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Last modified: 11 December 2023

Sherpa Threads


Beginners should start here. The Introductory threads explain how to start Sherpa and provide an overview of using the application.


To quickly access the scripts used in each of the Sherpa threads, visit the Sherpa Quick Scripts page.


Sherpa provides extensive facilities for modeling and fitting data. The topics here range from basic fits using source spectra and responses to more advanced areas, such as simultaneous fits to multiple data sets, accounting for the effects of pileup, and fitting spatial and grating data.

Before fitting ACIS spectral data sets with limited pulse-height ranges, please read the CIAO caveat "Spectral analyses of ACIS data with a limited pulse-height range."


Sherpa allows the user to plot data, fits, statistics, ARFs, contours, and more. These threads describe the basics of plotting as well as various methods for customizing plots when using matplotlib.

[New] CIAO 4.16 now supports using the Bokeh system but the threads use matplotlib since support for Bokeh is currently experimental and it is also more-suited for use in a Jupyter notebook.


Sherpa provides numerous tools for determining goodness of fit, errors in parameter values, confidence intervals, and other statistical measures of a model's validity. These threads describe how to use these tools in your analysis.


The Sherpa fake_pha command is available for simulating a Chandra PHA data set with an input instrument response and source model expression. These threads describe how to produce simulated data appropriate for your analysis.


These threads demonstrate miscellaneous tasks in Sherpa which you may find useful in your scientific analysis, and which are not specific to the other thread categories.