QPI-DeepONet-MAC: A Scalable and Stable Hybrid Classical-Quantum Architecture for Physics-Informed Deep Operator Networks
The QPI-DeepONet-MAC architecture is a hybrid quantum-classical model for learning operators in physics-based partial differential equations (PDEs). It combines classical DeepONet representations with parameterized quantum circuits using multiplicative and additive couplings. This framework aims to create a scalable, trainable, and expressive method for approximating complex PDE solutions.