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Diagram: Time-phase plots for fringe stopping (blue) vs Birli (gold) for five baselines (rows) at increasing integration times (columns, 0.5s, 1s, 2s, 4s, 8s).
Since Birli is widely used and its results accepted, it has served as the gold standard for correctness in our fringe stopping implementation. However, since real data tends to be quite noisy in practice, we do not expect Birli and fringe stopping to produce truly identical output files. To eliminate the guesswork involved in comparing two slightly different patterns of noise, we worked on developing some simpler comparisons.
For these hand-crafted tests, we modified voltage capture files to replace the sample data for all the RF sources, with identical copies of the data for one of them, so that the contents would be perfectly correlated, with zero phase difference at every instant and every frequency. Then, for each test case, we would create two copies. One had no fringe stopping metadata, while the other would have the same fringe stopping delays applied to the cloned voltage sources as would have been applied to the real data. Both copies were correlated offline and processed with Birli.
When Birli sees the copy with no fringe stopping, it applies its own corrections, unaware that it is applying corrections to already perfectly in phase data. Thus, when we plot phase vs time and frequency on the output, what we see is a neat visual representation of the corrections that would have been made for the original observation.
Likewise, for the copy with fringe stopping applied, it is being applied to data which is already in phase. Birli sees that fringe stopping is active and suppresses its usual corrections, and now we can make plots to directly compare what Birli would do, versus what fringe stopping would do. They should be the same, and indeed they are.
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Diagram: Frequency-phase plots for fringe stopping (left) vs Birli (right), using hand-crafted data to examine phase slopes at an instant in time.
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