Toward RHESSI Spectroscopic Imaging: I, Spectroscopy

Details Toward RHESSI Spectroscopic Imaging: I, Spectroscopy Toward RHESSI Spectroscopic Imaging: I, Spectroscopy

Jun 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006spd....37.0604i&link_type=abstract

American Astronomical Society, SPD meeting #37, #6.04; Bulletin of the American Astronomical Society, Vol. 38, p.226

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We examine two new approaches to determining parameter values to emission spectra from RHESSI and the Coronal Diagnostic Spectrometer (CDS) on board SoHO. Simulated annealing removes much of the bias inherent in initializing commonly used deterministic routines through implementing a parameter space search minimizing a suitable cost function (such as sum of squares of differences between data and a parameterized curve). This search gradually moves from being a full random search to a directed search where only parameter values which minimize the cost function are accepted. In comparison, Markov Chain Monte Carlo methods are used to sample from the Bayesian posterior distribution constructed from prior information on the observation (such as the number of emission lines present and likely parameter values) as well as the data itself. Parameter values can then be assigned by constructing the appropriate averages from the data.These methods have the advantage of sidestepping many of the problems of traditional analysis routines (for example, ill-conditioned matrices) whilst allowing the easy inclusion of other information, such as parameter constraints. Both approaches are applied to CDS and RHESSI spectroscopic data, and are compared to more commonly used routines.

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