Implementing Quantum Polar Codes in a Superconducting Processor: From State Preparation to Decoding

Abstract

Quantum polar codes are a class of capacity-achieving quantum codes, with fast and efficient error syndrome decoding for Pauli channels, emerging as a promising approach to fault-tolerant quantum computation. However, their implementation on superconducting quantum hardware with connectivity constraints is hindered by the need for long-range qubit interactions, which increases CNOT gate usage and reduces fidelity. A full-stack software framework for implementing quantum polar codes is presented, integrating a noise-aware compilation approach that optimizes resource usage by combining quantum and classical software. Experimental results demonstrate significant improvements in logical state preparation rates, with resource savings from 10% to 81% for both quantum and classical computations.