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Register a new userTotal Power Map to Visibilities (TP2VIS): Joint Deconvolution of ALMA 12m, 7m, and Total Power Array Data
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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.
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Aims. Radio observing efficiency can be improved by calibrating and reducing the observations in total power mode rather than in frequency, beam, or position-switching modes. Methods. We selected a sample of spectra obtained from the Institut de Radio-Astronomie Millimetrique (IRAM) 30-m telescope and the Green Bank Telescope (GBT) to test the feasibility of the method. Given that modern front-end amplifiers for the GBT and direct Local Oscillator injection for the 30 m telescope provide smooth pass bands that are a few tens of megahertz in width, the spectra from standard observations can be cleaned (baseline removal) separately and then co-added directly when the lines are narrow enough (a few km/s), instead of performing the traditional ON minus OFF data reduction. This technique works for frequency-switched observations as well as for position- and beam-switched observations when the ON and OFF data are saved separately. Results. The method works best when the lines are narrow enough and not too numerous so that a secure baseline removal can be achieved. A signal-to-noise ratio improvement of a factor of sqrt(2) is found in most cases, consistent with theoretical expectations. Conclusions. By keeping the traditional observing mode, the fallback solution of the standard reduction technique is still available in cases of suboptimal baseline behavior, sky instability, or wide lines, and to confirm the line intensities. These techniques of total-power-mode reduction can be applied to any radio telescope with stable baselines as long as they record and deliver the ONs and OFFs separately, as is the case for the GBT.
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As the largest radio telescope in the world, the Square Kilometre Array (SKA) will lead the next generation of radio astronomy. The feats of engineering required to construct the telescope array will be matched only by the techniques developed to exploit the rich scientific value of the data. To drive forward the development of efficient and accurate analysis methods, we are designing a series of data challenges that will provide the scientific community with high-quality datasets for testing and evaluating new techniques. In this paper we present a description and results from the first such Science Data Challenge (SDC1). Based on SKA MID continuum simulated observations and covering three frequencies (560 MHz, 1400MHz and 9200 MHz) at three depths (8 h, 100 h and 1000 h), SDC1 asked participants to apply source detection, characterization and classification methods to simulated data. The challenge opened in November 2018, with nine teams submitting results by the deadline of April 2019. In this work we analyse the results for 8 of those teams, showcasing the variety of approaches that can be successfully used to find, characterise and classify sources in a deep, crowded field. The results also demonstrate the importance of building domain knowledge and expertise on this kind of analysis to obtain the best performance. As high-resolution observations begin revealing the true complexity of the sky, one of the outstanding challenges emerging from this analysis is the ability to deal with highly resolved and complex sources as effectively as the unresolved source population.
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