Coronal seismology, AIAHMI and image processing : Best wishes :

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Coronal seismology, AIA/HMI and image
processing(- Best wishes -)

• JF Hochedez, E Robbrecht, O Podladchikova, A
  Zhukov, D Berghmans
• SIDC _at_ ROB
• Solar Influences Data analysis Center
• Royal Observatory of Belgium

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Mandate of this presentation
AIA
Coronal Seismology
Image Processing
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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

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EUV imaging observations and seismology(2) in
other coronal structures
EIT wave detector
Flare detector and Podladchikova et al
(submitted)
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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

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Optical Flow

• its application to fast modes

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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?

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Hopes from AIA-HMI (1/2)

• 8 bandpasses
• Longitudinal density profile (DEM tools)
• Heating profile
• Spatial resolution
• Radial density profiles concentric shells,
  threads?
• 0.6probably 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

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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_at_171, 61x _at_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
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VELOCIRAPTOR VELOCIty bRightness vAriations
maPs construcTOR

• Quantify motion together with intrinsic
  brightness variationin EIT image sequences

Gissot Hochedez, 2006
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Inputs outputs
Velocity field

• Similarity fieldbetweenIn(x,y) (warped)and
  In1(x,y)
• Local texture
• Residuals

Image In(x,y)
e.g. EIT CME Watch
Image In1(x,y)
Brightness Variation field
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Differential rotation recovered from a couple of
EIT images
(No BV estimation)
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BV map of the May 12, 1997 event
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Velocity map of the May 12, 1997 event
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(No BV estimation)
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14 July 1998 125016
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Differenced image
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Presence of texture in 2 orthogonal directions
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Presence of texture at least in one direction
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Zoom of the previous representation
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Velocity field produced by Velociraptor
Average displacement 0.3 pixel ? LCT not
appropriate (a posteriori justification)
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Velocity field corrected for global shift
Loop displacement 0.15 pixel
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Question What are the anticipated artifacts for
AIA?
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OF fast magneto-sonic wavesConclusions 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?

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Slow waves
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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

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Useful image processingfor slow waves (1)

• Loop extraction (ridge detection)

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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

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Computer Aided CME Tracking -CACTus
11 November 2003
15h18
15h54
17h06
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r
t
?t
t0
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EIT waves
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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 150400 km/s,
  typically around 250 km/s.
• Association with chromospheric Moreton waves,
  waves in He I and waves in SXR?

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If EIT waves are fast magnetosonic waves
Courtesy A Zhukov 2006
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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

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Skewness Kurtosis of PDF of difference image
versus time
Simultaneous peaks dimming area criteria? EIT
Waves!
Courtesy of Podladchikova Berghmans
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12 May 1997
Width m3-m2
mmax
Both quadratic
Distances vs Time
Integrated signals vs Time
Courtesy of Podladchikova Berghmans
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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 front balances integrated
  intensity of the dimmings (in early life of wave)
  
• EIT wave MHD wave?

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Sympathetic flaring
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Consecutive occurrence of flares in different AR

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Perturbation velocity from flare to flare to
set the fire
Vchar 110 km/s
?t Velocity km/s
3225 flares registered with coordinates since
01/01/2004. Statistically complete series.
Result does not depend on time interval
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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.

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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)
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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
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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