Spike Decomposition Technique: Modeling and Performance Tests

Abstract

We develop an automated technique for fitting the spectral components of solar microwave spike bursts, which are characterized by narrowband spectral features. The algorithm is especially useful for periods when the spikes occur in densely packed clusters, where the algorithm is capable of decomposing overlapping spike structures into individual spectral components. To test the performance and applicability limits of this data reduction tool, we perform comprehensive modeling of spike clusters characterized by various typical bandwidths, spike densities, and amplitude distributions. We find that, for a wide range of favorable combinations of input parameters, the algorithm is able to recover the characteristic features of the modeled distributions within reasonable confidence intervals. Having model-tested the algorithm against spike overlap, broadband spectral background, noise contamination, and possible malfunction of some spectral channels, we apply the technique to a spike cluster recorded by the Chinese Purple Mountain Observatory (PMO) spectrometer, operating above 4.5 GHz. We study the variation of the spike distribution parameters, such as amplitude, bandwidth, and related derived physical parameters, as a function of time. The method can be further applied to observations from other instruments and to other types of fine structures.

Particle acceleration by a solar flare termination shock

“…(3) The spike bandwidth tends to have less dispersion at larger brightness. These findings are generally consistent with earlier studies of solar spike bursts based on total-power dynamic spectral data (i.e., without spatial information) (38)(39)(40)(41).…”

“…(2) The spike bandwidth distribution is asymmetric, which peaks at ~23 MHz (or 2% relative to the observing frequency), with a long tail extending to larger values. (3) The spike bandwidth tends to have less dispersion at larger These findings are generally consistent with earlier studies of solar spike bursts based on total-power dynamic spectral data (i.e., without spatial information) (38)(39)(40)(41).…”

Fitting FFT-Derived Spectra: Theory, Tool, and Application to Solar Radio Spike Decomposition

“…Similar asymmetric shapes of the bandwidth distribution are typical and have been reported for both decimeter and microwave spikes (Elgarøy & Sveen 1973;Csillaghy & Benz 1993;Messmer & Benz 2000;Rozhansky et al 2008;Nita et al 2008). Rozhansky et al (2008) employed a theory of the ECM bandwidth formation in a source with random inhomogeneities of the magnetic field developed by Fleishman (2004a) and demonstrated that the observed distribution was in almost perfect agreement with this theory.…”

“…Solar radio spikes (Dröge 1977;Slottje 1978;Stähli & Magun 1986;Benz 1986) are a most intriguing type of solar coherent radio emission (Slottje 1981;Güdel & Benz 1988;Isliker & Benz 1994;Benz et al 2005b), and have attracted attention both observationally and theoretically because of their unique properties and potential diagnostic value (Elgarøy & Sveen 1973;Benz 1985;Csillaghy & Benz 1993;Fleishman & Melnikov 1998;Fleishman et al 2003;Fleishman 2004a;Dabrowski et al 2005;Rozhansky et al 2008;Benz et al 2009;Dabrowski et al 2011). For example, the spectral bandwidth of spikes is typically 1% or less of the frequency at which they occur (Elgarøy & Sveen 1973;Benz 1986;Csillaghy & Benz 1993;Messmer & Benz 2000;Rozhansky et al 2008;Nita et al 2008), which implies that some controlling parameter of the spike source can in principle be determined with a corresponding precision of 1% or better, which would be superior for remote diagnostics of the solar corona.…”

“…Thus, getting a reliable distribution of these spike parameters from observations can shed light on both the production mechanism and on the fast electron distribution over energy and pitch-angle. In addition, spike parameter distributions contain information on global properties of the spike cluster source, such as its fragmentation into sources of individual spikes (Benz 1985), and the level of magnetic irregularities (turbulence) in the source (Rozhansky et al 2008;Nita et al 2008).…”