Engineering topics

Young, C. A.

Publications and source records attributed to Young, C. A..

4 records

NASA NTRS2016

Persistence Mapping Using EUV Solar Imager Data

We describe a simple image processing technique that is useful for the visualization and depiction of gradually evolving or intermittent structures in solar physics extreme-ultraviolet imagery. The technique is an application of image segmentation, which we call "Persistence Mapping," to isolate extreme values in a data set, and is particularly useful for the problem of capturing phenomena that are evolving in both space and time. While integration or "time-lapse" imaging uses the full sample (of size N ), Persistence Mapping rejects (N - 1)/N of the data set and identifies the most relevant 1/N values using the following rule: if a pixel reaches an extreme value, it retains that value until that value is exceeded. The simplest examples isolate minima and maxima, but any quantile or statistic can be used. This paper demonstrates how the technique has been used to extract the dynamics in long-term evolution of comet tails, erupting material, and EUV dimming regions.

Thompson, B. J.↗

NASA NTRS2013

Energy Release from Impacting Prominence Material Following the 2011 June 7 Eruption

Solar filaments exhibit a range of eruptive-like dynamic activity, ranging from the full or partial eruption of the filament mass and surrounding magnetic structure as a coronal mass ejection to a fully confined or failed eruption. On 2011 June 7, a dramatic partial eruption of a filament was observed by multiple instruments on board the Solar Dynamics Observatory (SDO) and Solar-Terrestrial Relations Observatory. One of the interesting aspects of this event is the response of the solar atmosphere as non-escaping material falls inward under the influence of gravity. The impact sites show clear evidence of brightening in the observed extreme ultraviolet wavelengths due to energy release. Two plausible physical mechanisms for explaining the brightening are considered: heating of the plasma due to the kinetic energy of impacting material compressing the plasma, or reconnection between the magnetic field of low-lying loops and the field carried by the impacting material. By analyzing the emission of the brightenings in several SDO/Atmospheric Imaging Assembly wavelengths, and comparing the kinetic energy of the impacting material (7.6 × 10(exp 26) - 5.8 × 10(exp 27) erg) to the radiative energy (approx. 1.9 × 10(exp 25) - 2.5 × 10(exp 26) erg), we find the dominant mechanism of energy release involved in the observed brightening is plasma compression.

Sun: corona↗

NASA NTRS2010

The Connection Between Small Gamma-Ray Flares and SEPs with COMPTEL/CGRO

While it is clear that particle acceleration is occurring during flares, what is less clear is the connection between the neutral radiation observed concommitant with the flare and the in-situ observations of SEPs. For the largest SEP events, where current instruments possess the sensitivity to observe nuclear-related gamma-ray emission, the origin of SEPs is generally divided between an escaping accelerated flare population and a population of coronal particles (or some admixture) accelerated through CME-driven shocks. Small flares, as defined by their X-ray emission, have been found to correlate with the presence of small "impulsive" (enriched in electrons and heavy nuclei) SEP events, suggesting that small SEP events are originally flare particles. The difficulty with this interpretation is that small flares lack detectable nuclear-related gamma-ray emission. Whether this emission is there or not is unclear because current instruments capable of high-energy gamma-ray observations operate above the sensitivity threshold for observing gammaray emission from small flares (< C-class). The COMPton TELescope (COMPTEL) aboard the Compton Gamma Ray Observatory (CGRO) provided unprecedented, and as yet unsurpassed, sensitivity to y rays in the 0.7 to 30 MeV energy range and neutrons in the 20 to 150 MeV energy range. This, combined with its nine years of operation, has produced a unique data set of observations for almost a complete solar cycle. The COMPTEL archival data offers the best possibility to investigate a connection between SEP observations in space and small-flare gamma-ray emission. We present preliminary results of a small-flare search within the COMPTEL archival data and discuss the correlation between already well-established compilations of SEP events and small impulsive or 3He-rich SEP events. Establishing a connection and determining the characterization of this connection, would signify an important development in our understanding of how and where flare particles are accelerated and how these very same particles escape into the interplanetary medium. Equally important would be demonstrating the inconsistencies or poor correlation between gamma-ray emission and small impulsive SEP events.

deNolfo, Georgia↗

NASA NTRS2010

Automated Detection of Oscillating Regions in the Solar Atmosphere

Recently observed oscillations in the solar atmosphere have been interpreted and modeled as magnetohydrodynamic wave modes. This has allowed for the estimation of parameters that are otherwise hard to derive, such as the coronal magnetic-field strength. This work crucially relies on the initial detection of the oscillations, which is commonly done manually. The volume of Solar Dynamics Observatory (SDO) data will make manual detection inefficient for detecting all of the oscillating regions. An algorithm is presented that automates the detection of areas of the solar atmosphere that support spatially extended oscillations. The algorithm identifies areas in the solar atmosphere whose oscillation content is described by a single, dominant oscillation within a user-defined frequency range. The method is based on Bayesian spectral analysis of time series and image filtering. A Bayesian approach sidesteps the need for an a-priori noise estimate to calculate rejection criteria for the observed signal, and it also provides estimates of oscillation frequency, amplitude, and noise, and the error in all of these quantities, in a self-consistent way. The algorithm also introduces the notion of quality measures to those regions for which a positive detection is claimed, allowing for simple post-detection discrimination by the user. The algorithm is demonstrated on two Transition Region and Coronal Explorer (TRACE) datasets, and comments regarding its suitability for oscillation detection in SDO are made.

Ireland, J.↗