Pictured above: A still image from a numerical simulation of a black-hole binary merger. Credit: LIGO - N. Fischer, H. Pfeiffer, A. Buonanno (Max Planck Institute for Gravitational Physics).
A new method to analyse gravitational-wave data could transform how we study some of the Universe's most extreme events - black holes smashing into each other.
Researchers from the University of Portsmouth , University of Southampton and University College Dublin have created a method to more accurately analyse gravitational waves, which are ripples in spacetime generated when massive objects like black holes collide.
The approach, published in Nature Astronomy , doesn't offer new discoveries about black holes yet. But by improving how scientists compare gravitational wave data to existing models, it lays important groundwork for future breakthroughs.
Ever since the Nobel-prize winning detection of gravitational waves in 2015, the study of these ripples has revolutionised our understanding of the Universe, driven largely by the detection of colliding black holes which are almost impossible to observe with standard optical telescopes.
I've been thinking about how to incorporate model accuracy into gravitational-wave Bayesian inference for years, and it's very exciting to see our method come to life
Dr Charlie Hoy, Research Fellow at the University of Portsmouth's Institute of Cosmology and Gravitation, and lead author
Dr Charlie Hoy , a Research Fellow at the University of Portsmouth's Institute of Cosmology and Gravitation , and lead author for this work, explained: "When a gravitational wave passes through Earth, we capture a brief signal. To figure out what caused it, we compare the observation against millions of possible theoretical gravitational-wave signals generated with different models. The challenge is that not all models are equally accurate"
Typically, scientists use a technique known as Bayesian inference to analyse gravitational-wave signals. This technique is often performed multiple times with different models, and the results combined in different ways. The issue with combining results with existing methods is that it can overlook how faithful each model is to Einstein's theory of general relativity - and risks misleading conclusions.
"I've been thinking about how to incorporate model accuracy into gravitational-wave Bayesian inference for years, and it's very exciting to see our method come to life," added Dr Hoy.
"Directly computing gravitational-waves by solving Einstein's Field Equations is really hard. Many gravitational-wave models have been developed over the years, but they all have some degree of approximation. With our approach we are able to incorporate this uncertainty into gravitational-wave data analysis methods, and obtain tighter constraints on the fundamental properties of black holes as a consequence.
"Gravitational-wave models are continually being developed and will likely improve in accuracy over the coming years. Our method is designed so that once these models become available, they can be incorporated into our algorithm. All models can then collectively help to obtain together constraints on the mass and spin of black holes."
The full research paper and be read online in Nature Astronomy here: https://www.nature.com/articles/s41550-025-02579-7
