[PIPE2D-627] Characterize changes in FRD from near-focus or in-focus images Created: 01/Sep/20  Updated: 13/Jan/23

Status: In Progress
Project: DRP 2-D Pipeline
Component/s: None
Affects Version/s: None
Fix Version/s: None

Type: Story Priority: Normal
Reporter: Brent Belland Assignee: Brent Belland
Resolution: Unresolved Votes: 0
Labels: None
Remaining Estimate: Not Specified
Time Spent: Not Specified
Original Estimate: Not Specified

Attachments: PNG File BasicFit.png     PNG File Zernike4.png    
Issue Links:
Relates
relates to PIPE2D-628 Develop algorithms to be able to meas... Open
relates to PIPE2D-630 Deliver algorithms to handle FRD extr... In Progress
relates to PIPE2D-629 Better understand the hysteresis in t... Won't Fix
relates to PIPE2D-549 Investigating extraction of FRD from ... Done
relates to PIPE2D-574 Increasing defocus effect on FRD anal... Done
Sprint: 2DDRP-2021 A

 Description   

From Jim's notes during discussion on Friday (August 29):

"The notion is that we will have images with high S/N from some standard
configuration which can be used as a template and for which we have
PSFs.  When we are on the sky with some different configuration, we need
to be able to measure the delta `FRD' to predict the PSFs in this
configuration."

This combines all of the work that I've done so far into a compact deliverable. In particular, the purpose of this ticket is to deliver code that takes in a base fiber configurations' PSFs and corresponding FRD values as well as the current fiber configurations' PSFs to output FRD values for all of the current fiber configurations.



 Comments   
Comment by Brent Belland [ 15/Sep/20 ]

I worked on characterizing the maximum variation in PSF as a change in FRD with a linear combination of Zernike coefficients Z4-Z22. BasicFit.png displays the maximum 2D variation as a function of detector position, the corresponding best fit from a linear algebra least squares solution. (https://numpy.org/doc/stable/reference/generated/numpy.linalg.lstsq.html) Unfortunately this fit does not describe the structure in much detail at all. This indicates that algorithms I develop should have data for each relevant position as inputs rather than deriving PSFs from wavefront alone.

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