Testing $Lambda$CDM with ANN-Reconstructed Expansion History from Cosmic Chronometers
Testing $Lambda$CDM with ANN-Reconstructed Expansion History from Cosmic Chronometers Yuki Hashimoto, Kazuharu Bamba, Sanjay Mandal arXiv:2604.22372v2 Announce Type: replace Abstract: In modern cosmology, the rapid growth of high-precision observational data, along with significant theoretical advances, has intensified the challenge of identifying a robust, model-independent framework to probe the expansion history of the Universe. In this work, we propose a novel artificial neural network (ANN)-based framework for the non-parametric reconstruction of the late-time cosmic expansion. The framework is trained and validated through a three-stage screening pipeline prior to its application to real observational data. As a demonstration of its effectiveness, we reconstruct the Hubble parameter $H(z)$Read More →