I have to admit I haven’t really kept up with developments in the world of gravitational waves this summer, though there have been a number of candidate events reported in the third observing run (O3) of Advanced LIGO which began in April 2019 to which I refer you if you’re interested.
I did notice, however, that late last week a new paper from the LIGO Scientific Collaboration and Virgo Collaboration appeared on the arXiv. This is entitled A guide to LIGO-Virgo detector noise and extraction of transient gravitational-wave signals and has the following abstract:
The LIGO Scientific Collaboration and the Virgo Collaboration have cataloged eleven confidently detected gravitational-wave events during the first two observing runs of the advanced detector era. All eleven events were consistent with being from well-modeled mergers between compact stellar-mass objects: black holes or neutron stars. The data around the time of each of these events have been made publicly available through the Gravitational-Wave Open Science Center. The entirety of the gravitational-wave strain data from the first and second observing runs have also now been made publicly available. There is considerable interest among the broad scientific community in understanding the data and methods used in the analyses. In this paper, we provide an overview of the detector noise properties and the data analysis techniques used to detect gravitational-wave signals and infer the source properties. We describe some of the checks that are performed to validate the analyses and results from the observations of gravitational-wave events. We also address concerns that have been raised about various properties of LIGO-Virgo detector noise and the correctness of our analyses as applied to the resulting data.
It’s an interesting paper that gives quite a lot of detail, especially about signal extraction and parameter-fitting, so it’s very well worth reading.
Two particular things caught my eye about this. One is that there’s no list of authors anywhere in the paper, which seems a little strange. This policy may not be new, of course. I did say I haven’t really been keeping up.
The other point I’ll mention relates to this Figure, the caption of which refers to paper [41], the famous `Danish paper‘:
The Fourier phase is plotted vertically (between 0 and 2π) and the frequency horizontally. A random-phase distribution should have the phases uniformly distributed at each frequency. I think we can agree, without further statistical analysis, that the blue points don’t have that property! Of course nobody denies that the strongly correlated phases in the un-windowed data are at least partly an artifact of the application of a Fourier transform to a non-stationary time series.
I suppose by showing that using a window function to apodize the data removes phase correlations is meant to represent some form of rebuttal of the claims made in the Danish paper. If so, it’s not very convincing.
For a start the caption just says that after windowing resulting `phases appear randomly distributed‘. Could they not provide some more meaningful statistical statement than a simple eyeball impression? The text says little more:
In addition to causing spectral leakage, improper windowing of the data can result in spurious phase correlations in the Fourier transform. Figure 4 shows a scatter plot of the Fourier phase as a function of frequency … both with and without the application of a window function. The un-windowed data shows a strong phase correlation, while the windowed data does not.
(I added the link to the explanation of `spectral leakage’.)
As I have mentioned before on this blog, the human eye is very poor at distinguishing pattern from randomness. There are some subtleties involved in testing for correlated phases (e.g. because they are periodic) but there are various techniques available: I’ve worked on this myself (see, e.g., here and here.). The phases shown may well be consistent with a uniform random distribution, but I’m surprised the LIGO authors didn’t present a proper statistical analysis of the windowed phases to prove beyond doubt the point they seem to be trying to make.
Then again, later on in the caption, there is a statement that `the phases show some clustering around the 60 Hz power line’. So, on the one hand the phases `appear random’, but on the other hand they’re not. There are other plausible clusters elsewhere too. What about them?
I’m afraid the absence of quantitative detail means I don’t find this a very edifying discussion!
In the Dark 