Pandeia

Introduction to Pandeia for WFIRST

Simulated high-redshift galaxy with a superimposed supernova
Simulated high-redshift galaxy with a superimposed supernova.

Pandeia is the Exposure Time Calculator (ETC) system that is being developed for the James Webb Space Telescope (JWST). It's based on a Python engine that calculates three-dimensional data cubes from user-specified spatial and spectral properties of one or more sources. The cubes are projected to a detector plane given an instrument configuration and two-dimensional pixel-by-pixel signal and noise properties are extracted. This allows for appropriate handling of realistic point spread functions (as calculated by WebbPSF), MULTIACCUM detector readouts, correlated detector readnoise, dithering, and multiple photometric and spectroscopic extraction strategies. Pandeia includes support for a variety of observing modes and has a highly modular, data-driven design that allows for easy extensibility to other instruments and telescopes.

This extensibility has been applied to create an implementation of the WFIRST Imager (WFI), as it is currently prototyped.

 

Functionality

Pandeia is designed to perform high-fidelity modeling of a small, representative portion of a detector image and to allow for extensive parameter space investigations. This typically small "postage-stamp" field of view is referred to as the "scene" and is composed of one or more astronomical sources. The size of the scene is dynamic and can in principle be arbitrarily large. However, because of the detail involved in the calculations Pandeia performs, calculations for very large scenes are not currently supported. STIPS is the more appropriate tool for simulating full fields of view.

Pandeia supports both point and extended sources. Extended sources are modeled by a Sérsic surface brightness profile with major/minor axis scale lengths, a position angle, and a Sérsic index (e.g., n=1 for exponential disk, n=0.5 for Gaussian, and n=4 for de Vaucouleurs). A variety of source spectra are available for use, including power-law, blackbody, stars (via a grid of PHOENIX models), HST calibration sources, and integrated spectra of a range extragalactic objects (via Brown et al. (2014)). It is also possible to add emission and absorption lines to a spectrum as well as input custom spectra. Normalization of source flux is accomplished by providing a flux density (e.g., mJy or AB mag) at a specific wavelength or a magnitude in a specific bandpass (e.g., SDSS z).

The output of a Pandeia calculation provides two-dimensional signal-to-noise maps as well as extracted flux and signal-to-noise products that are defined by a flux extraction strategy. For WFIRST imaging, this consists of aperture photometry with a circular source aperture and annular background estimation region. WFIRST Integral Field Unit (IFU) will support strategies that use dithers to facilitate background subtraction.

 

Documentation

The Pandeia engine has been developed to be data driven and flexible enough to support multiple missions. Thus, while the majority of the Pandeia documentation written to date has been written for the JWST implementation of Pandeia, the same computations are performed on WFIRST data, and the same functionalities for setting up calculations, including source and scene creation, are available. Pontoppidan et al. (2016) describes the general approach, features, and design of Pandeia. Users may also find it helpful to review the JWST documentation for an overview of the features and functionality of the Pandeia engine and an explanation of the quantities calculated by Pandeia.

The Pandeia engine and WFIRST data package is available for download and installation on the user's own computer via PyPI (the Python Package Index). To aid users interested in getting started with STScI’s simulation tools for WFIRST, including the WFIRST implementation of Pandeia, we have written tutorial Jupyter notebooks, available from GitHub. The introductory notebook contains examples and documentation about how to customize the calculation inputs and analyze the outputs. The GitHub repository also includes instructions for installing Pandeia locally, as well as instructions for installing STScI’s simulation tools WebbPSF and Pandeia in a self-contained installation using Docker. This is the suggested option for users who are less familiar with Python.

The WFIRST Pandeia functionality is still in development. The present implementation is available to the community as a beta version.

 

Assumptions and Caveats

Pandeia functionality in general and its WFIRST functionality in particular is still in continued development. The present implementation is available to the community as a beta version.

The WFIRST Mission is not yet in development and observatory designs continue to evolve. Hence, Pandeia simulations may not accurately reflect the actual future observatory.

At this stage the model for the WFI makes several assumptions and approximations:

  • The Pandeia WFIRST WFI model is based on the Cycle 7 WFIRST design revision and incorporates information from the GSFC Instrument Reference Information files.
  • PSFs are obtained using the WebbPSF-WFIRST software for a notional point within the WFI field-of-view. The field-dependence of the PSF is not currently accounted for within Pandeia.
  • The filter transmission for broadband PSF and Pandeia calculations is assumed to be flat across the filter bandpass.
  • The instrument modes, including details such as available readout patterns and subarray configurations, are modeled after those currently planned for JWST's NIRCam imager (including the NIRCam imaging and grism modes) and NIRSpec IFU.

 

Credits, Acknowledgements, and Feedback

Pandeia is developed by the ETC team at STScI.

Users are encouraged to address questions, suggestions, and bug reports to help@stsci.edu with "Pandeia-WFIRST question" in the subject line. The message will be directed to the appropriate members of the Pandeia-WFIRST team at STScI.

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Questions?

Please contact help@stsci.edu with "Pandia-WFIRST Question" in the subject line.


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