Quantum computers have the potential to revolutionize drug discovery, material design and fundamental physics — that’s, if we are able to get them to work reliably.
Certain problems, which might take a traditional computer billions of years to unravel, would take a quantum computer just hours. Nonetheless, these recent processors are more susceptible to noise than conventional ones. If we have the desire to make quantum computers more reliable, especially at scale, we want to accurately discover and proper 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 speed up progress on constructing a reliable quantum computer.
Accurately identifying errors is a critical step towards making quantum computers able to performing long computations at scale, opening the doors to scientific breakthroughs and lots of recent areas of discovery.
