Quantum Technologies From Discovery to Delivery

We present a comprehensive top-to-bottom paradigm for embedding quantum acceleration within high-performance classical pipelines. Using aerospace materials science and corrosion modeling as a primary exemplar, specifically capturing localized electrochemical dynamics and strongly correlated surface electronic states on aluminum alloys, we demonstrate how continuum-level models (such as finite element analysis) can be tightly coupled with quantum chemistry algorithms. Grounded in rigorous resource estimation for methods like Quantum Phase Estimation (QPE) and quantum embedding, we evaluate current algorithmic scalability, hardware constraints, and fault-tolerant timelines relative to state-of-the-art classical computing capabilities.

Our findings underscore the essential role of quantum–classical hybrid workflows in enabling practical quantum computing use cases. Moreover, they demonstrate that advancements in quantum hardware must be paralleled by breakthroughs in algorithm design and quantum error correction (QEC) to realize the full potential of quantum computing in materials science. This study represents the first fully integrated, multi-scale quantum-classical simulation of corrosion, laying critical groundwork for future materials design strategies that merge continuum-level modeling with quantum-accurate atomistic insights.