Abstract We present Aletheia, a new emulator of the non-linear matter power spectrum, P(k), built upon the evolution mapping framework. This framework addresses the limitations of traditional emulation, the need to densely sample high-dimensional parameter spaces, by focusing on h-independent cosmological parameters, which can be separated into those defining the linear power spectrum shape (Θs) and those affecting only its amplitude evolution (Θe). The combined impact of evolution parameters and redshift is compressed into a single amplitude parameter, σ12. Aletheia uses a two-stage Gaussian Process emulation: a primary emulator predicts the non-linear boost factor as a function of (Θs) and σ12 for fixed evolution parameters, while a second one applies a small linear correction based on the integrated growth history. The emulator is trained on shape parameters spanning ±5σ of Planck constraints and a wide clustering range 0.2 σ12 1.0, providing predictions for 0.006 Mpc−1 k 2 Mpc−1. We validate Aletheia against N-body simulations, demonstrating sub-percent accuracy. When tested on a suite of dynamic dark energy models, the full emulator’s predictions show a variance of approximately 0.2%, a factor of five smaller than that of the state-of-the-art EuclidEmulator2 (around 1% variance). Furthermore, Aletheia maintains sub-percent accuracy for the best-fit dynamic dark energy cosmology from recent DESI data, a model whose parameters lie outside the training ranges of most conventional emulators. This demonstrates the power of the evolution mapping approach, providing a robust and extensible tool for precision cosmology.
Sánchez et al. (Thu,) studied this question.