The analysis of astronomical interferometric data is often performed on the
images obtained after deconvolution of the interferometer's point spread
function (PSF). This strategy can be understood (especially for cases of sparse
arrays) as fitting models to models, since the deconvolved images are already
non-unique model representations of the actual data (i.e., the visibilities).
Indeed, the interferometric images may be affected by visibility gridding,
weighting schemes (e.g., natural vs. uniform), and the particulars of the
(non-linear) deconvolution algorithms. Fitting models to the direct
interferometric observables (i.e., the visibilities) is preferable in the cases
of simple (analytical) sky intensity distributions. In this paper, we present
UVMULTIFIT, a versatile library for fitting visibility data, implemented in a
Python-based framework. Our software is currently based on the CASA package,
but can be easily adapted to other analysis packages, provided they have a
Python API. We have tested the software with synthetic data, as well as with
real observations. In some cases (e.g., sources with sizes smaller than the
diffraction limit of the interferometer), the results from the fit to the
visibilities (e.g., spectra of close by sources) are far superior to the output
obtained from the mere analysis of the deconvolved images. UVMULTIFIT is a
powerful improvement of existing tasks to extract the maximum amount of
information from visibility data, especially in cases close to the
sensitivity/resolution limits of interferometric observations.Comment: 10 pages, 4 figures. Accepted in A&A. Code available at
http://nordic-alma.se/support/software-tool
