SSTRED: A data-processing and metadata-generating pipeline for CHROMIS and CRISP

We present a data pipeline for the newly installed SST/CHROMIS imaging spectrometer, as well as for the older SST/CRISP spectropolarimeter. The aim is to provide observers with a user-friendly data pipeline, that delivers science-ready data with the metadata needed for archival. We generalized the CRISPRED data pipeline for multiple instruments and added metadata according to recommendations worked out as part of the SOLARNET project. We made improvements to several steps in the pipeline, including the MOMFBD image restoration. A part of that is a new fork of the MOMFBD program called REDUX, with several new features that are needed in the new pipeline. The CRISPEX data viewer has been updated to accommodate data cubes stored in this format. The pipeline code, as well as REDUX and CRISPEX are all freely available through git repositories or web download. We derive expressions for combining statistics of individual frames into statistics for a set of frames. We define a new extension to the World Coordinate System, that allow us to specify cavity errors as distortions to the spectral coordinate.Comment: Draf

Multi-frame blind deconvolution and phase diversity with statistical inclusion of uncorrected high-order modes

Images collected with ground-based telescopes suffer blurring and distortions from turbulence in Earth's atmosphere. Adaptive optics (AO) can only partially compensate for these effects. Neither multi-frame blind deconvolution (MFBD) nor speckle techniques restore AO compensated images to the correct power spectrum and contrast. MFBD can only compensate for a finite number of low-order aberrations, leaving a tail of uncorrected high-order modes. Speckle restoration of AO-corrected data depends on calibrations of the AO corrections and assumptions regarding the height distribution of atmospheric turbulence. We seek to develop an improvement to MFBD that combines speckle's usage of turbulence statistics to account for high-order modes with the ability of MFBD to sense low-order modes that can be partially corrected by AO and/or include fixed or slowly changing instrumental aberrations. We modify the image formation model, supplementing the fitted low-order wavefront aberrations with tails of random high-order aberrations that follow Kolmogorov statistics, scaled to estimated or measured values of Fried's parameter, r0, that characterize the strength of the seeing at the moment of data collection. We refer to this as statistical diversity (SD). We test MFBD with SD with noise-free synthetic data, simulating many different r0 and numbers of AO-corrected modes. SD improves the contrasts and power spectra of restored images, both in accuracy and in consistency with varying r0, without penalty in processing time. With focus diversity (FD), the results are almost perfect. SD also reduces errors in the fitted wavefront parameters. MFBD with SD and FD seems robust with respect to several percents of error in r0. Adding SD to MFBD shows great promise for improving contrasts and power spectra in restored images. Further studies with real data are motivated.Comment: Submitted to Astronomy & Astrophysics. Abstract is abridge

GNU Data Language 1.0: a free/libre and open-source drop-in replacement for IDL/PV-WAVE

GNU Data Language (github.com/gnudatalanguage/gdl) release for the Journal of Open Source Software manuscript