Google Quantum AI has made a significant advancement in quantum error correction using the surface code, a method that groups physical qubits into “logical qubits” to protect calculations from errors. This development, demonstrated with their Willow quantum processor, showed that scaling from 3×3 to 5×5 and then to 7×7 grids of physical qubits successfully reduced errors by a factor of two each time. While the surface code has been a dominant error-correction strategy for years, it requires a large number of qubits, limiting its scalability and practical use in quantum computing.
However, a competing error-correction method introduced by IBM in 2023, called quantum low-density parity-check (QLDPC) code, promises greater efficiency and scalability. Unlike the surface code, QLDPC connects each qubit to six others, allowing them to monitor each other’s errors. IBM suggests that QLDPC could provide the same error-correction capabilities as the surface code but with far fewer qubits. For instance, while the surface code might require 4,000 qubits, QLDPC could achieve similar performance with only 288 qubits.
The lower qubit overhead of QLDPC has sparked interest, with experts like Joe Fitzsimons from Horizon Quantum emphasizing its potential advantages. IBM has designed its quantum chips to support the complex connectivity required for QLDPC, overcoming engineering challenges without compromising the reliability of the chips. At the Q2B conference in December, IBM researcher Oliver Dial highlighted the importance of customizing error-correction codes to align with specific hardware capabilities.
This competition between surface code and QLDPC also underscores the broader challenge in quantum computing: the delicate balance between hardware and software. The limitations of superconducting qubits, such as those used by both Google and IBM, affect the practicality of certain error-correction methods. Alternative technologies, like qubits made from ultracold atoms, could offer more flexibility and enable new approaches to error correction, as discussed by Yuval Boger of QuEra Computing, a quantum startup exploring such possibilities.
Despite the excitement surrounding QLDPC, the surface code remains a strong contender in the field of quantum error correction. Its theoretical framework has been well-studied for over two decades, providing a solid foundation for its application in quantum computing. Google’s team continues to explore alternative error-correction methods, but they emphasize that the surface code strikes a balance between performance and hardware requirements, making it particularly suitable for the superconducting qubits used in their Willow processor.
