Quantum Circuit Qubit Mapping via Simulated Annealing

The patent transforms the discrete optimization problem of qubit allocation into a continuous parameter optimization problem by mapping logical qubits to physical qubits through a cost function that depends on connectivity parameters and fidelity metrics. This allows the use of gradient-based optimization methods instead of exhaustive search, reducing computational complexity from exponential to polynomial scaling while maintaining high mapping fidelity through continuous parameter adjustment.

The patent introduces an intermediary cost function that mediates between the logical quantum circuit requirements and the physical quantum hardware constraints. This cost function serves as a bridge, translating the allocation problem into an optimization landscape that can be navigated using simulated annealing, thereby avoiding direct exhaustive search while preserving fidelity requirements.

The patent creates a universal qubit allocation framework that works across different quantum hardware architectures with varying connectivity patterns. The cost function and simulated annealing approach are architecture-agnostic, allowing the same methodology to be applied to various qubit topologies (linear, grid, hypercube, etc.) while adapting to specific connectivity constraints, thus achieving both high fidelity and broad adaptability.

The patent employs dynamic optimization where the allocation strategy adapts to the specific connectivity structure of the target quantum hardware. The simulated annealing process dynamically adjusts the search space and acceptance criteria based on the hardware graph structure, enabling the system to optimize mappings for different connectivity patterns without requiring architecture-specific algorithms.