Harvard-Smithsonian Center for Astrophysics MS-81, 60 Garden Street, Cambridge, MA 02138

We describe enhancements made to * Sherpa*
for the CIAO 2.0 release, concentrating upon those
that enable a user to: (1) analyze * Chandra* X-ray Observatory grating
data with wavelength- or energy-space models;
(2) simultaneously fit background and source datasets; and
(3) estimate and visualize confidence intervals and regions.
We also list enhancements that we plan to make to * Sherpa*
for future CIAO releases.

* Sherpa* is the modeling and fitting tool of the
* Chandra* Interactive Analysis of Observations (CIAO) software package
(Doe et al. 1998 and references therein).
We have developed it with the primary goal that a user should be able to
take
full advantage of * Chandra*'s unprecedented observational capabilities
and be able to analyze data in up to four dimensions
(energy or wavelength , time , and spatial location
) with a wide variety of models, optimization methods, and
fit statistics. The enhancements that we have made to * Sherpa*
for the CIAO 2.0 release, described below,
represent major steps towards this goal.

Previous versions of * Sherpa* allowed the user to input
background data with the commands ` BACK` or ` READ BACK`,
but these data could only be subtracted from the source data.
* Sherpa* now allows the simultaneous
analysis of one (or two) background dataset(s)
for every source dataset that is read in.
A background model is fit directly to the background
data, and is also extrapolated to the source region, where it is added
to the source model before convolution.
Rescaling for different extraction region
sizes is done using the values of the ` BACKSCAL` keyword,
set in the header of the PHA files containing source and
background data, using the commands ` SETDATA` and ` SETBACK`.

* Sherpa* contains many new methods that one can use to estimate
confidence intervals or visualize confidence regions for best-fit
model parameters. Note that these methods are strictly valid,
i.e., provide 1 confidence intervals that actually
contain 68.3% of the
integrated probability, when (1) the or
(log-likelihood) surface in parameter
space is approximately shaped like a multi-dimensional
paraboloid, and (2)
the best-fit point is sufficiently far from parameter space boundaries.

Below we list other enhancements to * Sherpa* made
for the CIAO 2.0 release.

- We have extensively retooled the algorithms for the
optimization methods
`POWELL`,`SIMPLEX`, and`LEVENBERG-MARQUARDT`to make them more robust. - The parameter value guessing algorithm now takes into account the exposure time and ARF if PHA spectral data are input.
- One can use ARFs and RMFs with different photon-space binning.
- One can simulate one-dimensional spectra with
`FAKEIT`. - One can define two-dimensional spatial models in either image coordinates or in the World Coordinate System (WCS).
- New models other than
`ngauss`and`delta`include a broken power law (`bpl`), one- and two-dimensional constants (`const`and`const2d`), a two-dimensional delta function (`delta2d`), a phenomenological photoionization edge model (`edge`), and a line broadening model (`linebroad`). - One can set preferences in a
`.sherparc`file in the home directory.

This project is supported by the * Chandra* X-ray
Center under NASA contract NAS8-39073.

Doe, S., Noble, M., & Smith, R. 2001, this volume, 310

Doe, S., Ljungberg, M., Siemiginowska, A., & Joye, W. 1998, in ASP Conf. Ser., Vol. 145, Astronomical Data Analysis Software and Systems VII, ed. R. Albrecht, R. N. Hook, & H. A. Bushouse (San Francisco: ASP), 157

Rots, A., McDowell, J., Wise, M., He, H., & Freeman, P. 2001, this volume, 479

- ... space.
^{1} -
Models in the
*XSPEC*v.10 library are available to users of CIAO 2.0, while the v.11 library will be available starting with CIAO 2.1. - ... spaces.
^{2} -
The reader will find
more information about
`ANALYSIS`, as well as all other*Sherpa*commands, at`http://asc.harvard.edu/ciao/documents_manuals.html`. - ... errors.
^{3} -
Flux errors are easily estimated for three
*Sherpa*models for which the amplitude is equal to the flux: the normalized Gaussian (`ngauss`); the delta function (`delta`); and the Lorentzian (`lorentz`).

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