Davis, John E., Bautz, Marshall W., Dewey, Daniel, Heilmann, Ralf K., Houck, John C., Huenemoerder, David P., Marshall, Herman L., Nowak, Michael A., Schattenburg, Mark L., Schulz, Norbert S., and Smith, Randall K. 2012. "Raytracing with MARX: x-ray observatory design, calibration, and support." Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series 8443:https://doi.org/10.1117/12.926937
MARX is a portable ray-trace program that was originally developed to simulate event data from the trans- mission grating spectrometers on-board the Chandra X-ray Observatory (CXO). MARX has since evolved to include detailed models of all CXO science instruments and has been further modified to serve as an event simulator for future X-ray observatory design concepts. We first review a number of CXO applications of MARX to demonstrate the roles such a program could play throughout the life of a mission, including its design and calibration, the production of input data products for the development of the various software pipelines, and for observer proposal planning. We describe how MARX was utilized in the design of a proposed future X-ray spectroscopy mission called ÆGIS (Astrophysics Experiment for Grating and Imaging Spectroscopy), a mission concept optimized for the 0.2 to 1 keV soft X-ray band. ÆGIS consists of six independent Critical Angle Transmission Grating Spectrometers (CATGS) arranged to provide a resolving power of 3000 and an effective area exceeding 1000 cm2 across its passband. Such high spectral resolution and effective area will permit ÆGIS to address many astrophysics questions including those that pertain to the evolution of Large Scale Structure of the universe, and the behavior of matter at very high densities. The MARX ray-trace of the ÆGIS spectrometer yields quantitative estimates of how the spectrometer's performance is affected by misalignments between the various system elements, and by deviations of those elements from their idealized geometry. From this information, we are able to make the appropriate design tradeoffs to maximize the performance of the system.