Please read the background information in the slides at
Elahe is investigating potential scheduling algorithms (note: this means, what kinds of algorithms are useful, from an operations research point of view, in developing scheduler ‘controllers’), and as part of that development, she is building prototype cost functions and evaluations of the resulting observations. Currently she is investigating ‘approximate optimal control’ solutions. The scheduling algorithms are focused on optimizing observations within a single night.
One of the questions Elahe has is how to decide whether a filter change is worthwhile or not?
The obvious cost of a filter change is the 120 second delay in observing, and perhaps this could be a weight that combines in some fashion with the slew time cost. There are some additional constraints or costs that may be desirable to include, such as preferring to change filter fewer times per night (wear and tear on the mechanisms) or fewer times per hour (the filter change time constraints from the camera team).
The benefits of filter changes would presumably be SNR depending on the phase of the moon (sky brightness in various filters) and seeing (tied into airmass, as the seeing depends on airmass and filter, as well as raw seeing at zenith) vs. the ‘best possible’ SNR for the field (minimum sky brightness and seeing/airmass), with some weighting due to amount of time the minimum vs. current SNR would be available for. I don’t know how much we have to define this in order to make it useful for Elahe, so perhaps she can weigh in with some clarifications.
@connolly has been charged with summarizing and making a final recommendation to Elahe.