Speaker
Description
BlueMUSE is going to be an integral field spectrograph similar to MUSE but cover a more blue wavelength range than MUSE. As the two instruments are similar, the data reduction pipeline of BlueMUSE will be based on the pipeline for MUSE. While the MUSE pipeline does propagate the variance of pixels during the resampling into datacubes, it currently does not consider covariances. This can cause an underestimation of the flux uncertainties, which in turn can affect the uncertainties and values of derived spectral parameters.
In this presentation, we introduce our approach to handling covariances between voxels in the MUSE data reduction pipeline, which is also applicable to BlueMUSE. While it is possible to derive and save all covariances in a MUSE observation, it is not very practical to handle these large datasets for various post-processing steps. We found an approximation for the covariances that is a correction of the already existing variance cube that makes handling the covariance information trivial. We will detail this approach and show its strengths in reproducing the true covariance correction on flux uncertainties, but also its limitations.
| Affiliation of the submitter | Georg-August-Universität Göttingen |
|---|---|
| Attendance | in-person |
