Data Reduction
We have created a Python-based data reduction pipeline that leverages PypeIt to handle raw data products from DMD-MOS and perform standard data reduction steps to output science-ready spectra.
Leveraging PypeIt
PypeIt is an open-source, Python-based data reduction pipeline for astronomical spectroscopic data. It is designed to handle a variety of spectrograph configurations and provides a modular framework for data reduction tasks such as bias subtraction, flat-fielding, wavelength calibration, sky subtraction, and spectral extraction. PypeIt is widely used in the astronomical community due to its flexibility and ease of use. These attributes make it an ideal framework on which to build custom data reduction pipelines for novel instruments like DMD-MOS. The pipeline is under development but we have successfully used it to reduce multi-object DMD-MOS data taken in the lab and will continue testing the pipeline as we prepare for on-sky testing. See the images below for example pipeline outputs.
Wavelength calibration output showing fitted arc lines from a HgNe lamp for one slit from a multi-slit reduction. The green text shows the identified arc lines while the right half of the figure shows the fitted wavelength solution and fit residuals. From this, we obtain a wavelength solution with fit residuals better than ~0.5 Angstroms.
QA product for one slit from a multi-slit reduction showing successful object detection along spatial-direction pixel 1031. The reduction steps in the pipeline after this initial detection use this information to optimally extract the 1D spectrum.