Candidate detections will create visibility data to be archived. However, many candidates will be bad and should be cut before archiving.
Initially, this will require human feedback ("Astronomer on duty", AOD) to remove bad candidates and reduce the archived data rate. It is expected that this can be done on a ~day cadence.
Observing control interface should be able to control candidate rate (e.g., set threshold for given SB)
Need a plan to go from duty astronomer to NRAO (autonomous) system
Does this require 15 min a day? If so, NRAO can handle via data analyst.
If longer, we need to reduce output somehow. ML classifier?
Candidate detections will create visibility data to be archived. However, many candidates will be bad and should be cut before archiving.
Initially, this will require human feedback ("Astronomer on duty", AOD) to remove bad candidates and reduce the archived data rate. It is expected that this can be done on a ~day cadence.