MAISIE: a multipurpose astronomical instrument simulator environment

Alan O'Brien; Steven Beard; Vincent Geers; Pamela Klaassen

doi:10.1117/12.2231649

26 July 2016 MAISIE: a multipurpose astronomical instrument simulator environment

Alan O'Brien, Steven Beard, Vincent Geers, Pamela Klaassen

Proceedings Volume 9913, Software and Cyberinfrastructure for Astronomy IV; 991312 (2016) https://doi.org/10.1117/12.2231649
Event: SPIE Astronomical Telescopes + Instrumentation, 2016, Edinburgh, United Kingdom

Abstract

Astronomical instruments often need simulators to preview their data products and test their data reduction pipelines. Instrument simulators have tended to be purpose-built with a single instrument in mind, and at- tempting to reuse one of these simulators for a different purpose is often a slow and difficult task. MAISIE is a simulator framework designed for reuse on different instruments. An object-oriented design encourages reuse of functionality and structure, while offering the flexibility to create new classes with new functionality. MAISIE is a set of Python classes, interfaces and tools to help build instrument simulators. MAISIE can just as easily build simulators for single and multi-channel instruments, imagers and spectrometers, ground and space based instruments. To remain easy to use and to facilitate the sharing of simulators across teams, MAISIE is written in Python, a freely available and open-source language. New functionality can be created for MAISIE by creating new classes that represent optical elements. This approach allows new and novel instruments to add functionality and take advantage of the existing MAISIE classes. MAISIE has recently been used successfully to develop the simulator for the JWST/MIRI- Medium Resolution Spectrometer.

Citation Download Citation

Alan O'Brien, Steven Beard, Vincent Geers, and Pamela Klaassen "MAISIE: a multipurpose astronomical instrument simulator environment", Proc. SPIE 9913, Software and Cyberinfrastructure for Astronomy IV, 991312 (26 July 2016); https://doi.org/10.1117/12.2231649

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