Testing CDM with ANN-Reconstructed Expansion History from Cosmic Chronometers
This work proposes an artificial neural network (ANN) framework to reconstruct late-time cosmic expansion using Cosmic Chronometer data. A staged methodology, involving mock validation and architecture screening based on smoothness diagnostics, was used to select a robust model. The final reconstruction showed stable results across different H0 priors, establishing a reproducible pipeline for testing cosmological models like Lambda-CDM.