Glossary#
Key terms used throughout Pyralysis:
- Imaging (image formation, image synthesis)
Forming an image from interferometric visibilities. In radio astronomy this is the usual name for the task; CASA and similar packages call it imaging or image synthesis. Pyralysis docs and APIs also say reconstruction and image optimization for the same broad family of methods (dirty mapping, CLEAN-style workflows, and regularized / RML optimization). Prefer imaging in user-facing prose when talking to observatory users; code packages may still use
reconstruction.- Reconstruction
Synonym for imaging / image synthesis in Pyralysis. Often used when the image is obtained by minimizing an objective (data fidelity + regularizers) rather than by a CLEAN-style minor cycle alone. See also Optimization in Pyralysis.
- Image optimization
Imaging via gradient-based or proximal algorithms (RML / compressed sensing). Same scientific goal as imaging; emphasizes the optimizer stack (Optimization in Pyralysis, Optimizers).
- Dataset
The main in-memory container for interferometric data in Pyralysis. It holds metadata (antenna, baseline, field, spectral windows, polarization, observation) and a list of SubMS (
ms_list) that contain the actual visibility data. Returned by the simulator (e.g.sim.simulate(create_dataset=True)) or by I/O readers such as DaskMS.- SubMS (sub–measurement set)
A partition of the measurement set by field and spectral window. Each SubMS has an id, field_id, spw_id, polarization_id, and a VisibilitySet with the visibility arrays (DATA, UVW, weights, etc.) for that partition. The Dataset’s
ms_listis a list of SubMS; one SubMS for single field/spw, multiple for multi-field or multi–spectral-window data. Used by dask-ms and Pyralysis for efficient I/O and per-partition processing.- RML (Regularized Maximum Likelihood)
An imaging method that uses regularization to improve solutions.
- Measurement operator
The forward model that maps a model image to model visibilities at irregular UV coordinates. It applies (optionally) primary beam and intensity scaling, 2D FFT, phase shift, then samples the Fourier grid at observed UV positions using nearest neighbor, bilinear interpolation, or degridding.
- Gridding
Interpolating Fourier space data onto a uniform grid.
- Degridding
Visibility estimation from a Fourier grid using a convolution kernel (inverse of gridding). One of the three visibility-estimation methods in the measurement operator.