ASCL.net

Astrophysics Source Code Library

Making codes discoverable since 1999

Searching for codes credited to 'Vlemmings, W'

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[ascl:1402.014] ARTIST: Adaptable Radiative Transfer Innovations for Submillimeter Telescopes

ARTIST is a suite of tools for comprehensive multi-dimensional radiative transfer calculations of dust and line emission, as well as their polarization, to help interpret observations from submillimeter telescopes. The ARTIST package consists of LIME, a radiative transfer code that uses adaptive gridding allowing simulations of sources with arbitrary multi-dimensional (1D, 2D, 3D) and time-dependent structures, thus ensuring rapid convergence; the DustPol and LinePol tools for modeling the polarization of the line and dust emission; and an interface run from Python scripts that manages the interaction between a general model library and LIME, and a graphical interface to simulate images.

[ascl:1402.017] UVMULTIFIT: Fitting astronomical radio interferometric data

UVMULTIFIT, written in Python, is a versatile library for fitting models directly to visibility data. These models can depend on frequency and fitting parameters in an arbitrary algebraic way. The results from the fit to the visibilities of sources with sizes smaller than the diffraction limit of the interferometer are superior to the output obtained from a mere analysis of the deconvolved images. Though UVMULTIFIT is based on the CASA package, it can be easily adapted to other analysis packages that have a Python API.

[ascl:1912.019] STACKER: Stack sources in interferometric data

STACKER stacks sources in interferometric data, i.e., averaging emission from different sources. The library allows stacking to be done directly on visibility data as well as in the image domain. The code is in format of a CASA (ascl:1107.013) task and implements uv- and image-stacking algorithms; it also provides several useful tasks for stacking related data processing. It allows introduction and stacking of random sources to estimate bias and noise, and also allows removal of a model of bright sources from the data.