Flexure Correction¶
This document will describe how a flexure correction is performed for each 1D spectrum extracted in PypeIt.
Overview¶
By default, the code will calculate a flexure shift based on the extracted sky spectrum (boxcar). A cross-correlation between this sky spectrum and an archived spectrum is performed to calculate a single, pixel shift. This is then imposed on the wavelength solution with simple linear interpolation.
The general approach is to compare the sky model from the observation with an archived sky model. Generally, by default, the Paranal sky spectrum is used, as derived from the SDSS codes. The default is different for Kast blue and LRIS blue where sky_kastb_600.fits and sky_LRISb_600.fits are respectively used (see Alternate sky models for all sky models).
Algorithm¶
The basic algorithm may be summarized as follows:
- Identify the overlapping wavelength range between data and archived sky.
- Rebin the archived sky spectrum onto the overlapping wavelength range.
3. Smooth the sky spectrum to the resolution of the data, if the archive has higher spectral resolution (preferred). 4. Normalize each spectrum to unit average sky counts 5. Subtract a bspline continuum from each 6. Perform a cross-correlation 7. Fit the cross-correlation with a parabola to find center 8. Apply shift
Usage¶
By default in ARMLSD, a flexure correction is performed on the boxcar extraction of the sky. This may be disabled by the following setting in the .pypeit file:
reduce flexure spectrum None
One can alternatively use the optimal extraction (if it is performed) with:
reduce flexure spectrum optimal
By default, the maximum shift allowed in pixels is 20. If you suspect a higher shift is required (e.g. results are poor), you may increase the default (e.g. to 50 pixels):
reduce flexure maxshift 50
Alternate sky models¶
You may find that the default sky models are not the best suited for your data.There is a script that allows the user to plot the extracted sky spectrum for their data against any of the sky models in the PypeIt archive. To use this script:
pypeit_compare_sky <Name of 1D spectrum> <Name of sky model>
As noted above, the Paranal sky model is the default reference. Presently, we are finding that the sky spectrum at Mauna Kea (measured with LRIS) is sufficiently variable and dark that a robust solution is challenging. Fair results are achieved by using the instrument-specific sky spectra in the LowRedux package. The best practice currently is to use the one that best matches as an optional parameter
You can use a different sky model than the default by placing the following line under the ‘’Reduce’’ block in your .pypeit file:
reduce flexure spectrum <Name of sky model>
The models supplied with PypeIt are,
Other¶
An alternate algorithm (activated with: reduce flexure spec slit_cen) measures the flexure from a sky spectrum extracted down the center of the slit. This is then imposed on the wavelength image so that any extractions that follow have a flexure correction already applied. Thus far, this algorithm has given poorer results than the default.