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."
Spectral (1-D) Data
- Introduction to Fitting PHA Spectra
- Changing the grouping scheme of a data set within Sherpa
- Simultaneously Fitting Two Data Sets
- Fitting a PHA Data Set with Multiple Responses
- Simulating X-ray Spectral Data (PHA): the fake_pha command
- Simulating Chandra ACIS-S Spectra with Sherpa
- Simulating Chandra ACIS-S LETG Spectra with Sherpa
- Simulating NuSTAR X-Ray Spectra with Sherpa
- Fitting PHA Data with Multi-Component Source Models
- Calculating Uncertainties by Simulating Flux Distributions
- Calculating Model Flux and Flux Uncertainty
- Simultaneously Fitting Source and Background Spectra
- Using A Pileup Model
- Sherpa User Models
- Sherpa Table Models
- Sherpa Template Models
- Creating an Input Spectrum for MARX and ChaRT Simulations
- Bayesian Analysis in Sherpa
- Using XSpec User Models in Sherpa
Spatial (2-D) Data
- Fitting FITS Image Data
- Radial and elliptical profiles of Image Data
- Using an Exposure Map in Fitting Image Data
- Accounting for PSF Effects in 2D Image Fitting
- Fitting Image Data with Convolved and Unconvolved Model Components
- See also: the Obtain and Fit a Radial Profile CIAO thread
- Sherpa User Models
These threads involve data analysis which is not specific to X-ray spectral or spatial modeling, therefore they can be followed using simple ASCII files as input, or other non-X-ray data.
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.
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.