John Preskill, one of quantum computing's most respected voices, has laid out a roadmap for the field's next major challenge. It's not about building bigger quantum computers. It's about proving they can do something useful that we can actually verify.
The problem is surprisingly fundamental. We're approaching quantum systems with 100 logical qubits - enough power to potentially outperform classical computers on specific tasks. But how do we know they're working correctly when the calculations are too complex for classical computers to check?
The verification problem
Think about it this way. If a quantum computer solves a problem too hard for classical computers to solve, how do you check the answer? You can't just run the calculation on your laptop to verify it. That's the whole point - your laptop can't do it.
This is what Preskill calls "classically verifiable quantum advantage." It's the sweet spot where quantum computers do something genuinely useful, something classical computers struggle with, but we can still verify the results without needing another quantum computer.
The technical term is "quantum advantage in the 100-logical-qubit regime." In simpler terms: quantum computers with about 100 high-quality, error-corrected qubits that can demonstrate clear advantages over classical computing while still allowing us to check their work.
Why 100 logical qubits matters
The number isn't arbitrary. Physical qubits - the raw quantum bits in current machines - are noisy and error-prone. To get one reliable "logical qubit" requires many physical qubits working together with error correction. We're getting closer to systems that can maintain 100 of these high-quality logical qubits.
At that scale, interesting things become possible. Certain quantum algorithms start to show real advantages. Chemical simulations become tractable. Optimisation problems that would take classical computers years could potentially run in hours or days.
But only if they're working correctly. And that's where Preskill's roadmap focuses.
The proposed path forward
Preskill outlines several approaches to the verification challenge. One involves fault-tolerant circuits - quantum computations designed to be robust against errors, with built-in redundancy that allows checking without destroying the quantum state.
Another approach uses symmetry. Many useful quantum calculations have inherent symmetries - patterns that should be preserved regardless of the specific computation. By checking whether these symmetries hold, we can verify results without fully simulating the quantum system classically.
A third method involves what Preskill calls "planted-secret sampling schemes." The idea is clever: design problems where the answer is secretly known to the problem designer but computationally hard for classical computers to find. The quantum computer attempts to find the secret. If it succeeds, we know it worked - without needing a classical computer to verify the calculation itself.
What this means for practical quantum computing
For anyone following quantum computing's progress, this roadmap matters because it addresses the credibility gap. We've had announcements of "quantum supremacy" or "quantum advantage" before, but they've often involved artificial problems designed specifically to favour quantum computers without clear practical applications.
Classically verifiable quantum advantage is different. It requires demonstrating real capability on problems that matter, with results we can trust. That's the threshold for quantum computing to move from research curiosity to practical tool.
The timeline isn't certain. Reaching 100 logical qubits with sufficient quality is itself a significant engineering challenge. Google, IBM, and other quantum hardware developers are making progress, but we're likely still a few years away from systems that consistently hit this target.
The practical reality check
It's worth being clear about what this doesn't mean. Even with classically verifiable quantum advantage at 100 logical qubits, we're not talking about quantum computers replacing classical computers for everyday tasks. Your laptop will remain faster for email, spreadsheets, and web browsing for the foreseeable future.
What we are talking about is quantum computers becoming genuinely useful for specific, high-value problems. Drug discovery simulations that would be impractical classically. Materials science calculations that unlock new battery chemistries. Optimisation problems in logistics or finance that classical methods struggle with.
But only if we can verify the results. Preskill's roadmap is essentially saying: let's prove quantum computers work before we scale them further. It's the kind of rigorous, measured approach the field needs.
Why this matters now
The quantum computing industry is at an inflection point. Significant investment is flowing in. Companies are making bold claims. The hype cycle is in full swing. Preskill's framework offers a concrete milestone to aim for - one that's ambitious but achievable, meaningful but verifiable.
For business owners and decision-makers evaluating quantum computing, this roadmap provides useful context. If someone claims their quantum system has achieved breakthrough performance, ask about verification. Can they prove it? How do they check the results? Are they working toward classically verifiable advantage, or just demonstrating quantum effects without clear practical benefit?
The next few years in quantum computing will likely focus on hitting this milestone. Not the biggest quantum computer, but the most reliable one. Not quantum supremacy on abstract problems, but quantum advantage on tasks we actually need to solve.
That shift from impressive demonstrations to verifiable utility might be the most important development in quantum computing since the field began. And it starts with asking a simple question: how do we know it works?