Quantum computing promises to tackle problems that classical supercomputers simply can’t finish — problems that might take thousands, millions, or even billions of years to solve using conventional hardware. But that begs a tricky question: if a quantum machine returns a result that no classical computer can feasibly check, how can we trust that result?
Researchers at Swinburne recognized this paradox and moved to address it head-on. Their new work focuses on one of the most promising — but hard to verify — types of quantum machines: Gaussian Boson Sampler (GBS) devices. Rather than trying to re-run the same problem on a classical supercomputer (which would take literally millennia), they developed methods that let engineers check a quantum result with a standard laptop — in minutes.
What they actually did
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Using the new validation techniques, the Swinburne team re-examined the output of a recent GBS experiment that claimed a quantum advantage. That experiment, if done on a classical supercomputer, would have required an estimated 9,000 years of compute time.
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The validation showed the output distribution from the GBS device didn’t match the expected theoretical distribution. In addition, the output included extra noise that had gone unnoticed in the original analysis.
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In short: the results failed the new verification test — indicating that despite the headline-grabbing claim, the GBS device may not have delivered a reliably quantum result.
Why this matters more than ever
Quantum advantage — the idea that quantum computers can solve certain problems way faster than classical systems — has been a central motivation for funding, hype, and development in the field. But if we can’t independently and reliably verify their outputs, those claims remain fragile.
The new methods from Swinburne offer a path toward scalable, realistic checks. Instead of relying on brute-force classical simulations (which quickly become infeasible), engineers can use statistical and analytic tools to flag when a quantum device might be slipping: producing noise, drifting off-model, or simply failing to deliver a valid quantum distribution.
For the quantum field, this could be a turning point. If adopted broadly, these verification tools could make the difference between speculative demonstrations and engineering-grade quantum systems — paving the way toward machines you can trust for cryptography, materials simulation, and other critical applications.
What still needs to be done
The results from the Swinburne study aren’t a blanket condemnation of quantum computing — but they are a clear warning. For any claim of quantum advantage to hold water, the devices must pass independent verification. Many current experiments may need re-evaluation.
Furthermore, the verification techniques thus far apply only to certain classes of quantum machines (like GBS). Extending them to other architectures — such as superconducting qubit arrays, trapped ions, or future fault-tolerant systems — will remain a major research challenge.
Finally, as quantum hardware grows in complexity, error sources multiply: environmental noise, decoherence, control-system flaws, hardware imperfections, calibration drift, and more. Testing for all of these — and validating correct behavior under realistic conditions — will require even more sophisticated validation tools.
The bottom line
Quantum computers hold extraordinary promise. They might one day crack problems that today seem impossible — simulating complex molecules, optimizing vast systems, or enabling next-generation cryptography. But without reliable, practical methods to check their output, that promise remains hypothetical.
The new validation methods from Swinburne offer the first realistic path toward trust: a way to check quantum results using classical resources, quickly and at scale. If further developed and widely adopted, this may mark the moment quantum computing shifts from speculative science to engineering reality.
Full Story: If quantum computing is answering unknowable questions, how do we know they’re right? | Swinburne
