Special-Purpose Coherent Optical Quantum Computers Empower Qubit Mapping Optimization in General-Purpose Superconducting Quantum Computing

Special-purpose and general-purpose quantum computers offer two distinct paths toward practical quantum computing applications. While both accelerate solutions to classical problems, little research has explored how integrating different quantum systems can enhance quantum computing. This work presents a novel approach that uses a coherent optical quantum computer to optimize qubit layout mapping for superconducting quantum processors. It formulates qubit mapping as a Quadratic Unconstrained Binary Optimization (QUBO) problem, enabling efficient placement of quantum circuits onto IBM’s heavy-hex topology. Using the QBoson 550w optical Ising machine to solve and post-process this model, we tested 54 quantum circuits and achieved an 88.07% reduction in SWAP gate count. This result outperforms Qiskit’s LookaheadSwap and SabreSwap routing methods by at least 21.35% when those methods are executed without prior layout optimization. Our approach surpasses TrivialLayout, DenseLayout, and SabreLayout in Qiskit, delivering at least 7.06% better optimization. Additionally, we demonstrated that the quantum approach offers notable advantages in solution success rate and efficiency, as its solution time is below the millisecond level, and it can maintain an optimization rate comparable to that of classical quadratic solvers (e.g., Gurobi and CPLEX) for the QUBO model. To our knowledge, our work is the first deep integration of optical and superconducting quantum systems, introducing a new paradigm where quantum computing optimizes itself—unlocking new possibilities for self-improving quantum architectures.