Preparing for tomorrow: simulating the Scientific Challenges of Next-Gen ground-based Gravitational Wave Interferometers

The next generation ground-based gravitational-wave interferometers such as Cosmic Explorer and Einstein Telescope will be able to detect $\mathcal{O}(10^5-10^6)$ signals annually from compact binary mergers. These signals, some spanning several hours and others from an epoch when the universe was still assembling its first stars, will present an unprecedented opportunity for discoveries and high-precision tests of nuclear physics, cosmological models, alternative gravity theories and astrophysical population models. The sheer volume of signals will necessitate novel algorithms for extracting the science from these signal-rich datasets. In anticipation, we employ the gwforge Python package to simulate mock data, providing a publicly released playground dataset. This initiative aims to challenge existing algorithms, foster refinement, and inspire the development of new approaches, ensuring the realisation of the scientific potential embedded in these signal-rich datasets. This talk briefly describes this playground dataset and the associated scientific objectives for the community.