Frequency Allocation in Multi-Qubits Architectures

With the increse in number of superconducting qubits , frequency crowding becomes a critical issue that limits scalability and performance. In this work, we address the challenge of frequency allocation by exploring manual and optimization-based approaches to effectively distribute qubit frequencies [1] . The manual method uses design intuition and experiment feedback, while the optimization-based method [2] looks for configurations that systematically reduce frequency collisions and crosstalk. For the optimization we implement Quantum Approximate Optimization Algorithm (QAOA) on multi-qubit system [3]. We compare the outcomes of both approaches and demonstrate a hybrid strategy by examining the geometry of the lattice. It can efficiently mitigate crowding and improve overall frequency distribution in multi-qubit systems [4][5].