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RESEARCH · QUANTUM ERROR CORRECTION

Why One Logical Qubit Can Need 101 Physical Qubits

Physical qubits are the hardware. Logical qubits are error-protected systems built from them—and the conversion is never a universal ratio.

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Conceptual diagram of many physical qubits feeding parity checks and a classical decoder to protect one logical qubit, with a note that Willow's 101-to-one memory example is not universal.
A logical qubit encodes information across physical data and measurement qubits while classical decoding interprets repeated parity checks. The 101-to-one callout is the Willow distance-7 memory example, not a universal conversion ratio.Original conceptual diagram by QubitWire editorial desk. Diagram: QubitWire editorial desk · Original QubitWire conceptual diagramFull image credit

A is a controllable quantum device: perhaps a superconducting circuit, trapped ion or neutral atom. A is different. It is encoded across multiple physical qubits so errors can be detected and corrected without directly measuring away the information researchers want to preserve.[1][2]

That distinction makes raw qubit counts a poor shortcut for comparing machines. The overhead depends on the error-correcting code, hardware connectivity, physical error rates and the logical reliability a workload needs. More physical qubits help only when operations are good enough for a larger code to suppress errors instead of adding more of them.[1][2]

Google's Willow experiment offers a concrete example. Its distance-7 surface-code memory used 101 physical qubits and reported a logical error rate of 0.143% per correction cycle. Increasing the code distance by two produced a 2.14-fold error-suppression factor, while the logical memory lifetime exceeded the best constituent physical-qubit lifetime by 2.4 times.[1][2]

Those numbers do not mean every logical qubit costs 101 physical qubits. This memory used 49 data qubits, 48 measurement qubits and four additional leakage-removal qubits. Other codes and devices use different structures. The experiment protected memory rather than running a complete fault-tolerant application, and the authors still observed rare correlated errors.[1][2]

Useful systems need more than isolated logical memories. They must perform logical gates, decode error signals quickly, remain stable and scale without correlated failures overwhelming the code. When reading hardware announcements, compare physical and logical counts separately—and ask what logical operation, error rate and workload were actually demonstrated.[1][2]

October 15 update: measure the logical operations too

An October 13 preprint uses Quantinuum H1 and the seven-qubit Steane code to characterize a universal single-logical-qubit gate set. Its hardware and emulator results answer different questions. The experiment retained about 50 shots per circuit; the larger emulator studies used 14,100. The absence of compelling non-Markovian behavior in hardware data does not prove smaller effects were absent: the paper treats sensitivity as a limitation.[3]

Circuits containing logical T gates were kept only when all relevant injections passed postselection. The fitted T operation describes accepted events rather than the unconditional operation including discarded attempts. A usable computer therefore needs more than a logical-qubit count or a conditional diagnostic: acceptance and throughput still matter.[3]

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Evidence & context

3 linked sources

Evergreen explainer based on a peer-reviewed Google-authored experiment and current IBM documentation. The 101-to-one example is a logical memory in one surface-code layout, not a universal qubit conversion or a general-purpose fault-tolerant computer.

How to read the evidence and dates

An announcement records what an organization stated. An experiment reports an observation. A simulation or resource estimate depends on its assumptions. QubitWire’s analysis connects these sources; the labels are not quality scores.

Published is the article’s first QubitWire publication. Updated marks a substantive content change. Sources checked records a review of the underlying evidence. An older paper can support a new explanation, and another press release about the same work is not independent replication.

For material corrections, check the article’s context note and source trail. A routine formatting or link change does not create a new scientific result.

Sources

  1. Nature: Quantum error correction below the surface code threshold
  2. IBM Quantum: Repetition codes
  3. Logical Gate Set Tomography - arXiv:2610.19034v1

    Preprint submitted October 13, 2026; full methods reviewed October 15. Distinguishes H1 hardware from emulator samples and a postselected logical T operation from an unconditional operation.

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