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AIA/HMI Science Teams Meeting, Monterey, Feb 13-17, 2006 Session S4: Feature Recognition: Needs and Techniques

Feature & Pattern Recognition in EUV Corona : Prospects for AIA. Markus Aschwanden (Lockheed Martin Solar Astrophysics Laboratory). AIA/HMI Science Teams Meeting, Monterey, Feb 13-17, 2006

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AIA/HMI Science Teams Meeting, Monterey, Feb 13-17, 2006 Session S4: Feature Recognition: Needs and Techniques

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  1. Feature & Pattern Recognition in EUV Corona : Prospects for AIA Markus Aschwanden (Lockheed Martin Solar Astrophysics Laboratory) AIA/HMI Science Teams Meeting, Monterey, Feb 13-17, 2006 Session S4: Feature Recognition: Needs and Techniques

  2. Content of talk : • Scientific Motivation for reconstructing 3D structures: • - Hydrodynamics of elementary coronal loops • Hydrodynamics and evolution of flare loops • Hydrodynamics and evolution of filaments • Tracing the real coronal magnetic fields • (2) Methods and Problems of extracting 3D structures: • Fingerprinting (automated detection) of curvi-linear structures • Background subtraction, disentangling, confusion problems • Disentangling of multi-temperature, multi-thread structures • 3D reconstruction of 2D curvi-linear features • Stereoscopic analysis with 2 spacecraft (STEREO 2006) (3) Conclusions

  3. (1a) Hydrodynamic modeling of elementary and composite loops • Problems: • Isolated loops don’t exist • Every background consists of loops itself • Disentangling of nested loop strands often impossible • due to lack of 3D information and insufficient resolution • -Background is often ill-defined because it requires • modeling of background loops ad infinitum

  4. (1b) Hydrodynamics and evolution of flare loops Aschwanden (2002) • - Spatio-temporal tracing of magnetic reconnection • Hydrodynamics, heating, cooling of postflare loops • Footpoint (double) ribbon separation and X-point height h(s) • Shear vs. height relation of reconnecting field lines

  5. (1c) Hydrodynamics and evolution of filaments Envold (2001) Aulanier & Schmieder (2002) • Geometry and multi-threat structure of filaments • (helicity, chirality, handedness  conservation, fluxropes) • Spatio-temporal evolution and hydrodynamic balance • Stability conditions for quiescent filaments • Hydrodynamic instability and magnetic instability • of erupting filaments leading to flares and CMEs

  6. (1d) Tracing the real coronal magnetic field Wiegelmann & Neukirch (2002) Aschwanden et al. (1999) • Tests of (theoretical) potential field, linear force-free, • and nonlinear force-free magnetic field extrapolation by • comparison with observed EUV loops (projected in 2D) • -3D reconstruction of EUV loop coordinates with “dynamic • solar-rotation stereoscopy” or “two-spacecraft observations”

  7. (1e) Measuring the twist of magnetic field lines Aschwanden (2004) • Measuring the number of turns in twisted loops • Testing the kink-instability criterion for stable/erupting loops • Monitoring the evolution of magnetic relaxation (untwisting) • between preflare and postflare loops

  8. (1e) Measuring the twist of magnetic field lines Aschwanden (2004) • Measuring number of turns in (twisted) sigmoids • before and after eruption • -Test of kink-instability criterion as trigger of flares/CMEs

  9. (1f) Measuring the twist of erupting fluxropes Gary & Moore (2004) • Measuring number of turns in erupting fluxropes • -Test of kink-instability criterion as trigger of flares/CMEs

  10. 2) Pattern and Feature Recognition: Methods and Problems

  11. (2a) Fingerprinting (automated detection) of curvi-linear structures Louis Strous (2002) http:/www.lmsal.com/~aschwand/stereo/2000easton/cdaw.html • Strous detects curvi-linear segments from brightness gradients • in 3x3 neighborhood areas • -Problems: incompleteness of coronal loops • no discrimination between noisy pixels and loops • combination of curvi-linear segments to full loops

  12. (2a) Fingerprinting (automated detection) of curvi-linear structures • Lee, Newman & Gary • improve detection of • coronal loops with • “Oriented connectivity • Method” (OCM): • median filtering • contrast enhancement • unsharp mask • detection threshold • directional connectivity Lee, Newman, & Gary (2004), 17th Internat. Conf. On Pattern Recognition, Cambridge UK, 23-26 Aug 2004

  13. Lee, Newman, & Gary (2004),  see poster by Lee et al. at this workshop

  14. Simulation results: -OCM renders most of the loop structures • Remaining problems: • crossing loops • misconnections • ambiguous connections • faint loops • crowded regions Lee, Newman, & Gary (2004)

  15. Lee, Newman, & Gary 2006, “Dynamic Aperture-based Solar Loop Segmentation” (in prep.)

  16. Loop detection in triple-filter TRACE data (171 A, 195 A, 284 A) 1998-Jun-12 1205:20 UT -Manual tracing (10 pts) -spline interpolation x(s),y(s) -1D stretching with bilinear interpolation -multiple strands visible -spatial offsets of loop centroids in 3 filters -background loops -background moss

  17. Loops Widths Loop/Backgr. Instrument Ref. • 1 ~12 Mm ? CDS Schmelz et al. (2001) • ? 170%150% EIT Schmelz et al. (2003) • 7.10.8 Mm 30%20% EIT Aschwanden et al. (1999) • 1 ~5.8 Mm 76%34% TRACE/CDS DelZanna & Mason (2003) • 3.71.5 Mm ? TRACE Aschwanden et al. (2000) • (no highpass filter) • 1.40.2 Mm 8%3% TRACE Aschwanden & Nightingale • 2005 (with highpass filter)

  18. (2d) 3D reconstruction of loop structures Full testing of theoretical magnetic field extrapolation models with EUV-traced loops requires 3D reconstruction of loop coordinates [x(s), y(s), z(s)]  (1) Solar-rotation dynamic stereoscopy (2) Two-spacecraft stereoscopy

  19. Matching/Fitting of EUV tracings and extrapolated field lines allows to constrain free parameters: Alpha of nonlinear force-free field model. Wiegelmann & Neukirch (2002)

  20. (2e) Stereoscopic analysis with 2 STEREO spacecraft • Identification of a common feature from two views is difficult • for nested structures (loop arcades, active region loops) • -Stereoscopic 3D-reconstruction is least ambiguous for small • stereo-angles, but 3D accuracy is best for large stereo-angles: • optimum at angles of ~10-30 deg.

  21. Conclusions • Stereoscopic reconstruction of 3D structures • can be used to detect and quantify coronal loops, • filaments, and postflare loops.

  22. Conclusions (cont.) (2) 3D-reconstruction of coronal loop structures is most useful to test theoretical models of magnetic field extrapolations.

  23. Conclusions (cont.) (3) Hydrostatic/hydrodynamic modeling of coronal loops requires careful disentangling of neighbored loops, background modeling, multi-component modeling, and multi-filter temperature modeling. Accurate modeling requires the identification of elementary loops.

  24. Conclusions (cont.) (4) The latest TRACE study has shown the existence of elementary loop strands with isothermal cross- sections, at FWHM widths of <1500 km. TRACE has a pixel size of 0.5” and a point-spread function of 1.25” (900 km) and is able to resolve some of them, while AIA (0.6” pixels, PSF~1.5”=1100 km) will marginally resolve the largest ones. Multi-filter analysis is a necessity to discriminate elementary from composite loops.

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