Generic Predictions for Primordial Perturbations and their implications

Understand

We introduce a novel framework for studying small-scale primordial perturbations and their cosmological implications.

• The framework uses a deep reinforcement learning to generate scalar power spectrum profiles that are consistent with current observational constraints.
• The framework is shown to predict the abundance of primordial black holes and the production of secondary induced gravitational waves.
• We demonstrate that the set up under consideration is capable of generating predictions that are beyond the traditional model-based approaches.