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Quantum computers have the potential to revolutionize drug discovery, materials design, and fundamental physics—assuming we can make them work reliably.
Certain problems that would take a traditional computer billions of years to solve would only take a quantum computer a few hours. However, these new processors are more susceptible to noise than traditional ones. If we want to make quantum computers more reliable, especially on a large 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 expertise and Google Quantum AI's error-correction expertise to accelerate progress in building a reliable quantum computer.
Accurately identifying errors is a crucial step in enabling quantum computers to perform long calculations at scale, opening the doors to scientific breakthroughs and many new areas of discovery.
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