CALPRODUCT-NI-009: NISP Inoculation (DEACTIVATED)¶
Deactivated. The reason is that the impact of inoculation on nonlinearity (at the faint end) has not been investigated. While spotty inoculation will occur naturally in flight from supersaturated stars, it is not clear whether massive flooding of all pixels and the associated high currents and fields may change the diode juntion in the H2RGs, perhaps causing other effects that would not be seen in survey data otherwise. Therefore, deep inoculation is not foreseen in-flight. Shallow inoculation will occur by means of the monthly small-scale flats.
Parent requirement¶
Scheduling¶
Monthly.
Time-critical¶
No.
Objective¶
Inoculation is the process of deeply saturating the NISP detectors, possibly repeatedly. Tests have shown that afterwards the overall amount of persistence can be significantly reduced by factors of a few, over timescales of weeks. Inoculation appears to affect the fastest traps, only (those with detrapping timescales of a few 10 minutes).
Persistence has been characterized on ground only when the detectors were turned on warm. In flight, detectors are turned on cold, meaning that in flight we do not have accurate persistence models. Our aim is to reduce persistence further using inoculation, to minimize the fraction of masked pixels, and possibly to have a simpler masking procedure.
Fulfilled by¶
In-orbit duration¶
Data volume¶
17600 MB, assuming we take 200 photo-MACC darks over 5 hours after saturation. The cadence longer into the tail can be reduced, e.g. if we run into a telemetry limit with the parallel VIS exposures (nonlinearity or PSF).
Processing input¶
Ground Processing Input Data: Darks (without persistence)
Data Description: 10 deeply saturated NI-CU flats, and on the order of 200 darks.
Processing method¶
Measure the decay of the persistence signal after a standard set of LED flats was taken. This has to be done within super-pixels (of yet undefined size) to ensure sufficient S/N.
Processing output¶
Updated persistence factors. It is assumed that the time constants do not change, just their amplitudes and relative contributions.
Required accuracy, constraints¶
Must be able to deeply saturate the detectors with NI-CU.
Processing tools¶
Manual tools.
Validation¶
The underlying physics of inoculation is poorly understood, and only few characterization data are available. Nothing is known about this effect for the detectors in their in-flight state (powered on when cold), and thus reference criteria against which inoculation could be benchmarked and compared to are unavailable at this time.
The monthly observations outlined above allow to quantify the effect of inoculation, and hence will provide a reference point early in the survey against which future inoculation procedures can be compared to.
Recovery¶
Assume a scenario in which we observe a change / evolution over time in the inoculation effect.
We know too little to decide if this change is expected and predictable (i.e. a consequence of
repeated inoculations) or not, and hence whether the associted CalProduct must be repeated or not.
Since currently inoculation is not planned in-flight, validation and recovery procedures are not being developed.
Quality control parameters¶
DataModel: https://gitlab.euclid-sgs.uk/
Contact person¶
NISP-P calibration scientist