Essays / Foundations

What a logical qubit actually is

The word “logical qubit” is now used for at least four different things, only one of which is the thing that matters. This is how to tell which one an announcement means.

By Christian Stark · Published 8 September 2026 · Reviewed 8 September 2026 · Intermediate · Living essay

“Logical qubit” has become the field’s most abused phrase. It appears in roadmaps, in funding announcements, and in headlines, attached to numbers that are not comparable with each other. Some of those numbers describe a genuine piece of protected memory. Some describe an encoded state that was prepared, looked at, and discarded. The word is the same in both cases.

The distinction is worth learning, because it is the difference between hardware that is on the path to a machine and hardware that is demonstrating a component of one.

The problem error correction solves

Classical error correction is straightforward: copy the bit three times, read all three, take the majority. Quantum information forbids both halves of that. You cannot copy an unknown quantum state, and reading a qubit destroys the superposition you were trying to protect.

The way around it is indirect. Encode one logical qubit across many physical qubits so that the information lives in the correlations between them rather than in any single one. Then measure not the data but a set of parities — whether neighbouring qubits agree — chosen so that the answers reveal where an error occurred without revealing what state is stored. Those answers are the syndrome. A decoder reads the syndrome, infers which error most likely occurred, and applies the correction.

This has to happen repeatedly, faster than errors accumulate, for the entire duration of the computation. Error correction is not a step you run at the end. It is a process the machine performs continuously, in the background, forever, while also doing the actual computation.

The threshold, and why it is the whole game

Codes have a threshold: a physical error rate below which the scheme works. Below threshold, making the code larger — adding more physical qubits per logical qubit — makes the logical error rate fall, and it falls fast, roughly exponentially in the code distance. Above threshold, making the code larger makes things worse, because you have added more places for errors to appear than the code can fix.

The threshold is therefore a sign change, not a gradient. It is the reason “below threshold” is the phrase to look for in any error-correction result and “we added more qubits” is not.

For the surface code, the most studied family, the threshold sits around one per cent per operation, with the exact figure depending on the noise model and the decoder. Real hardware has to be comfortably below that, not marginally, because the overhead required to reach a useful logical error rate grows sharply as you approach the threshold from below.

That overhead is large. Reaching logical error rates low enough for a long computation typically requires something on the order of a thousand physical qubits per logical qubit, and under pessimistic assumptions considerably more. This is why a chip with a few thousand physical qubits does not correspond to a few thousand logical ones, and why the ratio, rather than either number alone, is the thing to track.

Newer code families, particularly quantum low-density parity-check codes, promise better ratios by giving up the surface code’s convenient nearest-neighbour layout. They require connectivity that most hardware does not have. Whether that trade is winnable on real machines is one of the open questions this site follows.

Four things called a logical qubit

When an announcement reports logical qubits, it is usually reporting one of these, and they are not equivalent.

An encoded state that was prepared and measured. The team encoded a logical state, verified it looked right, and stopped. This shows the encoding works. It says nothing about whether the state survives.

A logical memory that beat its physical parts. The encoded qubit held information longer, or with lower error, than the best single physical qubit in the same device. This is a real milestone and the first genuine evidence that correction is doing work.

A logical memory that improves as the code grows. Increasing the code distance lowered the logical error rate. This is the below-threshold result, and it is the one that matters most, because it is the only one that implies the approach scales.

Logical qubits performing logical operations. Entangling gates between logical qubits, error correction running throughout, with the logical error rate holding up across the sequence. This is where useful computation begins, and it is the hardest of the four.

The gap between the third and the fourth is the current frontier, and it is wider than it looks. Some logical operations are comparatively cheap: the Clifford gates, which can often be performed by rearranging the code rather than acting on it directly. But Clifford gates alone are classically simulable, so a machine that can only do them cannot outperform a laptop. Universality requires at least one non-Clifford gate, and in most schemes that is supplied through magic state distillation, which consumes a large number of additional physical qubits and a great deal of time to produce a single usable resource state.

In many resource estimates, distillation dominates the cost of the machine. The memory is not the expensive part. Doing something with it is.

How to read the next announcement

Three questions cut through most of the ambiguity.

What is the logical error rate per cycle, and what is it compared against? A logical qubit that is worse than the best physical qubit in the same device has not yet demonstrated protection.

Does the logical error rate fall when the code distance increases? If the result covers only one code size, it is a demonstration of encoding, not of correction that scales.

Did the logical qubits do anything? Idle memory, Clifford operations, and a universal gate set are three different achievements, and only the third is on the path to a computation.

A physical qubit is not a logical qubit. A logical qubit that sits still is not a logical qubit that computes. Both distinctions get flattened in summary, and both are where the real state of the field is hiding.

This is a foundation essay. It is kept current rather than frozen, so the reviewed date above matters more than the publication date.