Quantum computers have the potential to revolutionize drug discovery, material design and fundamental physics — that is, if we can get them to work reliably. Certain problems, which would take a conventional computer billions of years to solve, would take a quantum computer just hours. However, these new processors are more prone to noise than conventional ones. If we want to make quantum computers more reliable, especially at scale, we need to accurately identify and correct these errors. In a paper published today in Nature, we introduce AlphaQubit, an AI-based decoder that identifies quantum computing errors with state-of-the-art accuracy. This collaborative work brought together Google DeepMind’s machine learning knowledge and Google Quantum AI’s error correction expertise to accelerate progress on building a reliable quantum computer. Accurately identifying errors is a critical step towards making quantum computers capable of performing long computations at scale, opening the doors to scientific breakthroughs and many new areas of discovery. Quantum computers harness the unique properties of matter at the smallest scales, such as superposition and entanglement, to solve certain types of complex problems in far fewer steps than classical computers. The technology relies on qubits, or quantum bits, which can sift through vast sets of possibilities using quantum interference to find an answer.

Full report : Googles’ AlphaQubit AI system accurately identifies errors inside quantum computers, helping to make this new technology more reliable.