scholarly journals CHILES. VII. Deep Imaging for the CHILES Project, an SKA Prototype

2022 ◽  
Vol 163 (2) ◽  
pp. 59
Author(s):  
R. Dodson ◽  
E. Momjian ◽  
D. J. Pisano ◽  
N. Luber ◽  
J. Blue Bird ◽  
...  

Abstract Radio astronomy is undergoing a renaissance, as the next generation of instruments provides a massive leap forward in collecting area and therefore raw sensitivity. However, to achieve this theoretical level of sensitivity in the science data products, we need to address the much more pernicious systematic effects, which are the true limitation. These become all the more significant when we consider that much of the time used by survey instruments, such as the Square Kilometre Array (SKA), will be dedicated to deep surveys. CHILES is a deep H i survey of the COSMOS field, with 1000 hr of Very Large Array time. We present our approach for creating the image cubes from the first epoch, with discussions of the methods and quantification of the data quality from 946 to 1420 MHz—a redshift range of 0.5−0. We lay out the problems we had to solve and describe how we tackled them. These are important because CHILES is the first deep wide-band multiepoch H i survey and has relevance for ongoing and future surveys. We focus on the accumulated systematic errors in the imaging, as the goal is to deliver a high-fidelity image that is only limited by the random thermal errors. To understand and correct these systematic effects, we ideally manage them in the domain in which they arise, and that is predominately the visibility domain. CHILES is a perfect test bed for many of the issues we can expect for deep imaging with the SKA or ngVLA, and we discuss the lessons we have learned.

2012 ◽  
Vol 64 (3) ◽  
pp. 47 ◽  
Author(s):  
Shin-ichiro Okumura ◽  
Kota Nishiyama ◽  
Seitaro Urakawa ◽  
Tsuyoshi Sakamoto ◽  
Noritsugu Takahashi ◽  
...  

2017 ◽  
Vol 13 (S336) ◽  
pp. 239-242
Author(s):  
Carolina B. Rodríguez-Garza ◽  
Stanley E. Kurtz ◽  
Arturo I. Gómez-Ruiz ◽  
Peter Hofner ◽  
Esteban D. Araya ◽  
...  

AbstractWe present observations of massive star-forming regions selected from the IRAS Point Source Catalog. The observations were made with the Very Large Array and the Large Millimeter Telescope to search for Class I methanol masers. We made interferometric observations of 125 massive star-forming regions in the 44 GHz methanol maser transition; 53 of the 125 fields showed emission. The data allow us to demonstrate associations, at arcsecond precision, of the Class I maser emission with outflows, HII regions and shocks traced by 4.5 μm emission. We made single-dish observations toward 38 of the 53 regions with 44 GHz masers detected to search for the methanol transitions at 84.5, 95.1, 96.7, 107.0, and 108.8 GHz. We find detection rates of 74, 55, 100, 3, and 45%, respectively. We used a wide-band receiver which revealed many other spectral lines that are common in star-forming regions.


Big Data ◽  
2016 ◽  
pp. 2199-2225
Author(s):  
Chris A. Mattmann ◽  
Andrew Hart ◽  
Luca Cinquini ◽  
Joseph Lazio ◽  
Shakeh Khudikyan ◽  
...  

Big data as a paradigm focuses on data volume, velocity, and on the number and complexity of various data formats and metadata, a set of information that describes other data types. This is nowhere better seen than in the development of the software to support next generation astronomical instruments including the MeerKAT/KAT-7 Square Kilometre Array (SKA) precursor in South Africa, in the Low Frequency Array (LOFAR) in Europe, in two instruments led in part by the U.S. National Radio Astronomy Observatory (NRAO) with its Expanded Very Large Array (EVLA) in Socorro, NM, and Atacama Large Millimeter Array (ALMA) in Chile, and in other instruments such as the Large Synoptic Survey Telescope (LSST) to be built in northern Chile. This chapter highlights the big data challenges in constructing data management systems for these astronomical instruments, specifically the challenge of integrating legacy science codes, handling data movement and triage, building flexible science data portals and user interfaces, allowing for flexible technology deployment scenarios, and in automatically and rapidly mitigating the difference in science data formats and metadata models. The authors discuss these challenges and then suggest open source solutions to them based on software from the Apache Software Foundation including Apache Object-Oriented Data Technology (OODT), Tika, and Solr. The authors have leveraged these solutions to effectively and expeditiously build many precursor and operational software systems to handle data from these astronomical instruments and to prepare for the coming data deluge from those not constructed yet. Their solutions are not specific to the astronomical domain and they are already applicable to a number of science domains including Earth, planetary, and biomedicine.


