Evaluating data analysis challenges in the 3G detector era and discussing the solutions
Boris Goncharov, Alexander H. Nitz, Jan Harms
Einstein Telescope (ET) is the third-generation gravitational wave detector expected to start observing in around 2034. Thanks to its remarkable sensitivity, ET will open pathways to new scientific discoveries. Unlike other current and future ground-based detectors that are L-shaped, ET will be composed of three low-frequency and high-frequency components forming an equilateral triangle with a side length of 10 kilometers. This will enable a special bonus feature for ET. A sum of strain output from three ET components will cancel all gravitational wave signals. This synthetic data channel of the ET is called the null stream. Whereas one can still construct a null stream from three arbitrary-located detectors, these null streams will depend on a signal sky position and only cancel one gravitational-wave signal at a given point in time.
In this work, we demonstrate the two data analysis problems that ET will face, as well as the solutions that ET null stream will provide:
- Eliminating non-stationary noise artifacts in the data and distinguishing them from astrophysical signals.
- We suggest that in the case of the ET the problem will be most relevant to two kinds of signals. First, to the most-distant binary black holes originating from the first stars or the early universe. This is due to such signals being quiet and short-durational, as transient detector glitches currently observed. Glitches, despite being incoherent, can still appear as false positives with apparent excess coherence. Second, to new signals with a complex waveform or to those without a clear physical model that are modeled phenomenologically.
- We then demonstrate the two methods for eliminating glitches using the null stream. First, using the so-called null SNR, and next using the so-called null stream likelihood. The former does not depend on a signal model and appears to be very effective.
- Estimating noise power spectra in presence of multiple overlapping signals.
- We simulate a population of merging binary neutron stars and binary black holes and demonstrate that it will be challenging to find signal-free data segments for estimating the noise spectra.
- Next, we demonstrate the recovery of the clean noise power spectrum using the null stream. We find that the ET null stream will be able to provide an easy solution for offline and online analyses at a low computational cost.
Finally, we review other applications of null streams in gravitational-wave astronomy and discuss the limitations of null stream analyses.
The article is accepted in Physical Review D.
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