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A recent study published in Nature has detailed a major achievement by Google’s Quantum AI team. Their latest quantum processor, named “Willow,” solved a computational problem in five minutes that would have taken the world’s most advanced supercomputer an estimated 10 septillion years. This achievement marks significant progress in overcoming one of the greatest challenges in quantum computing — reducing errors as the machines scale.

Breakthrough in Quantum Error Correction

Quantum computers are known for their high error rates, where approximately one in 1,000 qubits fail during calculations. In comparison, traditional computers experience failures in only one out of a billion billion bits. This discrepancy has made error-correction methods critical for advancing the technology. The Willow processor, which contains 105 physical qubits, employs error-correcting technologies that reduce inaccuracies as more qubits are added, an achievement first theorised by computer scientist Peter Shor in 1995.

Google Quantum AI’s Julian Kelly, director of quantum hardware, told Live Science that the team’s focus has been on achieving a state where fewer errors are introduced than are corrected. The Willow processor’s design integrates physical qubits into “logical qubits,” enabling calculations to proceed even if individual qubits fail.

Through advancements in machine learning, device fabrication, and calibration techniques, the team reported coherence times of up to 100 microseconds — five times better than their previous Sycamore processor, the researchers stated in the study.

Path to Practical Applications

The team’s immediate goal is to construct a logical qubit with an error rate of one in a million, requiring 1,457 physical qubits. Once achieved, their efforts will shift towards connecting multiple logical qubits to solve real-world problems. While the Willow processor has demonstrated exponential error reduction, scientists aim to move beyond benchmarks and focus on practical computations that extend the capabilities of quantum machines.

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This progress, as highlighted in the study and expert discussions, indicates a path forward for quantum computing to outperform classical systems in diverse applications.

 


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