Keeping the Chandra Satellite Cool with Python
Tom Aldcroft
The Chandra X-ray Observatory has been providing groundbreaking astronomical
data since its launch by NASA in July of 1999. Now starting the second decade
of science the Chandra operations team has been using Python to create
predictive thermal models of key spacecraft components. These models are being
used in the mission planning and command load review process to ensure that the
series of planned observations and attitudes for each week will maintain a safe
thermal environment. Speaking from my perspective as a scientist working to
create and calibrate the models, I will discuss the process and the key
off-the-shelf tools that made it all possible. This includes fitting
many-parameter models with the Sherpa package, parallel computation with
mpi4py/MPICH2, large table manipulations with pytables/HDF5, and of course fast
array math with NumPy.
telescope, NASA, MPI, astronomy, control
DOI10.25080/Majora-92bf1922-000