[논문]THE AUTOMATIC CALIBRATION OF KOREAN VLBI NETWORK DATA

HODGSON, JEFFREY A.; LEE, SANG-SUNG; ZHAO, GUANG-YAO; ALGABA, JUAN-CARLOS; YUN, YOUNGJOO; JUNG, TAEHYUN; BYUN, DO-YOUNG

doi:10.5303/jkas.2016.49.4.137

THE AUTOMATIC CALIBRATION OF KOREAN VLBI NETWORK DATA 원문보기

Journal of the Korean astronomical society = 천문학회지, v.49 no.4, 2016년, pp.137 - 144

HODGSON, JEFFREY A. (Korea Astronomy and Space Science Institute) , LEE, SANG-SUNG (Korea Astronomy and Space Science Institute) , ZHAO, GUANG-YAO (Korea Astronomy and Space Science Institute) , ALGABA, JUAN-CARLOS (Korea Astronomy and Space Science Institute) , YUN, YOUNGJOO (Korea Astronomy and Space Science Institute) , JUNG, TAEHYUN (Korea Astronomy and Space Science Institute) , BYUN, DO-YOUNG (Korea Astronomy and Space Science Institute)

Abstract ▼ AI-Helper

The calibration of Very Long Baseline Interferometry (VLBI) data has long been a time consuming process. The Korean VLBI Network (KVN) is a simple array consisting of three identical antennas. Because four frequencies are observed simultaneously, phase solutions can be transferred from lower frequencies to higher frequencies in order to improve phase coherence and hence sensitivity at higher frequencies. Due to the homogeneous nature of the array, the KVN is also well suited for automatic calibration. In this paper we describe the automatic calibration of single-polarisation KVN data using the KVN Pipeline and comparing the results against VLBI data that has been manually reduced. We find that the pipelined data using phase transfer produces better results than a manually reduced dataset not using the phase transfer. Additionally we compared the pipeline results with a manually reduced phase-transferred dataset and found the results to be identical.

주제어

AI 본문요약
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제안 방법

This paper describes the automatic reduction software (pipeline) of an example KVN dataset and compares the results of the KVN Pipeline with that of the same dataset reduced in the manual way

성능/효과

The KVN pipeline has demonstrated its ability to automatically reduce a single polarisation KVN datset without direct human intervention. The performance of the KVN Pipeline is consistently superiour to manually reduced data without FPT being applied.
The KVN pipeline has demonstrated its ability to automatically reduce a single polarisation KVN datset without direct human intervention. The performance of the KVN Pipeline is consistently superiour to manually reduced data without FPT being applied. While the KVN is a simple network consisting of 3 identical telescopes, the methods described here (although not including the FPT capability) should be applicable to less homogoneous arrays such as the GMVA, KaVA and the EAVN.
The results are comparable, with differences in amplitude being due to the vector averaging performed in POSSM. To further investigate, we subtracted the differences between the amplitudes and phases (Figure 5) and find minimal differences, with 0.94° difference in phases on average and 0.00016 Jy difference on average in the amplitudes. Significant improvement can also be seen in the phase residuals (Figure 6), which compares the phase residuals of the manual method (left) and the KVN pipeline (right).
In general, both methods produce consistent numbers of good solutions, though in all cases the pipeline using FPT produces a greater numbers of solutions with the manually reduced dataset producing identical number of results as the pipeline. To investigate if the manually reduced (with FPT) dataset is identical to the pipeline version, we subtracted the differences in the visibilities and found the difference to be zero (see Figure 4).

후속연구

Currently the pipeline is only capable of reducing single polarisation continuum data. In future versions of the pipeline, we wish to add a polarisation reduction capability, spectral line reduction and possibly automated imaging and phase referencing capabilities.
The performance of the KVN Pipeline is consistently superiour to manually reduced data without FPT being applied. While the KVN is a simple network consisting of 3 identical telescopes, the methods described here (although not including the FPT capability) should be applicable to less homogoneous arrays such as the GMVA, KaVA and the EAVN. Currently the pipeline is only capable of reducing single polarisation continuum data.

참고문헌 (14)

Algaba, J.-C., Zhao, G.-Y., Lee, S.-S., et al. 2015, Interferometric Monitoring of Gamma-Ray Bright Active Galactic Nuclei II: Frequency Phase Transfer, JKAS, 48, 237
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Greisen, E. W. 2003, Information Handling in Astronomy - Historical Vistas, 285, 109
Kettenis, M., van Langevelde, H. J., Reynolds, C., & Cotton, B. 2006, ParselTongue: AIPS Talking Python, Astronomical Data Analysis Software and Systems XV, 351, 497
Lee, S.-S., Han, M., Kang, S., et al. 2013, Monitoring of Multi-Frequency Polarization of Gamma-Ray Bright AGNs, European Physical Journal Web of Conferences, 61, 07007

상세보기
Lee, S.-S., Petrov, L., Byun, D.-Y., et al. 2014, Early Science with the Korean VLBI Network: Evaluation of System Performance, AJ, 147, 77

상세보기
Lee, S.-S., Byun, D.-Y., Oh, C. S., et al. 2015, A New Hardware Correlator in Korea: Performance Evaluation Using KVN Observations, JKAS, 48, 229
Martí-Vidal, I., Krichbaum, T. P., Marscher, A., et al. 2012, On the Calibration of Full-Polarization 86 GHz Global VLBI Observations, A&A, 542, A107

상세보기
Pearson, T. J., & Readhead, A. C. S. 1984, Image Formation by Self-Calibration in Radio Astronomy, ARA&A, 22, 97

상세보기
Reynolds, C., Paragi, Z., & Garrett, M. 2002, Pipeline Processing of VLBI Data, arXiv:astro-ph/0205118
Rioja, M., & Dodson, R. 2011, High-Precision Astrometric Millimeter Very Long Baseline Interferometry Using a New Method for Atmospheric Calibration, AJ, 141, 114

상세보기
Rioja, M. J., Dodson, R., Jung, T., et al. 2014, Verification of the Astrometric Performance of the Korean VLBI Network, Using Comparative SFPR Studies with the VLBA at 14/7 mm, AJ, 148, 84

상세보기
Taylor, G. B., Carilli, C. L., & Perley, R. A. 1999, Synthesis Imaging in Radio Astronomy II, 180,
Zensus, J. A., & Ros, E. 2015, European VLBI Network: Present and Future, arXiv:1501.050799

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THE AUTOMATIC CALIBRATION OF KOREAN VLBI NETWORK DATA 원문보기

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THE AUTOMATIC CALIBRATION OF KOREAN VLBI NETWORK DATA 원문보기

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