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Register a new userData Models for Radio Astronomy in the VO
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Added by
Juan de Dios Santander-Vela
Publication date
2009
fields
Physics
and research's language is
English
Authors
J.D. Santander-Vela
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Data Models are an essential part of automatic data processing, but even more so when trying to tie together data coming from many different data sources, as is the case for the International Virtual Observatory. In this talk we will review the different data models used in the IVOA, which parts of that Data Modelling work are still incomplete, specially in radio wavelengths, and the work the AMIGA group has done within the IVOA Data Modelling Working Group to overcome those shortcomings both in missing data models and support for Radio Astronomy.
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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.
RF system-on-chip (RFSoC) devices provide the potential for implementing a complete radio astronomy receiver on a single board, but performance of the integrated analogue-to-digital converters is critical. We have evaluated the performance of the data converters in the Xilinx ZU28DR RFSoC, which are 12-bit, 8-fold interleaved converters with a maximum sample speed of 4.096 Giga-sample per second (GSPS). We measured the spurious-free dynamic range (SFDR), signal-to-noise and distortion (SINAD), effective number of bits (ENOB), intermodulation distortion (IMD) and cross-talk between adjacent channels over the bandwidth of 2.048 GHz. We both captured data for off-line analysis with floating-point arithmetic, and implemented a real-time integer arithmetic spectrometer on the RFSoC. The performance of the ADCs is sufficient for radio astronomy applications and close to the vendor specifications in most of the scenarios. We have carried out spectral integrations of up to 100 s and stability tests over tens of hours and find thermal noise-limited performance over these timescales.
A community meeting on the topic of Radio Astronomy in the LSST Era was hosted by the National Radio Astronomy Observatory in Charlottesville, VA (2013 May 6--8). The focus of the workshop was on time domain radio astronomy and sky surveys. For the time domain, the extent to which radio and visible wavelength observations are required to understand several classes of transients was stressed, but there are also classes of radio transients for which no visible wavelength counterpart is yet known, providing an opportunity for discovery. From the LSST perspective, the LSST is expected to generate as many as 1 million alerts nightly, which will require even more selective specification and identification of the classes and characteristics of transients that can warrant follow up, at radio or any wavelength. The LSST will also conduct a deep survey of the sky, producing a catalog expected to contain over 38 billion objects in it. Deep radio wavelength sky surveys will also be conducted on a comparable time scale, and radio and visible wavelength observations are part of the multi-wavelength approach needed to classify and understand these objects. Radio wavelengths are valuable because they are unaffected by dust obscuration and, for galaxies, contain contributions both from star formation and from active galactic nuclei. The workshop touched on several other topics, on which there was consensus including the placement of other LSST Deep Drilling Fields, inter-operability of software tools, and the challenge of filtering and exploiting the LSST data stream. There were also topics for which there was insufficient time for full discussion or for which no consensus was reached, which included the procedures for following up on LSST observations and the nature for future support of researchers desiring to use LSST data products.
The concept of a Square Kilometre Array was developed to ensure that progress in Radio Astronomy in the early 21st Century continued at the same impressive pace as was achieved during the first 50 years. The SKA telescope is designed to pave that road to greater and greater sensitivity. So what technical challenges does the project face and what key innovations will drive the success of the SKA? What will the next Radio Astronomy mega-science project look like? In this article the author discusses the likely avenues of progress in the coming decades and comments on the status of radio astronomy in 2049 - the authors 70th (and presumably her retirement) year.
As our capacity to study ever-expanding domains of our science has increased (including the time domain, non-electromagnetic phenomena, magnetized plasmas, and numerous sky surveys in multiple wavebands with broad spatial coverage and unprecedented depths), so have the horizons of our understanding of the Universe been similarly expanding. This expansion is coupled to the exponential data deluge from multiple sky surveys, which have grown from gigabytes into terabytes during the past decade, and will grow from terabytes into Petabytes (even hundreds of Petabytes) in the next decade. With this increased vastness of information, there is a growing gap between our awareness of that information and our understanding of it. Training the next generation in the fine art of deriving intelligent understanding from data is needed for the success of sciences, communities, projects, agencies, businesses, and economies. This is true for both specialists (scientists) and non-specialists (everyone else: the public, educators and students, workforce). Specialists must learn and apply new data science research techniques in order to advance our understanding of the Universe. Non-specialists require information literacy skills as productive members of the 21st century workforce, integrating foundational skills for lifelong learning in a world increasingly dominated by data. We address the impact of the emerging discipline of data science on astronomy education within two contexts: formal education and lifelong learners.
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