Google scientists have developed a novel algorithm capable of solving problems on a quantum processor 13,000 times faster than the world’s speediest supercomputers— a leap they say brings quantum computing closer to real-world use in drug discovery, materials science, and other scientific fields.​

Named Quantum Echoes, the algorithm marks a key breakthrough: it not only achieves “quantum advantage” (outperforming classical systems) but is also the first such algorithm verifiable independently by running it on another quantum computer.​

Its ultra-fast performance was demonstrated in benchmark tests on Google’s Willow quantum processing unit (QPU). The researchers detailed the algorithm’s mechanics in a study published October 22 in the journal Nature.​

“Quantum algorithms guide quantum computers to solve problems efficiently, much like software drives classical computing,” Xiao Mi, a Google Quantum AI research scientist who led the work, told Live Science via email. “For either classical or quantum computing to solve future problems, both software and hardware must exist and work in tandem.”​

While the first study proved Quantum Echoes’ quantum advantage, the team also sought to show its practical utility. In a second study—published the same day (October 22) in the arXiv preprint database—they designed a quantum circuit to replicate molecular dynamics as observed in nuclear magnetic resonance (NMR) spectroscopy labs.​

Through this, they uncovered previously unknown details about the atomic spacing and structures of two molecules: [4-¹³C]-toluene (15 atoms) and [1-¹³C]-3′,5′-dimethylbiphenyl (DMBP, 28 atoms).​

The experiment used a small system (15 qubits), but the team noted in the study that future work will enable simulating molecules four times larger—a scale beyond the reach of classical computer simulations.