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Segmentation of Coronal Holes Using Active Contours Without Edges  

R.T.James McAteer   Submitted: 2016-09-30 09:53

An application of active contours without edges is presented as an efficient and effective means of extracting and characterizing coronal holes. Coronal holes are regions of low-density plasma on the Sun with open magnetic field lines. The detection and characterization of these regions is important for testing theories of their formation and evolution, and also from a space weather perspective because they are the source of the fast solar wind. Coronal holes are detected in full-disk extreme ultraviolet (EUV) images of the corona obtained with the Solar Dynamics Observatory Atmospheric Imaging Assembly (SDO/AIA). The proposed method detects coronal boundaries without determining any fixed intensity value in the data. Instead, the active contour segmentation employs an energy-minimization in which coronal holes are assumed to have more homogeneous intensities than the surrounding active regions and quiet Sun. The segmented coronal holes tend to correspond to unipolar magnetic regions, are consistent with concurrent solar wind observations, and qualitatively match the coronal holes segmented by other methods. The means to identify a coronal hole without specifying a final intensity threshold may allow this algorithm to be more robust across multiple datasets, regardless of data type, resolution, and quality.

Authors: L.E. Boucheron, M. Valluri, R.T.J. McAteer
Projects:

Publication Status: Published
Last Modified: 2016-10-03 12:33
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Prediction of Solar Flare Size and Time-to-Flare Using Support Vector Machine Regression  

R.T.James McAteer   Submitted: 2015-11-05 15:44

We study the prediction of solar flare size and time-to-flare using 38 features describing magnetic complexity of the photospheric magnetic field. This work uses support vector regression to formulate a mapping from the 38-dimensional feature space to a continuous-valued label vector representing flare size or time-to-flare. When we consider flaring regions only, we find an average error in estimating flare size of approximately half a geostationary operational environmental satellite (GOES) class. When we additionally consider non-flaring regions, we find an increased average error of approximately 3/4 a GOES class. We also consider thresholding the regressed flare size for the experiment containing both flaring and non-flaring regions and find a true positive rate of 0.69 and a true negative rate of 0.86 for flare prediction. The results for both of these size regression experiments are consistent across a wide range of predictive time windows, indicating that the magnetic complexity features may be persistent in appearance long before flare activity. This is supported by our larger error rates of some 40 hr in the time-to-flare regression problem. The 38 magnetic complexity features considered here appear to have discriminative potential for flare size, but their persistence in time makes them less discriminative for the time-to-flare problem.

Authors: Boucheron, L.E., Al-Ghraibah, A., McAteer, R.T.J.
Projects: GOES X-rays ,SoHO-MDI

Publication Status: ApJ, 2015, 812, 51
Last Modified: 2015-11-06 10:53
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An automated classification approach to ranking photospheric proxies of magnetic energy build-up  

R.T.James McAteer   Submitted: 2015-06-29 09:14

Aims. We study the photospheric magnetic field of ~2000 active regions over solar cycle 23 to search for parameters that may be indicative of energy build-up and its subsequent release as a solar flare in the corona. Methods. We extract three sets of parameters: (1) snapshots in space and time: total flux, magnetic gradients, and neutral lines; (2) evolution in time: flux evolution; and (3) structures at multiple size scales: wavelet analysis. This work combines standard pattern recognition and classification techniques via a relevance vector machine to determine (i.e., classify) whether a region is expected to flare (≥C1.0 according to GOES). We consider classification performance using all 38 extracted features and several feature subsets. Classification performance is quantified using both the true positive rate (the proportion of flares correctly predicted) and the true negative rate (the proportion of non-flares correctly classified). Additionally, we compute the true skill score which provides an equal weighting to true positive rate and true negative rate and the Heidke skill score to allow comparison to other flare forecasting work. Results. We obtain a true skill score of ~0.5 for any predictive time window in the range 2 to 24 h, with a true positive rate of ~0.8 and a true negative rate of ~0.7. These values do not appear to depend on the predictive time window, although the Heidke skill score (<0.5) does. Features relating to snapshots of the distribution of magnetic gradients show the best predictive ability over all predictive time windows. Other gradient-related features and the instantaneous power at various wavelet scales also feature in the top five (of 38) ranked features in predictive power. It has always been clear that while the photospheric magnetic field governs the coronal non-potentiality (and hence likelihood of producing a solar flare), photospheric magnetic field information alone is not sufficient to determine this in a unique manner. Furthermore we are only measuring proxies of the magnetic energy build up. We are still lacking observational details on why energy is released at any particular point in time. We may have discovered the natural limit of the accuracy of flare predictions from these large scale studies.

