Speaker
Description
The Einstein Telescope is expected to deliver extraordinary scientific results in gravitational-wave astronomy. However, as the ET design continues to evolve, important analysis challenges still need to be identified to fully realize its science potential, while existing tools for generating mock data are often limited in scope or difficult to use. We present gwmock, a new modular Python package for simulating realistic GW detector data. Built around a flexible architecture with independent lower-level components, gwmock is easily extensible to accommodate new signal models, noise glitches, or evolving detector configurations. The package emphasizes user-friendliness, with built-in metadata tracking for full reproducibility of generated datasets and a command-line interface for uploading data to Zenodo. We demonstrate the reliability of gwmock through a series of validation tests comparing simulated data against analytical expectations and established benchmarks.