Quantum computing doesn't show up often in the news. After all, it has gigantic potential, but the technology has been promising practical real-world uses in "just a few years" for decades now. The science world may have finally reached a tipping point for practicality, though. Google's engineers demonstrated a world-first of running a verifiable algorithm on its Willow quantum chip — 13,000 times faster than a supercomputer.
The algorithm in question is called Quantum Echo and models a physics experiment in Nuclear Magnetic Resonance (NMR, the spectroscopic variant of the popular MRI), revealing internal molecular structures by detecting magnetic spins at the center of atoms. According to Google, Willow runs this 13,000x faster than "the best classic algorithm on the world's fastest supercomputers", meaning that the one chip is many order of magnitudes faster than an entire datacenter at this specific task.
This is a gross oversimplifications, but the main issue with quantum computers is that they're not intrinsically deterministic. They arrive at a probable solution, although they have the advantage of considering most every possible input simultaneously — hence the insane speedups for highly specific tasks that fit the exact mold. A quantum computer's solutions are thus inherently error-prone, and it's necessary to reduce the error rate by several orders of magnitude to make practical applications viable.
The fact that Quantum Echo is de facto verifiable and "deterministic" comes by way of of sending a "ping" into Willow's 105-qubit array and reading its effects millions per second, revealing information about the state of the system, thus (again, I'm oversimplifying) letting scientists peer into the outcome without significantly altering it.
This is apparently the largest such type of data collection in any quantum computing project, and was key to making the NMR analysis verifiable by helping reduce the error rate enough to arrive at a "deterministic" solution.
The team predicts that quantum computers are key to modelling quantum phenomena in nature, as in the aforementioned example, and it's not hard to imagine other similar applications now that a baseline for practicality has been reached. Google Quantum AI is now moving to Milestone 3 of its roadmap of building a long-lived logical qubit. Schrödinger would be happy.
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