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Warren McLaughlin

Publications and source records attributed to Warren McLaughlin.

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CIAO: Chandra's Data Analysis System for X-Ray Astronomy and Beyond

The Chandra Interactive Analysis of Observations (CIAO) software, developed by the Chandra X-ray Center, has been the data analysis package for the Chandra X-ray Observatory since its launch in 1999. Over nearly three decades, CIAO has grown from a small software suite into a widely used system for X-ray data analysis and beyond. CIAO provides tools for calibration, spectral, imaging, and timing analysis, together with high-level scripts and the \sherpa\ modeling and fitting application. Its modular design and unified data model allow users to build flexible analysis workflows while maintaining consistency with the Chandra data processing pipeline. Visualization capabilities are provided through integration with SAOImageDS9 and Python-based tools, and simulation components such as ChaRT and MARX extend the analysis environment to include detailed modeling of instrumental effects. In this paper we describe CIAO's design, evolution, and capabilities after 25 years of Chandra operations. We also describe its core architecture, scripting environment, modeling, visualization tools, simulation components, and testing infrastructure, as well as the documentation and user support system that have contributed to its widespread use. CIAO's continued development and broad adoption highlight its important role in X-ray astronomy and its usefulness in multiwavelength astrophysical research.

astro-ph.IM

Sherpa: An Open Source Python Fitting Package

We present an overview of Sherpa, an open source Python project, and discuss its development history, broad design concepts and capabilities. Sherpa contains powerful tools for combining parametric models into complex expressions that can be fit to data using a variety of statistics and optimization methods. It is easily extensible to include user-defined models, statistics, and optimization methods. It provides a high-level User Interface for interactive data-analysis, such as within a Jupyter notebook, and it can also be used as a library component, providing fitting and modeling capabilities to an application. We include a few examples of Sherpa applications to multiwavelength astronomical data. The code is available GitHub: https://github.com/sherpa/sherpa

astro-ph.IM