Artificial Intelligence and Electrical & Electronics Engineering: AIEEE Open Access
Cosmological Quantum Computing: Applying Friedmann Expansion Theory to Transformer-Optimized Willow and Majorana Quantum Systems
Abstract
Chur Chin
The convergence of quantum computing and cosmological physics represents a frontier in computational science. This study presents a novel framework integrating Friedmann equations from cosmological expansion theory with Transformer neural networks to optimize quantum computational systems, specifically Google’s Willow qubits and Majorana fermion- based topological quantum computing. We demonstrate that by mapping cosmic expansion dynamics—including dark energy (Λ), energy density (ρ), and curvature (k)—onto quantum circuit optimization parameters, we achieve significant improvements in phase stability and error suppression. Our Friedmann-Willow Hybrid (FWH) protocol exhibits error rate reductions of 1000-fold compared to conventional approaches. Simulation results confirm that Transformer-guided Riemannian optimization on quantum manifolds, combined with cosmological acceleration principles, enables dynamic gate timing control and topological gap expansion in Majorana systems. The extracted Quantum Cosmic Microwave Background (Q-CMB) data validates AdS/CFT correspondence and provides experimental evidence for the ER=EPR hypothesis in quantum gravity research.