University of Tasmania

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Improving the efficiency of the AuScope VLBI observations through dynamic observing

posted on 2024-04-17, 06:00 authored by Chin Chuan Lim

The current efficiency of the global very-long-baseline interferometry (VLBI) observations is about 80%, which means about 5 hours of data are unused for every 24-hour ses?sion. Various factors may cause such inefficiency in VLBI observation, including harsh weather, temporary telescope failures, and low signal-to-noise ratio (SNR) achievement. The last factor is usually the result of a significant mismatch between the predicted and actual telescope sensitivity and flux density of radio sources. Whilst mitigating the ef?fect of weather and other external factors largely depends on the individual station, my PhD research tackles telescopes and SNR concerns for the Australian VLBI network via automation. I have designed and developed the automation tool, named Dynob, for a more efficient, streamlined, and uniform VLBI procedure. Dynob is a multiple-step pro?gram, which means human interaction is possible at any stage, with the goal of improving SNR achievement through a continuous feedback loop. Dynob is designed and optimised for Australian VLBI observations but should also run for a global network. The tool has been tested with the Australian VLBI sessions in collaboration with the telescopes in New Zealand and South Africa.
The observations for my research utilised a new observing technique called ‘mixed?mode’, which makes it possible for telescopes with upgraded receivers and back ends to observe with the old telescopes concurrently. Given the difference in signal digitising back end, mixed-mode observations have different sensitivities in the three baseline types it produces, i.e., pure new system baselines, mixed-new and legacy baselines, and pure legacy system baselines. I investigated the sensitivities of all baselines from theoretical and experimental points of view. Mixed-mode observing technique can give comparable sensitivity to the legacy sessions after accounting for the baseline differences in the plan?ning and post-processing stage. I also investigated a new method for source flux density and antenna sensitivity monitoring, which improves the SNR achievement by about two times the standard deviation of the old method. Dynob makes all the research products fully automated with a performance feedback mechanism, thereby improving the opera?tional and observation efficiency of VLBI.



  • PhD Thesis


179 pages


School of Natural Sciences

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