Flexibility and Extensibility of Sherpa in CIAO 4.2

Mathematics – Probability

Scientific paper

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Scientific paper

Sherpa is the general modeling and fitting application developed in CIAO (Chandra Interactive Analysis of Observations). It provides a flexible environment for modeling a variety of Chandra data (spectra, images, time series) as well as data from other X-ray missions. It also allows for modeling multi-frequency data simultaneously (e.g. spectral energy distributions using X-ray, optical and radio data; modeling and fitting optical images with PSFs; or any other type of data that are provided as collections of arrays). Sherpa uses the forward fitting technique, so parameterized models are fit by minimization of the statistic that describes the differences between the data and the model. Sherpa has a library of mathematical and astrophysical models including the XSPEC 12.5 models. Sherpa allows for fitting high counts data with a choice of weighted chi-square statistics. The Poisson likelihood for low counts data is available with Cash statistics and simulations to access the probability distributions. The final model parameters have confidence bounds that are calculated, and visualization of the parameter space allows for analysis of correlations between parameters or multi-modality of the parameter space. Sherpa's modular and extensible design allows for a considerable degree of user customization. Models and statistical functions of arbitrary complexity can be written in C, Fortran or Python, and can be easily imported into a running Sherpa session. We briefly describe the new Sherpa and give examples of the complex cases that can be successfully modeled in the current version. This work is supported by NASA contract NAS8-03060 (CXC).

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