2014 ◽  
Vol 439 (4) ◽  
pp. 4057-4060 ◽  
Author(s):  
D. Forgan ◽  
R. J. Ivison ◽  
B. Sibthorpe ◽  
J. S. Greaves ◽  
E. Ibar

2018 ◽  
Vol 616 ◽  
pp. A15 ◽  
Author(s):  
N. C. Hambly ◽  
M. Cropper ◽  
S. Boudreault ◽  
C. Crowley ◽  
R. Kohley ◽  
...  

Context. The European Space Agency’s Gaia satellite was launched into orbit around L2 in December 2013. This ambitious mission has strict requirements on residual systematic errors resulting from instrumental corrections in order to meet a design goal of sub-10 microarcsecond astrometry. During the design and build phase of the science instruments, various critical calibrations were studied in detail to ensure that this goal could be met in orbit. In particular, it was determined that the video-chain offsets on the analogue side of the analogue-to-digital conversion electronics exhibited instabilities that could not be mitigated fully by modifications to the flight hardware. Aims. We provide a detailed description of the behaviour of the electronic offset levels on short (<1 ms) timescales, identifying various systematic effects that are known collectively as “offset non-uniformities”. The effects manifest themselves as transient perturbations on the gross zero-point electronic offset level that is routinely monitored as part of the overall calibration process. Methods. Using in-orbit special calibration sequences along with simple parametric models, we show how the effects can be calibrated, and how these calibrations are applied to the science data. While the calibration part of the process is relatively straightforward, the application of the calibrations during science data processing requires a detailed on-ground reconstruction of the readout timing of each charge-coupled device (CCD) sample on each device in order to predict correctly the highly time-dependent nature of the corrections. Results. We demonstrate the effectiveness of our offset non-uniformity models in mitigating the effects in Gaia data. Conclusions. We demonstrate for all CCDs and operating instrument/modes on board Gaia that the video-chain noise-limited performance is recovered in the vast majority of science samples.


Author(s):  
Chris A. Mattmann ◽  
Andrew Hart ◽  
Luca Cinquini ◽  
Joseph Lazio ◽  
Shakeh Khudikyan ◽  
...  

Big data as a paradigm focuses on data volume, velocity, and on the number and complexity of various data formats and metadata, a set of information that describes other data types. This is nowhere better seen than in the development of the software to support next generation astronomical instruments including the MeerKAT/KAT-7 Square Kilometre Array (SKA) precursor in South Africa, in the Low Frequency Array (LOFAR) in Europe, in two instruments led in part by the U.S. National Radio Astronomy Observatory (NRAO) with its Expanded Very Large Array (EVLA) in Socorro, NM, and Atacama Large Millimeter Array (ALMA) in Chile, and in other instruments such as the Large Synoptic Survey Telescope (LSST) to be built in northern Chile. This chapter highlights the big data challenges in constructing data management systems for these astronomical instruments, specifically the challenge of integrating legacy science codes, handling data movement and triage, building flexible science data portals and user interfaces, allowing for flexible technology deployment scenarios, and in automatically and rapidly mitigating the difference in science data formats and metadata models. The authors discuss these challenges and then suggest open source solutions to them based on software from the Apache Software Foundation including Apache Object-Oriented Data Technology (OODT), Tika, and Solr. The authors have leveraged these solutions to effectively and expeditiously build many precursor and operational software systems to handle data from these astronomical instruments and to prepare for the coming data deluge from those not constructed yet. Their solutions are not specific to the astronomical domain and they are already applicable to a number of science domains including Earth, planetary, and biomedicine.


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