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Register a new userA joint deconvolution algorithm to combine single dish and interferometer data for wideband multi-term and mosaic imaging
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Imaging in radio astronomy is usually carried out with a single-dish radio telescope doing a raster scan of a region of the sky or with an interferometer that samples the visibility function of the sky brightness. Mosaic observations are the current standard for imaging large fields of view with an interferometer and multi-frequency observations are now routinely carried out with both types of telescopes to increase the continuum imaging sensitivity and to probe spectral structure. This paper describes an algorithm to combine wideband data from these two types of telescopes in a joint iterative reconstruction scheme that can be applied to spectral cube or wideband multi-term imaging both for narrow fields of view as well as mosaics. Our results demonstrate the ability to prevent instabilities and error that typically arise when wide-band or joint mosaicing algorithms are presented with spatial and spectral structure that is inadequetely sampled by the interferometer alone. For comparable noise levels in the single dish and interferometer data, the numerical behaviour of this algorithm is expected to be similar to the idea of generating artificial visibilities from single dish data. However, our discussed implementation is simpler and more flexible in terms of applying relative data weighting schemes to match noise levels while preserving flux accuracy, fits within standard iterative image reconstruction frameworks, is fully compatible with wide-field and joint mosaicing gridding algorithms that apply corrections specific to the interferometer data and may be configured to enable spectral cube and wideband multi-term deconvolution for single-dish data alone.
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Aims : We describe MS-MFS, a multi-scale multi-frequency deconvolution algorithm for wide-band synthesis-imaging, and present imaging results that illustrate the capabilities of the algorithm and the conditions under which it is feasible and gives accurate results. Methods : The MS-MFS algorithm models the wide-band sky-brightness distribution as a linear combination of spatial and spectral basis functions, and performs image-reconstruction by combining a linear-least-squares approach with iterative $chi^2$ minimization. This method extends and combines the ideas used in the MS-CLEAN and MF-CLEAN algorithms for multi-scale and multi-frequency deconvolution respectively, and can be used in conjunction with existing wide-field imaging algorithms. We also discuss a simpler hybrid of spectral-line and continuum imaging methods and point out situations where it may suffice. Results : We show via simulations and application to multi-frequency VLA data and wideband EVLA data, that it is possible to reconstruct both spatial and spectral structure of compact and extended emission at the continuum sensitivity level and at the angular resolution allowed by the highest sampled frequency.
The General Single-Dish Data format (GSDD) was developed in the mid-1980s as a data model to support centimeter, millimeter and submillimeter instrumentation at NRAO, JCMT, the University of Arizona and IRAM. We provide an overview of the GSDD requirements and associated data model, discuss the implementation of the resultant file formats, describe its usage in the observatories and provide a retrospective on the format.
We present a single-dish mapping algorithm with a number of advantages over traditional techniques. (1) Our algorithm makes use of weighted modeling, instead of weighted averaging, to interpolate between signal measurements. This smooths the data, but without blurring the data beyond instrumental resolution. Techniques that rely on weighted averaging blur point sources sometimes as much as 40%. (2) Our algorithm makes use of local, instead of global, modeling to separate astronomical signal from instrumental and/or environmental signal drift along the telescopes scans. Other techniques, such as basket weaving, model this drift with simple functional forms (linear, quadratic, etc.) across the entirety of scans, limiting their ability to remove such contaminants. (3) Our algorithm makes use of a similar, local modeling technique to separate astronomical signal from radio-frequency interference (RFI), even if only continuum data are available. (4) Unlike other techniques, our algorithm does not require data to be collected on a rectangular grid or regridded before processing. (5) Data from any number of observations, overlapping or not, may be appended and processed together. (6) Any pixel density may be selected for the final image. We present our algorithm, and evaluate it using both simulated and real data. We are integrating it into the image-processing library of the Skynet Robotic Telescope Network, which includes optical telescopes spanning four continents, and now also Green Bank Observatorys 20-meter diameter radio telescope in West Virginia. Skynet serves hundreds of professional users, and additionally tens of thousands of students, of all ages. Default data products are generated on the fly, but will soon be customizable after the fact.
We present a new package for joint deconvolution of ALMA 12m, 7m, and Total Power (TP) data, dubbed ``Total Power Map to Visibilities (TP2VIS). It converts a TP (single-dish) map into visibilities on the CASA platform, which can be input into deconvolvers (e.g., CLEAN) along with 12m and 7m visibilities. A manual is presented in the Github repository (https://github.com/tp2vis/distribute). Combining data from the different ALMA arrays is a driver for a number of science topics, namely those that probe size scales of extended and compact structures simultaneously. We test TP2VIS using model images, one with a single Gaussian and another that mimics the internal structures of giant molecular clouds. The result shows that the better uv coverage with TP2VIS visibilities helps the deconvolution process and reproduces the model image within errors of only 5% over two orders of magnitude in flux.
The Virtual Observatory (VO) is becoming the de-facto standard for astronomical data publication. However, the number of radio astronomical archives is still low in general, and even lower is the number of radio astronomical data available through the VO. In order to facilitate the building of new radio astronomical archives, easing at the same time their interoperability with VO framework, we have developed a VO-compliant data model which provides interoperable data semantics for radio data. That model, which we call the Radio Astronomical DAta Model for Single-dish (RADAMS) has been built using standards of (and recommendations from) the International Virtual Observatory Alliance (IVOA). This article describes the RADAMS and its components, including archived entities and their relationships to VO metadata. We show that by using IVOA principles and concepts, the effort needed for both the development of the archives and their VO compatibility has been lowered, and the joint development of two radio astronomical archives have been possible. We plan to adapt RADAMS to be able to deal with interferometry data in the future.
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