End-to-end performance modeling of the James Webb Space Telescope (JWST) Observatory

Computer Science – Performance

Scientific paper

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Scientific paper

The JWST Observatory currently under development for NASA and it's international partners contains a 6.5 meter diameter cryogenic telescope and a suite of 4 highly sensitive instruments which will collect imagery and spectroscopic data over the spectral range of 0.6 to 30 micrometers. The Observatory architecture contains a number of innovative and aggressive technologies including a light-weight primary mirror made up of 18 individually controllable segments, a large sunshield to permit stable low temperature operation, and a nested multi-loop pointing and tracking subsystem to establish milli-arc second line of sight stability. Detailed analytical models are being developed for each of the individual elements of the Observatory. The work described in this paper draws on these models so as to create a high level end-to-end model for the total Observatory. The principal thrust of this end-to-end model (OPTOOL) is to verify that the Observatory meets its overall image quality requirements. These requirements are codified in terms of Strehl ratio, encircled energy, and image anisotropy, and are applied at wavelengths of 1,2, and 5.6 micrometers. OPTOOL is implemented through Matlab (Version 7.0.1) with a Fourier optics based approach for PSF calculations, and uses a direct integration calculation to permit high spatial sampling of the PSF. Polychromatic PSFs are calculated using the Observatory band pass characteristic and an assumed constant Jansky level target. The focal plane arrays of each of the 4 instruments are also included in the model so that realistic signal with noise imagery can be simulated. Exit pupil optical path difference (OPD) maps can be generated using combinations of Zernike polynomials or shaped power spectral densities. Aberrations can be applied to the entire pupil or to the individual segments which make up the pupil. Global exit pupil OPD maps can also be imported and used to generate predicted Point Spread Functions (PSFs). Sample results are presented.

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