospective] sympathetic flares. How do they communicate? • 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
VELOCIRAPTORVELOCIty & bRightness vAriations maPs construcTOR Gissot & Hochedez, 2006 Quantify motiontogether withintrinsic brightness variationin EIT image sequences
Hochedez & Gissot Inputs& outputs Velocity field • Similarity fieldbetweenIn(x,y) (warped)and In+1(x,y) • Local “texture” • Residuals Image In(x,y) e.g. EIT “CME Watch” Image In+1(x,y) Brightness Variation field
Differential rotation recovered from a couple of EIT images (No BV estimation)
Velocity field produced by Velociraptor Average displacement ~0.2 pixel → LCT not appropriate (a posteriori justification)
OF & fast magneto-sonic waves:Conclusions and outlook • Velociraptor can measuresausage 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?
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 Good overall understandingbut …
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
Computer Aided CME Tracking -CACTus 11 November2003 15h18 15h54 17h06
r t Δt t0
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?
* * Wang (2000) Wu et al. (2001) Fast magnetosonic wave speed around 250 km/s means b ~ 1 or b > 1 in the “quiet Sun” corona Force-free approximation is not valid! If EIT waves are fast magnetosonic waves… Courtesy A Zhukov 2006
a quantitative investigation Podladchikova & Berghmans, 2005 • DIMMING & EIT wave extraction from EUV image • Brightness distribution (histogram) analysis • study of higher moments • EIT wave radial and polar analysis • Ring Analysis • radial velocities in the EIT wave • Angular-Ring Analysis • potential angular features
Skewness & Kurtosis of PDF of difference image versus time Simultaneous peaks + dimming area criteria→ EIT Waves! Courtesy of Podladchikova & Berghmans
12 May 1997 Width m3-m2 mmax Both quadratic Distances vs Time Integrated signals vs Time Courtesy of Podladchikova & Berghmans
Results • Anisotropy even without obstacles. Correlation with associated dimming; • Dimming contiguous to wave front in all directions • Width of the front grows ~quadratically in time; • Integrated intensity of wave front grows during > 1/2 hrThe front intensity of linear magnetosonic waves would decrease • Integrated intensity of frontbalances integrated intensity of the dimmings (in early life of wave) EIT wave = MHD wave?
Perturbation velocity from flare to flare “to set the fire” Vchar ~ 110 km/s t < 5h. Velocity [km/s] 3225 flares registered with coordinates since 01/01/2004. Statistically complete series. Result does not depend on time interval
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 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 At flare peak ½ log(μ(scale)) Just before the flare begins log(scale)
Beauty spotter Method: Extraction in scale space by Lipschitz coefficient Hochedez 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