THE ROLE OF NEUTRINOS IN THE UNIVERSE

Abstract

Neutrinos are fundamental particles that interact only weakly with matter, yet they hold significant power to reveal insights into both the microcosm of particle physics and the macrocosm of cosmology. This study presents a comprehensive, mixed-method investigation into the role of neutrinos in the universe, integrating theoretical modeling, computational simulations, observational data analysis, and detector performance evaluation. Theoretical predictions confirmed that neutrino oscillations and mass-squared differences follow expected behavior under varying baseline and energy conditions. Simulation results supported the normal mass hierarchy and constrained the total neutrino mass to below 0.12 eV, aligning with recent cosmological models. Detector efficiency studies showed that IceCube and DUNE perform optimally across different energy regimes, with event detection efficiency exceeding 85% in high-energy scenarios. Reconstructed energy spectra matched theoretical distributions within a ±5% margin, while flavor ratio analysis from astrophysical sources revealed post-oscillation convergence toward the expected 1:1:1 distribution. CP phase evaluations suggested weak but consistent indications of CP violation, particularly with clustering near δCP ≈ 3π/2. Moreover, machine learning models, specifically convolutional neural networks, achieved classification accuracies above 93% for distinguishing between neutrino flavors and background noise. Figures and tables validated the theoretical framework and demonstrated real-world applications of AI in neutrino physics. These findings underscore the critical role neutrinos play in shaping cosmic evolution, informing detector design, and opening new windows in high-energy astrophysics. The study provides a data-rich foundation for future explorations in particle physics, cosmology, and multi-messenger astronomy.