A Response Matrix Approach to the Reconstruction of Differential Emission Measure

Details A Response Matrix Approach to the Reconstruction of Differential Emission Measure A Response Matrix Approach to the Reconstruction of Differential Emission Measure

May 2003

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003spd....34.0201k&link_type=abstract

American Astronomical Society, SPD meeting #34, #02.01; Bulletin of the American Astronomical Society, Vol. 35, p.807

Astronomy and Astrophysics

Astronomy

Scientific paper

The differential emission measure (DEM) provides a powerful tool for the characterization of the temperature structure of a stellar atmosphere. In this talk we develop a new method for the reconstruction of a DEM distribution within a Bayesian framework. In particular, we use a ``response matrix" to map from the unobserved photon counts in a number of temperature bins to the spectral line counts. This requires high resolution data and the resolution of many spectral lines that we obtain using Chandra gratings. Numerically, to reconstruct the unobserved counts in the temperature bins we must solve a difficult problem, which we accomplish using the method of data augmentation. Specifically we treat the counts for each temperature bin as ``missing data". Under this construction, we are able to use statistical methods that are designed to handle missing data problems. In particular, we use the Expectation-Maximization (EM) and Markov chain Monte Carlo (MCMC) methods, which allow us to find the maximum a postriori estimates and the highest posterior density intervals to construct estimates and error bars. We implement a Bayesian multiscale (wavelet-like) model to smooth the DEM distribution, which gives us the flexibility to overcome the lack of information especially with low count data. This approach allows for global spectral modeling, with the ability to include prior information in the form of known sequences and relative strengths of lines; the inclusion and propagation of errors in atomic data; and a proper accounting of the uncertainties in the reconstructed DEM. We provide several simulation studies with both high-count and low-count data to evaluate the proposed method.
The authors gratefully acknowledge funding for this project partially provided by NSF grant DMS-01-04129 and by NASA contract NAS8-39073 (CXC).

Affiliated with

Also associated with

No associations

Rating

A Response Matrix Approach to the Reconstruction of Differential Emission Measure does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Response Matrix Approach to the Reconstruction of Differential Emission Measure, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Response Matrix Approach to the Reconstruction of Differential Emission Measure will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-985209