Quantum Memory Breakthrough: Google AI Reduces Errors

A team from Google Quantum AI has introduced a groundbreaking quantum memory system that significantly reduces error rates in quantum computers. Their recent study, available on the arXiv preprint server, details how this new memory technology operates and its effectiveness in minimizing errors.

Past research has shown that a quantum computer without errors could surpass the capabilities of today’s supercomputers. However, the inherent challenges of quantum phenomena result in high error rates, making current quantum computers less practical.

To combat this issue, prominent tech giants like Microsoft and Google are exploring ways to either decrease these errors or enhance correction methods. Google’s team has made strides in the latter with their innovative approach.

In quantum computing, various technologies are employed, but they all use quantum bits. Typically, physical qubits are utilized to form logical qubits. The Google team has progressed by employing multiple physical qubits to create one logical qubit and has developed a new error-correction algorithm known as the "surface code." This algorithm uses the arrangement of physical qubits to enhance error correction and is claimed to be more effective than existing systems.

Their experiments demonstrated that the surface code algorithm became increasingly effective at correcting errors as the number of logical qubits increased—from 72 to 105. This suggests that increasing the number of qubits could further improve error correction, potentially leading to a quantum computer with minimal errors.

Additionally, the researchers found that the logical qubits in their system had a longer lifetime than the underlying physical qubits. This implies that their quantum memory system is capable of maintaining reliable quantum memory.