Parent page: MIRI Instrumentation → MIRI Detector Overview → MIRI Detector Readout Overview

Since science cases that require extreme data rates are somewhat specialized, co-addition in MIRI FAST mode should be an optional readout pattern used less frequently than standard readout patterns.

For MIRI Imager or MRS observations of bright objects or high backgrounds that integrate for a day or more, a FAST 1 mode co-addition is available.  FAST mode co-addition is most useful when considering onboard data storage limits.  Several cases are described in detail by Friedman & Meixner (2006), which include:

• one array in FAST mode all day: MIRI imaging at 25.5 μm in deep surveys of cosmological fields, such as the HST Ultra Deep Field (SODRM 401; Petro et al. 2005);
• two arrays in FAST mode all day: MIRI MRS of transiting planets for half an orbital period (~1.5 days; Meixner et al. 2005);
• running all 3 arrays simultaneously in FAST mode (e.g., parallel calibrations).

This mode is also implemented for target acquisition to to keep within limits on onboard data volume.

FAST mode co-addition is currently implemented using a mode referred to as group average (FASTGRPAVG).  For FASTGRPAVG, the MIRI FPE reads out the detectors as if it was just FAST mode since the FPE has no frame processing capability of its own. The co-addition itself is performed by the ICDH focal plane array processor (FPAP) by averaging on a pixel-by-pixel basis as follows:

output pixel =  ${\frac{1}{N}\sum_{i = 1}^{N}m_i}$

where mi is the ith sample in a series of N consecutive pixel values. N must be a power of 2. The division by N to compute the average from the sum is done by bit shifting, which is a rapid and efficient method of dividing by a power of 2.

The readout scheme for FASTGRPAVG is illustrated in Figure 1.  Integration times appropriate for this mode are from 30–1,000 s, or 10–330 groups.  In this case, co-addition averages will be formed over N = 4 integrations, which is adequate to fit within data volume constraints with some margin in case the data compression is worse than expected.

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# References

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