A quantum computer with a thousand physical qubits and no error correction is not a thousandth of a useful quantum computer. It's a different kind of object altogether, in the way that a thousand bricks is a different kind of object from a thousandth of a house.
The number that matters is logical qubits, and the ratio between physical and logical is where the field really lives.
Why the ratio is so brutal¶
Quantum states decohere. A physical qubit holds its state for anything from microseconds to milliseconds depending on the technology, and every gate operation carries an error rate of its own.
Classical error correction copies bits. Quantum error correction can't, because the no-cloning theorem forbids it. Instead you encode one logical qubit across many physical ones and measure stabilisers: operators that tell you whether an error happened without telling you (and so collapsing) the encoded state.
Surface codes are the leading family. The physical cost per logical qubit is large, and it scales with how good your physical qubits are in the first place.
The threshold theorem, stated carefully¶
The threshold theorem says arbitrary-length quantum computation is possible if the physical error rate sits below some threshold. Above it, adding more physical qubits makes matters worse, because the correction machinery brings in more errors than it clears up.
Two things follow, and both get glossed over:
- The threshold isn't a single universal number. It depends on the code, the noise model and how well connected the architecture is.
- Being below threshold is necessary and not sufficient. How far below sets the overhead, and the overhead decides whether a useful machine is the size of a rack or the size of a small town.
Which is why "we have N qubits" is close to meaningless with no error rates beside it, and why the field's real milestones are the demonstrations where increasing the code distance decreases the logical error rate. That's the sign correction is working rather than merely being performed.
The engineering, not the physics¶
The part that gets least attention, and is arguably the hardest:
- Measuring stabilisers fast enough. Syndrome extraction has to run far faster than decoherence, which means real-time classical processing sitting in the loop with the quantum hardware.
- Decoding in real time. The classical decoder turning syndromes into corrections has a latency budget in microseconds. That's a hard classical computing problem that happens to live inside a quantum computer.
- Wiring. Routing control lines per qubit into a dilution refrigerator is a physical scaling problem and no amount of clever software will answer it.
That last one is thoroughly unglamorous and may well turn out to be the binding constraint.
The cryptographic story dominates the coverage and it is the least interesting application. Breaking RSA is a one-off event with a known mitigation that is already being deployed. The reasons to want one of these machines are elsewhere and they are substantial.
Simulating quantum systems is the obvious one, and it is obvious because it is the thing a quantum computer is natively for. Chemistry at useful accuracy: catalysts, battery electrolytes, nitrogen fixation, enzyme behaviour. Those are problems where the current method is to approximate, synthesise and test, which is why developing a new catalyst takes a decade and a laboratory. A machine that can model the electronic structure directly turns part of that loop into computation. The payoff, if it lands, looks like cheaper fertiliser and better batteries rather than anything to do with cryptography. The energy implications of either are larger than anything else in this field.
Optimisation is the claim to be most sceptical about, since the speedups are modest where they exist at all and classical methods keep improving. We would not plan a business on it.
The quiet benefit is to classical engineering, and it is already being paid out. Building error-corrected quantum hardware requires real-time classical decoding in microseconds, cryogenic control electronics and absurdly precise timing. That work produces instrumentation, low-noise electronics and real-time computing techniques that are useful whether or not the quantum machine ever works. A good deal of the field's actual output so far has been classical.
Code is not the scarce part. Capital is.
An error-corrected machine needs a dilution refrigerator, a fabrication capability, a real-time control stack and several hundred people, sustained for a decade with no product. That is a short list of organisations: a few very large technology companies, a few state programmes and a small number of well-funded specialists who will probably end up owned by the first group. There is no garage version of this today, and our bet is that there will not be one: the cryogenics and the error-correction overhead look structural, not early. If that holds, whatever comes out will be rented by the hour, and it will be the most concentrated computing capability ever built, by physics and finance rather than by a business strategy anyone chose. That is a bet about engineering economics, and we have marked it as one.
The consequence worth planning for is about archives rather than access. The asymmetry lies in the archive, not in three companies having a fast computer. The encrypted traffic recorded over the last twenty years is held by organisations with the budget to record it, and a capable machine arriving in that environment retroactively opens all of it. State communications, dissident networks, journalists' sources, medical records, anything with a long confidentiality horizon. The people with the most to lose from that are in the worst position to do anything about it, and the people who will get first access are the ones who have been collecting. That is the actual privacy story in quantum computing and it has very little to do with whether anyone can factor a number next year.
Which makes migration an equity question as much as a technical one. Those with a budget are already rotating to post-quantum key exchange. The clinic, the charity, the local authority, the small operator with embedded devices in the field: they are not, and the capability that decrypts their archives will be rented by somebody else. The useful response is unglamorous and available now: move to post-quantum key exchange where you terminate the connection yourself, because on a current TLS stack that part is close to a configuration change. Then start the inventory for everything else, because the appliances, the embedded kit and the long-lived certificates are a programme, not a setting. The cost later is an archive you cannot unpublish.
Where is the open version? Not in hardware, and it never will be. It is in the software and the standards, and that is where it matters: the algorithms are public, the implementations are open and nobody needs permission to protect their own traffic. Here at AxisOps that is the lever we can pull and the one we recommend pulling. You cannot build the machine and you do not have to; you can make the archive worthless, and the window for doing that cheaply is open now.
What a non-specialist should take from it¶
The summary for anyone outside the field: the progress is real, the timelines in the press coverage aren't reliable, and the things to watch are logical qubit counts and error rates rather than physical qubit counts.
We are reporting here, not measuring. We don't run quantum hardware, and the people who do are not publishing the numbers that would settle the overhead question.