Google Quantum AI Takes Step Towards climbable Quantum Error Correction

Google Quantum AI has taken a significant step forward in the development of scalable quantum error correction, according to a new study published by the company. Quantum computers are prone to errors due to noise from the underlying physical system, which must be reduced for quantum computers to achieve their potential. One way to address this is through error-correcting codes, which use an ensemble of physical qubits to form a logical qubit that can detect and correct errors without affecting information. However, scaling up such systems means manipulating more qubits, which can introduce more logical errors. To address this challenge, the Google team demonstrated that a surface code logical qubit can lower error rates as the system size increases. They created a superconducting quantum processor with 72 qubits and tested it with two different surface codes: a distance-5 logical qubit on 49 physical qubits and smaller ones called distance-3 logical qubits on 17 physical qubits. The larger surface code was shown to enable better logical qubit performance than the smaller surface code. While more work is needed to reach the logical error rates required for effective computation, the researchers believe that this work represents a fundamental requirement for future developments in quantum error correction.

Reference

"Suppressing quantum errors by scaling a surface code logical qubit." Nature 614, no. 7949 (2023): 676-681. https://doi.org/10.1038/s41586-022-05434-1