Using Python with Smoke and JWST Mirrors
Warren J. Hack
Perry Greenfield
Babak Saif
Bente Eegholm
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
DOI10.25080/Majora-92bf1922-008