UVMULTIFIT: A versatile tool for fitting astronomical radio interferometric data

By I. Martí-Vidal, W. Vlemmings, S. Muller, Simon Casey. 2014

142 citations recorded by the source corpus.

Context. The analysis of astronomical interferometric data is often performed on the images obtained after deconvolving the interferometer’s point spread function. 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. Aims. 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. Methods. The user can simultaneously fit an indefinite number of source components to the data, each of which depend on any algebraic combination of fitting parameters. Fits to individual spectral-line channels or simultaneous fits to all frequency channels are allowed. Results. We have tested the software with synthetic data and 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. Conclusions. 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.

Subfields: Astronomy and Astrophysics, Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/4c61e0a9e4214163e079e9a911b82952c22ac807

How researchers see this paper

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In Astronomy and Astrophysics

1. R. Maiolino
2. S. Aalto
3. Sylvain Veilleux
4. A. Bolatto
5. P. Hopkins
6. L. Hernquist
7. H. Netzer
8. D. Rupke

In Nuclear and High Energy Physics

1. R. Maiolino
2. Sylvain Veilleux

Citations in the corpus

• Cool outflows in galaxies and their implications (2020, methodology): “…from the analysis on the imaging data may also be checked independently by deriving the sizes and fluxes of the wing emission from a fit of the data directly in the uv plane (e.g., using CASA uv-Plane Model Fitting routines uvmodelfit and uvmultifit from the library of Martı́-Vidal et al. 2014).”
• Resolving the stellar activity of the Mira AB binary with ALMA (2015, methodology): “To analyze the uv-data directly, we used the UVMULTIFIT code (Martí-Vidal et al. 2014).”