LSST Progress Mockup

This mockup is intended as a tool for iterating LSST progress report design.

Currently, it does not show results based on any "real" data. The statistics it plots are currently read from data files update by hand, made using an alternate weather simulation. For production use, these statistics will be automatically generated from completed visits.

Progress as measured by scalar ("summary") metrics

Any MAF summary metric (such os those reported here) can potentially be computed and reported on either of these plots.

Two examples are shown below:

• the coadd depth in g, which shows the advantages plotting the instantaneous metric value vs. date.
• the total area with more than 750 visits in square degrees (f0Area), an example for which the extrapolated final value is a more useful measure of progress toward the final objective.

Median depth in g

In the left-hand plot below, the points and black line show the metric values at each point in time, as measured only from visits at or before that time. The green line shows the same metric values measured at these times in the baseline simulation. This kind of a plot is suitable for metric values that inclease steadily over time.

The right-hand plot below shows the final g band depth, extrapolated from the date to the end using the baseline simulation.

Total area with more than 750 visits

For some metrics, the current value does not provide a good indication of progress on that metric. For example, the value of fOArea metric (the total area that has reached a given depth) might not change much even when significant progress is being made if the progress is spread out evenly over the whole footprint.

For these metrics, the plot on the right, which shows the value extrapolated to the end of the survey, is more useful.

This value will be pessimistic, because it does not account for any response the scheduler might make to the difference in completed vs. baseline visits. A different approach is to create bespoke simulations from each date, starting the scheduler simulator with the completed visits pre-loaded and simulating to the end of the survey. The general appearance of the figure would remain much the same, however.

In the plot below, the black line and points show the metric values measured from the chimera simulations, while the green is the value from the baseline.

Hourglass plots

Hourglass plots can instantaneous values over a large period of time, e.g. a year: the colors each horizontal line within a column represent the values over that night. Hourglass plots can be additionally annotated with twilight times, moon rise, transit, and set times, and other astronomical events.

The HA of each visits represented in the sample plot below. Other good candidates for plotting in hourglass plots are time use (wide ugr, wide izy, each DDF, lost to weather, lost to instrument failure, etc.), depth, sky brightness, and seeing.

INFO:root:Working on January, 2033

INFO:root:Working on February, 2033

INFO:root:Working on March, 2033

INFO:root:Working on April, 2033

INFO:root:Working on May, 2033

INFO:root:Working on June, 2033

INFO:root:Working on July, 2033

INFO:root:Working on August, 2033

INFO:root:Working on September, 2033

INFO:root:Working on October, 2033

INFO:root:Working on November, 2033

INFO:root:Working on December, 2033

DDF Cadence

The y-axis (height of the vertical bars) represents the accumulated effective exposure time, t_eff, accumulated over all exposures on the field for the night, colored by filter. t_eff is a measure of survey depth that increases monatonically mith limiting magnitude: t_eff ∝ 10^{⅘ (m5 - m5_nom)}. The primary advantage of using t_eff over a magnitude limit is that it is addative in a coadd: the t_eff in a properly weighted coadd is the sum of the t_effs of the visits that were included in the coadd. As such, it makes sense to "stack" the t_eff values for a night in a bar plot, while stacking magnitudes is not physically meaningful. (It is called "effective exposure time" because, in the limit of noise domination by sky background photon noise and constant nominal instrument performance and observing conditions, t_eff is the accumulated exposure time in seconds.) For more details, see DMTN-296.

The plot only includes the current DDF "season."