Distortion Correction and Astrometric Solution
Users should be aware that the LBTI was not designed as an astrometric instrument. Thus, the astrometric precision is limited and great care should be exercised when deriving and using astrometric measurements from LBTI data. In the following, we describe the procedure to correct LMIRCam images for optical distortion and to derive a plate scale and true North measurement of the images. The required data for this are part of routine instrument calibrations and are obtained at regular intervals by the instrument team. Maire et al. (2015) provide a good description of their application of the methods outlined here. The tools and data used are described in more detail on this page. If you make use of these tools, please give appropriate credit as indicated under ‘attribution‘.
Optical Distortion Correction
LMIRCam images are subject to significant optical distortion and we highly recommend correcting it on any images. Optical distortion is measured by imaging a pinhole grid inserted at the entrance of NIC. This corrects for distortion of all optics downstream of the pinhole grid, but it is important to note that the typically small residual distortion from several optics upstream of the pinhole grid will not be measured (see astrometric solution below for a potential way to correct for the remaining distortion).
The position of the pinholes in the images can be measured and a solution can be derived that distorts the image in a way that the positions form a cartesian grid. This is the distortion that needs to be applied to any science images to correct for the optical distortion of the instrument. In the following we provide for download the reduced pinhole grid images used to derive distortion solutions and the distortion matrices derived.
Downstream of the pinhole grid, all optics are the same for the beams from the left (sx) and right (dx) beams of the telescope. Thus, there should not be a significant difference between the matrices derived from sx, dx, or double sided images. However, optics are hit at a lightly different angle and in a slightly different position for the two sides, so that in the future matrices for the individual sides will be provided.
Users can apply the distortion matrices using their own tools or use a basic Python package provided by our team (click here to download) where the appropriate matrices are simply copied into the code before running. The Python code has been run using Python 3.6.3 and recent versions of common libraries. We encourage our users to apply any correction to the corresponding pinhole image and to visually inspect the result as a test to their procedure. The distortion correction is typically applied to science frames after all pixel-specific corrections (e.g., dark/bias/nod subtraction, bad pixel correction) as it distorts the original image, but before any de-rotation or other morphing of the images as otherwise the effects of distortion would have to be tracked through these operations.
Note that the distortion corrections have been derived for the full 2048×2048 pixel images, but are only valid for the area of the image where pinholes are clearly visible. The easiest way to apply the correction to subframe images is to insert the smaller image at an appropriate position in an empty 2048×2048 image before applying the correction and then to crop again around the science image. An alternative may be to use the solution on a 2048×2048 image and to record the shifts for each pixel. The shifts to the relevant pixels can then be applied to the subframes images only rather than padding each image. This option has, however, not yet been explored by our team.
Older data have the subframe information in the fits headers in the keywords starting with ‘SUBSEC’. Newer data are almost exclusively taken in full frame or the ‘center stripe’ section of the detector which represents the central 1024 rows of the full frame. In case the subsection cannot be determined by the user, they should ask their LBTI team contact for clarification.
True North and Pixel Scale
Our team regularly observes the Trapezium cluster and uses the coordinates from Close et al. (2012) to derive an astrometric solution for LMIRCam. The information will be provided to our users here in the near future. In the mean time, the raw Trapezium data can be made available to our users upon request to derive their own astrometric solutions. Given the relatively dense stellar field that is mapped on the detector and the known coordinates of the stars, these observations can in principle also be used to derive a complete and precise distortion correction of the full optical system. This has not yet been attempted by the LBTI team or to our knowledge by any user. It may, however, be considered by expert users if a particularly high level of precision is required.
| coeff_lmir_double_161122.dat (1k) | Steve Ertel, Jan 16, 2020, 6:29 PM | v.4 | Download |
| coeff_lmir_double_171108.dat (1k) | Steve Ertel, Jan 16, 2020, 6:29 PM | v.4 | Download |
| coeff_lmir_double_190919.dat (1k) | Steve Ertel, Jan 16, 2020, 6:29 PM | v.4 | Download |
| coeff_lmir_dx_171108.dat (1k) | Steve Ertel, Jan 16, 2020, 6:29 PM | v.4 | Download |
| coeff_lmir_dx_20200102.rtf (1k) | Queue Scheduling | v.2 | Download |
| coeff_lmir_dx_20210521.rtf (48k) | Queue Scheduling | v.1 | Download |
| coeff_lmir_dx_20210521_strip.rtf (42k) | Queue Scheduling | v.1 | Download |
| coeff_lmir_sx_171108.dat (1k) | Steve Ertel, Jan 16, 2020, 6:30 PM | v.4 | Download |
| coeff_lmir_sx_191119.dat (1k) | Steve Ertel, Jan 28, 2020, 12:25 PM | v.1 | Download |
| coeff_lmir_sx_20200102.rtf (1k) | Queue Scheduling, Jan 29, 2020, 8:25 PM | v.2 | Download |
| dewarp_package.zip (15k) | Steve Ertel, Jan 16, 2020, 6:51 PM | v.3 | Download |
| pinholes_lmir_double_161122.fits (1 | Steve Ertel, Jan 16, 2020, 2:30 PM | v.3 | Download |
| pinholes_lmir_double_171108.fits (16400k) | Steve Ertel, Jan 16, 2020, 2:36 PM | v.3 | Download |
| pinholes_lmir_double_190919.fits (32771k) | Steve Ertel, Jan 16, 2020, 2:48 PM | v.3 | Download |
| pinholes_lmir_dx_171108.fits (16400k) | Steve Ertel, Jan 16, 2020, 2:43 PM | v.3 | Download |
| pinholes_lmir_dx_20200102.fits (32771k) | Queue Scheduling, Jan 29, 2020, 8:30 PM | v.3 | Download |
| pinholes_lmir_sx_171108.fits (16400k) | Steve Ertel, Jan 16, 2020, 2:41 PM | v.3 | Download |
| pinholes_lmir_sx_191119.fits (32771k) | Steve Ertel, Jan 28, 2020, 12:26 PM | v.1 | Download |
| pinholes_lmir_sx_20200102.fits (32771k) | Queue Scheduling, Jul 20, 2021, 2:59 PM | v.2 | Download |
| pinholes_lmir_sx_20210521.fits (32771k) | Queue Scheduling, Jul 20, 2021, 2:59 PM | v.1 | Download |
| pinholes_lmir_sx_20210521_strip.fits (16388k) | Queue Scheduling, Jul 20, 2021, 2:59 PM | v.1 | Download |
