13 August 2014 A generalized least square algorithm to process infrared data taken in non-destructive readout mode
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Abstract
We present a general algorithm to perform the linear fit of non-destructive ramps, the most common readout mode of IR detectors in Astronomy. The algorithm is based on the Generalized Least Square Method, appropriate when the data are heteroscedastic and correlated, and uses a covariance matrix accounting for readout noise, correlated Poisson noise of the integrated signal, group-averages, and digitization noise. The basic algorithm is expanded to allow for detection and removal of cosmic rays within the ramp on solid statistical ground. The procedure returns a statistically accurate estimate of the ramp’s slope, intercept and of the intensity of possible cosmic rays together with their associated uncertainties and correlation terms. An example of implementation exploiting IDL’s matrix operators is provided in the Appendix.
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M. Robberto, M. Robberto, } "A generalized least square algorithm to process infrared data taken in non-destructive readout mode", Proc. SPIE 9143, Space Telescopes and Instrumentation 2014: Optical, Infrared, and Millimeter Wave, 91433Z (13 August 2014); doi: 10.1117/12.2060114; https://doi.org/10.1117/12.2060114
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