Authors: A. Al-Ghraibah, L.E. Boucheron, R.T.J. McAteer
Projects: GOES X-rays ,GONG,SDO-HMI,SoHO-MDI

Publication Status: 2015, Accepted
Last Modified: 2015-06-29 11:54
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Performance Testing of an Off-Limb Solar Adaptive Optics System  

R.T.James McAteer   Submitted: 2015-06-25 12:13

Long-exposure spectro-polarimetry in the near-infrared is a preferred method to measure the magnetic field and other physical properties of solar prominences. In the past, it has been very difficult to observe prominences in this way with sufficient spatial resolution to fully understand their dynamical properties. Solar prominences contain highly transient structures, visible only at small spatial scales; hence they must be observed at sub-arcsecond resolution, with a high temporal cadence. An adaptive optics (AO) system capable of directly locking on to prominence structure away from the solar limb has the potential to allow for diffraction-limited spectro-polarimetry of solar prominences. We show the performance of the off-limb AO system and its expected performance at the desired science wavelength Ca II 8542 Å.

Authors: G.E. Taylor, D. Schmidt, J. Marino, T.R. Rimmele, R.T.James McAteer
Projects: National Solar Observatory (Sac Peak)

Publication Status: Accepted
Last Modified: 2015-06-29 11:55
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25 Years of Self-Organized Criticality: Numerical Detection Methods  

R.T.James McAteer   Submitted: 2015-06-25 11:58

The detection and characterization of self-organized criticality (SOC), in both real and simulated data, has undergone many significant revisions over the past 25 years. The explosive advances in the many numerical methods available for detecting, discriminating, and ultimately testing, SOC have played a critical role in developing our understanding of how systems experience and exhibit SOC. In this article, methods of detecting SOC are reviewed; from correlations to complexity to critical quantities. A description of the basic autocorrelation method leads into a detailed analysis of application-oriented methods developed in the last 25 years. In the second half of this manuscript space-based, time-based and spatial-temporal methods are reviewed and the prevalence of power laws in nature is described, with an emphasis on event detection and characterization. The search for numerical methods to clearly and unambiguously detect SOC in data often leads us outside the comfort zone of our own disciplines - the answers to these questions are often obtained by studying the advances made in other fields of study. In addition, numerical detection methods often provide the optimum link between simulations and experiments in scientific research. We seek to explore this boundary where the rubber meets the road, to review this expanding field of research of numerical detection of SOC systems over the past 25 years, and to iterate forwards so as to provide some foresight and guidance into developing breakthroughs in this subject over the next quarter of a century.

Authors: R.T. James McAteer, Markus J. Aschwanden, Michaila Dimitropoulou, Manolis K. Georgoulis, Gunnar Pruessner, Laura Morales, Jack Ireland, Valentyna Abramenko
Projects: GONG,National Solar Observatory (Sac Peak),Other,RHESSI,SDO-AIA,SDO-EVE,SoHO-EIT,STEREO,THEMIS/MTR

Publication Status: Accepted
Last Modified: 2015-06-29 11:55
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Automated Detection of Coronal Loops using a Wavelet Transform Modulus Maxima Method  

R.T.James McAteer   Submitted: 2010-02-16 07:32

We propose and test a wavelet transform modulus maxima method for the automated detection and extraction of coronal loops in extreme ultraviolet images of the solar corona. This method decomposes an image into a number of size scales and tracks enhanced power along each ridge corresponding to a coronal loop at each scale. We compare the results across scales and suggest the optimum set of parameters to maximise completeness while minimising detection of noise. For a test coronal image, we compare the global statis- tics (e.g., number of loops at each length) to previous automated coronal-loop detection algorithms.

