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3.10 Transient recognition

synopsis:  (1) residual systematic uncertainty, in case the stability criterion is satisfied, the residual uncertainty is less than 5%, (2) residual systematic uncertainty, in case the stability criterion is not satisfied the systematic uncertainty is higher than 5%, (3) statistical uncertainty increase due to decrease in effective integration time for partial stable measurements, (4) residual systematic uncertainty: the independent FCS measurement can be stable, partly stable or unstable, causing a additional systematic uncertainty to the sky measurements.

limitations and applicability:
In case the stability criterion is not met, no signals are discarded. A minimum of 7 signals per measurement or raster point is required to perform the analysis.

description:
Transient recognition determines whether there is a significant systematic signal variation in a measurement by applying the Mann algorithm. In case such variation is present the first half of the signals is discarded, this is repeated until a stability criterion is achieved or 7 signals are remaining. The criterion for rejection is a variation in excess of 5%.

purpose correction:
Transient responsivity variation is an important cause of systematic error which is minimized by this correction.

uncertainty/noise introduced:
The magnitude of the transient variation depends on the type of detector, flux step (positive or negative), and exposure time. A large flux step to a higher flux under-estimates and a flux step to lower fluxes over-estimates the ``true'' (i.e. stabilized at t=$\infty$) measurement signal. In multi-filter and multi-aperture AOTs the flux step is tuned to become positive. However, the flux of the FCS is often lower than the last sky measurement (i.e. negative step) which yields a negative systematic uncertainty because the detector responsivity is overestimated. The null hypothesis for drift recognition is 5%. Therefore, if the integration time is sufficiently long (>32 sec) and the transient recognition algorithm yields a stable signal after the iteration,  then it is most likely that the derived signal is within 5% of the ``true'' signal level. The same holds for the FCS measurement signal, which adds also a systematic uncertainty of at most 5% to the photometry via the systematic uncertainty in the responsivity.

auxillary data:
Parameters for the transient recognition algorithm:
Nmin = 7, minimum number of signals for correction;
$\alpha$ = 0.05, probability that the null-hypothesis is rejected.

keyword(s):
DRALPHA: significance level SPD header
DRMINPTS: min. no. of points for Mann-test SPD header
FITDRn: Drift fit flag (T or F, n=measurement number) SPD header


next up previous contents
Next: 3.11 Signal averaging per Up: 3. Derive SPD level Previous: 3.9 Discarding signals in
ISOPHOT Error Budgets: Derive_SPD Processing Steps, Version 1.0, SAI/98-091/Dc