Spectra derived from fast Fourier transform (FFT) analysis of time-domain data intrinsically contain statistical fluctuations whose distribution depends on the number of accumulated spectra contributing to a measurement. The tail of this distribution
, which is essential for separation of the true signal from the statistical fluctuations, deviates noticeably from the normal distribution for a finite number of the accumulations. In this paper we develop a theory to properly account for the statistical fluctuations when fitting a model to a given accumulated spectrum. The method is implemented in software for the purpose of automatically fitting a large body of such FFT-derived spectra. We apply this tool to analyze a portion of a dense cluster of spikes recorded by our FST instrument during a record-breaking event that occurred on 06 Dec 2006. The outcome of this analysis is briefly discussed.
We have developed a general framework for modeling gyrosynchrotron and free-free emission from solar flaring loops and used it to test the premise that 2D maps of source parameters, particularly magnetic field, can be deduced from spatially resolved
microwave spectropolarimetry data. In this paper we show quantitative results for a flaring loop with a realistic magnetic geometry, derived from a magnetic field extrapolation, and containing an electron distribution with typical thermal and nonthermal parameters, after folding through the instrumental profile of a realistic interferometric array. We compare the parameters generated from forward fitting a homogeneous source model to each line of sight through the folded image data cube with both the original parameters used in the model and with parameters generated from forward fitting a homogeneous source model to the original (unfolded) image data cube. We find excellent agreement in general, but with systematic effects that can be understood as due to finite resolution in the folded images and the variation of parameters along the line of sight, which are ignored in the homogeneous source model. We discuss the use of such 2D parameter maps within a larger framework of 3D modeling, and the prospects for applying these methods to data from a new generation of multifrequency radio arrays now or soon to be available.
Due to its conceptual simplicity and its proven effectiveness in real-time detection and removal of radio frequency interference (RFI) from radio astronomy data, the Spectral Kurtosis (SK) estimator is likely to become a standard tool of a new genera
tion of radio telescopes. However, the SK estimator in its original form must be developed from instantaneous power spectral density (PSD) estimates, and hence cannot be employed as an RFI excision tool downstream of the data pipeline in existing instruments where any time averaging is performed. In this letter, we develop a generalized estimator with wider applicability for both instantaneous and averaged spectral data, which extends its practical use to a much larger pool of radio instruments.
Modern observations and models of various astrophysical objects suggest that many of their physical parameters fluctuate substantially at different spatial scales. The rich variety of the emission processes, including Transition Radiation but not lim
ited to it, arising in such turbulent media constitutes the scope of Stochastic Theory of Radiation. We review general approaches applied in the stochastic theory of radiation and specific methods used to calculate the transition radiation produced by fast particles in the magnetized randomly inhomogeneous plasma. The importance of the theory of transition radiation for astrophysics is illustrated by one example of its detailed application to a solar radio burst, including specially designed algorithms of the spectral forward fitting.
