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Pardon Our Dust!

This space is Under Construction. The layout is entirely notional at present.

The latest release of the Pandeia engine is 1.5.1.

Some functionality requires optional pysynphot data files

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Next Planned Release

Important

  • This version drops support for Python 2
  • This version drops pysynphot use and replaces it with Astropy-affiliated synphot and stsynphot.

Version 1.5.2 is planned to release in late August 2020.

Highlights include:

  • Users will no longer need the pysynphot data files to specify sources normalized in Vegamags
  • Additional readout pattern for the NIRSpec Target Acquisition mode

Click here for draft engine release notes

question: do we need a separate fields for engine release notes & engine known issues? so far we have been doing laborious manual work to do this at release time. Yes, we think we do.


What support is available?

Nice carefully crafted statement about level of support

What is the Pandeia Engine?

The Pandeia engine uses a pixel-based 3-dimensional approach to perform calculations on small (typically a few arcseconds) 2-dimensional user-created astronomical scenes. It models both the spatial and the wavelength dimensions, using realistic point spread functions (produced using WebbPSF) for each instrument mode. It natively handles correlated read noise, inter-pixel capacitance, and saturation. Since the signal and noise are modeled for individual detector pixels, the ETC is able to replicate many of the steps that observers will perform when calibrating and reducing their JWST data. This simplifies interpretation of the extracted signal-to-noise ratio (SNR) calculated by the ETC.  

While the JWST ETC includes many effects not typically included in other ETCs, it is not an observation simulator. It does not simulate the full detector, nor does it include 2-dimensional effects such as distortion.

Details on the algorithms used to compute signal and noise on the detector and the strategies used to compute the extracted products can be found in Pontoppidan et al. 2016.

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