Quantum computing for optical system design

One of the main challenges of optimizing optical designs lies in handling discrete elements, such as selecting lens materials, test plate substitution or incorporating off-the-shelf components. Most commercial optical design packages allow for such optimizations, but results are not optimal, and the process is time consuming. The quantum computing department of the Netherlands Organization for Applied Scientific research (TNO) has implemented an AI-driving optimization method called QAFM (Quantum-Assisted Factorization Machine). This algorithm has demonstrated promising results in various fields particularly for problems involving discrete optimization. In this paper the possibilities of adapting this method for optical design of systems that requires element substitution are explored. The AI-driving discrete optimization project had two main goals: On one hand, it applied the QAFM model to the field of optical design, generating a set of optical designs compliant with the optical designer requirements. Second, developed a reusable, user-friendly and versatile implementation was developed which allows for knowledge transfer and paves the way for future applications.