BRITE Pivot: Hybrid Quantum-Classical Algorithms for Scalable Topology Optimization

This BRITE project explores how emerging quantum computing can enhance the design of high-performance engineering structures. As products such as aircraft components, automotive frames, and 3D-printed parts become more complex, engineers rely on computational tools to optimize material usage and performance. However, traditional methods struggle to keep up with the scale and complexity of modern design problems. This research seeks to develop a new hybrid computational approach that combines quantum and classical computing to improve design speed, efficiency, and quality. The project will also create educational materials to help students and professionals understand how quantum computing can be applied to real-world engineering challenges. This research introduces a hybrid quantum-classical approach to topology optimization that strategically applies quantum computing to the most computationally demanding steps in the design process. The project focuses on three main contributions, seeking to solving large, sparse linear systems using quantum methods; estimating design sensitivities via quantum gradient estimation without relying on adjoint solvers; and updating material distributions using variational quantum circuits optimized through quantum natural gradient descent. These research tasks are intended for near-term quantum hardware and will be implemented and tested on both simulators and available quantum processors. By targeting numerical bottlenecks of classical topology optimization, the proposed framework aims to improve solution efficiency, scalability, and robustness. The research outcomes will include a validated set of hybrid algorithms, performance benchmarks on relevant structural design problems, and accessible computational tools to support broader adoption in engineering and scientific communities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.