Google’s Quantum AI team reports that its 105-qubit Willow chip solves a complex calculation in about three hours, if the fastest supercomputer takes five years.

The findings, published in Nature, demonstrate that Willow chip uses a new algorithm called Quantum Echoes to run the complex calculations, making it 13,000 times faster than the powerful classical supercomputer. This marks the first time a quantum processor has produced results that are both faster and verifiable, with fewer errors, addressing one of the key criticisms of earlier quantum experiments.
The Quantum Echoes algorithm measures how information spreads within a quantum system. It performs a sequence of operations, slightly alters one qubit, and then reverses the process to compare results. This helps study how a small disturbance influences the whole system, a task that quickly becomes impossible for classical computers due to the exponential number of variables involved.
Google’s Willow chip didn’t calculate something like a weather forecast or a new molecule’s exact structure. It calculated what’s called an “out-of-time-order correlator” (OTOC): a kind of mathematical test used in physics to measure how information spreads inside a quantum system.
It ran a set of quantum operations on 65 of its qubits to create a complex, entangled state, like stirring a fluid until it’s chaotic. Then it slightly perturbed one qubit, introducing a small change. Finally, it ran all the operations in reverse, comparing the “before” and “after” states.
This forward-and-back process forms the Quantum Echoes algorithm. The name comes from the idea that the system “echoes” its own quantum state, revealing how much of the disturbance has spread and how irreversible the chaos is.
Classical computers can try to simulate this behaviour, but the number of calculations grows exponentially as you add more qubits. Even the Frontier supercomputer can’t fully simulate a 65-qubit quantum system at the precision needed for OTOC calculations.
So, what Willow actually calculated was how much and how fast information spreads inside a quantum network, a foundational step for modelling fundamental molecular interactions, energy transfer, and chemical reactions in future experiments.





