AI Could Aid Quantum Computers in Overcoming Biggest Roadblocks: Research
TEHRAN (Tasnim) – New research by Australia's national science agency indicates that artificial intelligence might be key to resolving errors in quantum computing, potentially advancing the technology to solve complex real-world problems.
CSIRO's recent study, published in Physical Review Research, reveals that AI can address quantum computing errors known as qubit noise, a significant obstacle to the development of advanced quantum computers.
Unlike conventional computers that use bits representing 0 or 1, quantum computers use quantum bits, or qubits, which can represent 0, 1, or both simultaneously. This unique property could unlock immense computing power, solving problems beyond the reach of traditional computers.
However, the fragile nature of qubits introduces 'noise' or errors in their outputs. Quantum error correction codes are necessary to detect and correct these errors.
CSIRO employed an AI neural network syndrome decoder to identify and correct these errors. Dr. Muhammad Usman, CSIRO's Data61 Quantum Systems Team Leader, explained, "Our work for the first time establishes that a machine learning-based decoder can, in principle, process error information obtained directly from measurements on IBM devices and suggest suitable corrections despite the very complex nature of noise."
He added, "In our work, we do not observe error suppression when the error correction code distance is increased, as theoretically anticipated, due to currently large noise levels (above code threshold) in IBM quantum processors."
Quantum error correction codes combat physical noise in qubits by distributing logical information across many physical qubits. These codes interpret error information by measuring stabilizers within a qubit lattice, known as a syndrome measurement.
To enhance correction efficiency, Dr. Usman implemented and trained an artificial neural network syndrome decoder. The decoder's performance, benchmarked on IBM quantum processors, demonstrated its ability to process complex errors from real quantum hardware and make appropriate corrections.
The research suggests that as physical error rates decrease in the coming years, AI could enable error suppression with increasing code distance, potentially achieving full fault-tolerance as the code distance becomes sufficiently large.