Authors: McAteer, R.T.James, Kestener, P., Arneodo, A., Khalil, A.
Projects: SoHO-EIT,STEREO,TRACE

Publication Status: Solar Physics (accepted)
Last Modified: 2010-02-18 11:37
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Turbulence, Complexity, and Solar Flares  

R.T.James McAteer   Submitted: 2009-09-30 09:42

The issue of predicting solar flares is one of the most fundamental in physics, addressing issues of plasma physics, high-energy physics, and modelling of complex systems. It also poses societal consequences, with our ever-increasing need for accurate space weather forecasts. Solar flares arise naturally as a competition between an input (flux emergence and rearrangement) in the photosphere and an output (electrical current build up and resistive dissipation) in the corona. Although initially localised, this redistribution affects neighbouring regions and an avalanche occurs resulting in large scale eruptions of plasma, particles, and magnetic field. As flares are powered from the stressed field rooted in the photosphere, a study of the photospheric magnetic complexity can be used to both predict activity and understand the physics of the magnetic field. The magnetic energy spectrum and multifractal spectrum are highlighted as two possible approaches to this

Authors: R. T. James McAteer, Peter T. Gallagher, Paul A. Conlon
Projects: GONG,Mount Wilson Observatory,SoHO-MDI

Publication Status: Advances in Space Science Research
Last Modified: 2009-10-01 06:31
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The bursty nature of solar flare X-ray emission  

R.T.James McAteer   Submitted: 2007-05-23 13:47

The complex and highly-varying temporal nature of emission from an X4.8 flare is studied across 7 X-ray energy bands. A wavelet transform modulus maxima method is used to obtain the multifractal spectra of the temporal variation of the X-ray emission. As expected from the Neupert effect, the time series of emission at low (3-6, 6-12 keV; thermal) energies is smooth. The peak Holder exponent around 1.2 for this low energy emission is indicative of a signal with a high degree of memory and suggestive of a smooth chromospheric evaporation process. The more bursty emission at higher energies (100-300, 300-800 keV; non-thermal) is described by a multifractal spectrum which peaks at a smaller Holder exponent (less than 0.5 for the largest singularities), indicative of a signal with a low degree of memory. This describes an anti-persistent walk and indicates a impulsive, incoherent driving source. We suggest this may arise from bursty reconnection, with each reconnection event producing differing and uncorrelated non-thermal particle sources. The existence of power law scaling of wavelet coefficients across timescales is in agreement with the creation of a fractal current sheet diffusion region.

Authors: R.T.James McAteer, C.Alex Young, Jack Ireland, Peter T. Gallagher
Projects: RHESSI

Publication Status: ApJ, 662, 691, 2007
Last Modified: 2007-06-11 07:58
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Observations of Hα Intensity Oscillations in a Flare Ribbon  

R.T.James McAteer   Submitted: 2005-02-22 10:00

High-cadence Hα blue wing observations of a C9.6 solar flare obtained at Big Bear Solar Observatory using the Rapid Dual Imager are presented. Wavelet and time-distance methods were used to study oscillatory power along the ribbon, finding periods of 4080 s during the impulsive phase of the flare. A parametric study found statistically significant intensity oscillations with amplitudes of 3% of the peak flare amplitude, periods of 69 s (14.5 mHz) and oscillation decay times of 500 s. These measured properties are consistent with the existence of flare-induced acoustic waves within the overlying loops.

Authors: McAteer, R.T.J., Gallagher P.T., Brown, D.S., Bloomfield, D.S., Moore R., Williams, D.R., Mathioudakis, M., Katsiyannis, A. Keenan, F.P.
Projects: None

Publication Status: 2005, APJ, 620, 1101
Last Modified: 2005-02-22 10:00
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Abstracts by Author
Segmentation of Coronal Holes Using Active Contours Without Edges
Prediction of Solar Flare Size and Time-to-Flare Using Support Vector Machine Regression
An automated classification approach to ranking photospheric proxies of magnetic energy build-up
Performance Testing of an Off-Limb Solar Adaptive Optics System
25 Years of Self-Organized Criticality: Numerical Detection Methods
Automated Detection of Coronal Loops using a Wavelet Transform Modulus Maxima Method
Turbulence, Complexity, and Solar Flares
The bursty nature of solar flare X-ray emission
Observations of H-alpha Intensity Oscillations in a Flare Ribbon

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