AutoEmulate:  Python library for automatically creating accurate and efficient emulators of complex simulations.

Physical systems are understood and developed through simulations. The complexity of these systems often results in costly and time-consuming simulations. Emulators (surrogate models) can approximate the solution of simulations at a fraction of the computational expense. However, building effective emulators typically requires significant machine learning (ML) expertise, posing a barrier for domain experts. To overcome this limitation, we present AutoEmulate, a Python package that automates the construction of the best emulator suited for a given simulation, employing state-of-the-art advancements in the field. AutoEmulate supports a wide range of emulator models as well as data preprocessing, calibration, and analysis methods. AutoEmulate’s user-friendly interface enables domain experts to deploy high-performance emulators with minimal ML expertise, offering a reliable solution for simulation-driven exploration across various disciplines. Acknowledgements Alan Turing Institute