A Hierarchical Renormalization Framework for Adaptive Optimization in Complex Biological Systems: Application to HIV Cure Strategies

This project mathematically and computationally demonstrates how a hierarchical renormalization framework with warm-start re-optimization solves NP-hard optimization problems in biology (such as the search for HIV cures), avoiding the typical error divergence of traditional methods. The framework guarantees error convergence to a theoretical floor through periodic re-normalization at each hierarchical level, providing a computationally tractable pathway for in silico clinical trials and adaptive therapy design in complex biological systems.