9 Conclusions
This thesis summarizes several novel findings in gravitational wave science, related to the detection and analysis of recent gravitational wave events and the preparation of data analysis techniques required for future detectors.
In January 2025 the LIGO-Virgo-KAGRA collaboration detected GW250114 (Abac et al. 2025), a merger of black holes which set a new record for clarity, as measured by its signal-to-noise ratio of nearly 80. Chapter 4 outlines how we used it to perform tests of General Relativity, constraining the frequency of the first overtone and validating Hawking’s area theorem. Working with such a precisely-measured signal also required a reexamination of the analysis assumptions that were previously made, which led to the identification and correction of a long-standing issue related to data normalization (Section 3.2.1).
Data analysis with the next generation of grond based detectors, such as the Einstein Telescope, will require efficient parameter estimation techniques. In Chapter 7, we show that parameter estimation on a population scale is possible thanks to neural posterior estimation (Section 2.3.2). While this work only included a subset of the sources we expect to be present in Einstein Telescope data, namely massive black hole binaries, it paves the way for the fast analysis of all the compact binary signals detected. Furthermore, it enables the comparison of different designs for the detector: we investigate the parameter constraints the Einstein Telescope would provide in several of its possible configurations. Our methods are fully Bayesian, and they allows us to illustrate how simple summary statistics like the variance in parameter estimates fail to fully capture the uncertainty in the inferred location of sources. For example, we show how the posterior distributions obtained with a triangular detector generally exhibit 8-fold multimodality in the sky for the sources in our sample, while a 2L configuration often yields multimodal estimates of the source’s distance.
The Lunar Gravitational Wave Antenna (LGWA, Chapter 8) will measure gravitational waves with an array of seismometers, a different principle compared to laser interferometers, in which the Moon itself is used as a resonant bar. Thanks to the quiet environment in permanently shadowed regions at the lunar pole, our seismometers will be able to make precise measurements at lower frequencies. We explore the science case of this detector, which ranges from lunar science to massive compact binaries of intermediate-mass black holes, light compact binaries such as those containing white dwarfs or neutron stars, and stellar-mass black hole binaries. The LGWA will probe the early inspiral of binaries in the population currently being observed by the LIGO-Virgo-KAGRA detectors, providing early warning and precise constraints on their evolution and sky position. The tight constraints on the chirp mass indicate that other, more astrophysically relevant parameters such as eccentricity or environmental matter density would also be tightly constrained, though that remains a topic for future work. We investigate the way the LGWA localizes its sources, and find it to be primarily through the measurement of Doppler phasing as the detector orbits the Sun, which is more effective for less massive sources.
We show that straightforwardly employing standard data analysis techniques to these binaries can lead to significant inefficiency: through a minimization procedure, requiring little computational overhead, we are able to find an optimized coordinate frame, which reduces sampling time by an order of magnitude. This procedure is of general applicability, and it will allow for coherent multi-band data analysis.