Page:SATCON2 Algorithms Report.pdf/31

  3.3.4. TrailAssess

We need to assess what the scientific impact of trails has been on our images. One way to do this is to take two images of the same field, one unaffected and one affected (either with trails, or still degraded after trail removal). These could be real images (with different epochs), or a pair of simulated images with and without trails. One metric of the effect on science is to detect and parameterize sources in the field, and compare the derived source list and source parameters before and after degrading the image with trails.

Inputs:  Simulated image without trails, output from ImageSimulate Simulated image with trails, output from TrailSimulate or from TrailMask (with trails removed at some level) Trail catalog (from TrailMask) Data reduction parameters, to be determined 

Outputs:
 * 1) Point source detection list with source parameters for both images
 * 2) Extended source detection list with source parameters for both images
 * 3) Detection efficiency and photometric accuracy for both lists
 * 4) Sensitivity limit for both lists
 * 5) Derived output: percentage degradation in source detection efficiency vs brightness percentage degradation in detection threshold.

3.3.5. Simulation assessment

This is not a software application per se. We are also tasked with aggregating the simulation results generated by the tools described in the preceding subsection. and interpreting them, summarizing them for the community.

We will need to define a set of simulations to cover the relevant parameter spaces and provide sufficient data for an assessment, then actually run the simulations. Then we need to generate summary trend plots and tables versus time of year, observatory location, etc., for different types of observation/ science, different telescopes, and for different constellation scenarios. These will allow us to provide recommendations on desired limits on trails and make progress on suggesting corresponding limits on various types of satellite. Rh