Google’s Willow Chip Sets New Benchmarks in Quantum Computing

Google Quantum AI has introduced Willow, its latest quantum computing chip. With cutting-edge performance across multiple metrics, Willow achieves two groundbreaking milestones: exponential error reduction as the number of qubits scales and a computational feat that surpasses classical supercomputers by incomprehensible margins, says the company.

One of the most persistent challenges in quantum computing is error correction. Qubits, the fundamental units of quantum computation, are prone to rapidly losing information due to environmental interference, increasing errors as systems scale up. Willow overcomes this challenge by achieving what experts call “below threshold” error correction.

In tests published in Nature, Willow demonstrated exponential error reduction across grids of increasing qubit sizes — 3x3, 5x5, and 7x7 — achieving a 50% error rate reduction at each step. Willow’s system lifetimes surpassed those of individual qubits, a hallmark of effective real-time error correction. This development signals the viability of building scalable, logical qubits, a crucial component for large-scale quantum computers.

Willow’s power is exemplified by its performance on the Random Circuit Sampling (RCS) benchmark, a rigorous test that gauges whether a quantum computer can outperform classical counterparts. This achievement reaffirms the promise of quantum computing, says the company.

Willow was developed in Google Quantum AI’s custom fabrication facility in Santa Barbara, designed specifically for quantum chip production. Its 105 qubits boast best-in-class performance in error correction and computational benchmarks, driven by advancements in gate development, calibration, and chip architecture.

Google Quantum AI’s next objective is to achieve “useful, beyond-classical” computations that address real-world problems. Willow’s advancements bring this goal within reach, bridging the gap between theoretical benchmarks and commercially relevant applications, says Google.