Near Real-Time Photometric Data Processing for the Solar Mass Ejection Imager (SMEI)

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Scientific paper

The Solar Mass Ejection Imager (SMEI) records a photometric white-light response of the interplanetary medium from Earth over most of the sky in near real time. In the first two years of operation the instrument has recorded the inner heliospheric response to several hundred CMEs, including the May 28, 2003 and the October 28, 2003 halo CMEs. In this preliminary work we present the techniques required to process the SMEI data from the time the raw CCD images become available to their final assembly in photometrically accurate maps of the sky brightness relative to a long-term time base.
Processing of the SMEI data includes integration of new data into the SMEI data base; a conditioning program that removes from the raw CCD images an electronic offset ("pedestal") and a temperature-dependent dark current pattern; an "indexing" program that places these CCD images onto a high-resolution sidereal grid using known spacecraft pointing information. At this "indexing" stage further conditioning removes the bulk of the the effects of high-energy-particle hits ("cosmic rays"), space debris inside the field of view, and pixels with a sudden state change ("flipper pixels").
Once the high-resolution grid is produced, it is reformatted to a lower-resolution set of sidereal maps of sky brightness. From these sidereal maps we remove bright stars, background stars, and a zodiacal cloud model (their brightnesses are retained as additional data products). The final maps can be represented in any convenient sky coordinate system. Common formats are Sun-centered Hammer-Aitoff or "fisheye" maps. Time series at selected locations on these maps are extracted and processed further to remove aurorae, variable stars and other unwanted signals. These time series (with a long-term base removed) are used in 3D tomographic reconstructions.
The data processing is distributed over multiple PCs running Linux, and, runs as much as possible automatically using recurring batch jobs ('cronjobs'). The batch scrips are controlled by Python scripts. The core data processing routines are written in several computer languages: Fortran, C++ and IDL.

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