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Using Python with Smoke and JWST Mirrors

Warren J. Hack
Space Telescope Science Institute

Perry Greenfield
Space Telescope Science Institute

Babak Saif
Space Telescope Science Institute

Bente Eegholm
Space Telescope Science Institute


We will describe how the Space Telescope Science Institute is using Python in support of the next large space telescope, the James Webb Space Telescope (JWST). We will briefly describe the 6.5 meter segmented-mirror infra-red telescope, currently planned for a 2014 launch, and its science goals. Our experience with Python has already been employed to study the variation of the mirror and instrument support structures during cyrogenic cool-down from ambient temperatures to 30 Kelvin with accuracies better than 10 nanometers using a speckle interferometer. Python was used to monitor, process (initially in near real-time) and analyze over 15 TB of data collected. We are currently planning a metrology test that will collect 10 TB of data in 7 minutes. We will discuss the advantages of using Python for each of these projects.


astronomy, telescope, NASA, measure, real-time, big data



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