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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsA quantum error rate estimates how often a specified quantum operation or benchmark departs from its intended behavior under a particular test. It is not a free-standing probability that an entire quantum program will fail: a gate-level figure, a readout error, and a processor-wide benchmark describe different things.
What does quantum error rate mean?
A quantum error rate is an estimate tied to a defined operation, device, and characterization method. Depending on the source, the reported quantity may be an error probability, an infidelity, or a value derived from a benchmark’s decay fit. Those measures can be related, but they are not automatically interchangeable; retain the metric’s stated name and definition.
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For a plain-language example, the National Academies explains that a 1% error rate for a given type of gate operation means that, on average, it produces the correct measured result 99 times out of 100. That is an average for the specified gate type, not a promise about every individual operation or a claim that a complete algorithm has a 99% chance of success. A circuit uses many operations, and their errors can accumulate, interact, or spread.
How are quantum gate error rates measured?
Randomized benchmarking
Randomized benchmarking estimates how errors affect sequences of operations. A typical experiment chooses random gate sequences, adds a recovery operation intended to undo each sequence, and measures how often the system returns to its starting state. The experiment is repeated with sequences of different lengths. As errors accumulate, the return probability typically decays with sequence length; researchers fit that decay to obtain a benchmark estimate.
The method is useful because direct process tomography can be affected by imperfections in state preparation, measurement, and gates. NIST’s 2007 paper describes randomized benchmarking as a way to estimate computationally relevant errors without relying on perfectly accurate state preparation and measurement. That reduces dependence on those imperfections; it does not make the result independent of the chosen protocol or its assumptions, nor does one aggregate value reveal every error mechanism.
IBM’s explanation of layer fidelity likewise describes measuring errors across increasing numbers of random gates, fitting an exponential decay, and extracting a fidelity-related quantity. The exact interpretation depends on the benchmark used, so a number should be read alongside its protocol rather than as a universal score.
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Examples from published experiments
The figures below illustrate why operation and experimental context matter. They are results reported in specific papers, not current, directly comparable rankings of quantum computers.
| Source and context | Reported result | What it describes |
|---|---|---|
| NIST, 2007, experimental paper | 0.00482(17) error probability per randomized one-qubit π/2 pulse | A particular randomized one-qubit pulse result in that experiment. |
| NIST, 2012, trapped-ion experimental procedure | 0.162 ± 0.008 error per randomized two-qubit Clifford; 0.069 ± 0.017 per phase gate | Two different operation groupings measured in the same reported experimental context; they should not be treated as the same metric. |
Which quantum error metrics are different?
“Quantum error rate” can refer to results with different scopes. Identify what was tested before comparing figures.
- Single-qubit gate error: estimates performance for a specified one-qubit gate set or pulse protocol.
- Two-qubit gate or Clifford error: characterizes entangling operations or a defined group of operations. Such tests involve different interactions and calibration challenges than single-qubit tests. NIST’s 2012 paper, for example, reports separate results for a randomized two-qubit Clifford and an individual phase gate.
- Readout error: concerns whether measurement assigns the state correctly. It is distinct from the error in carrying out a gate.
- Leakage: occurs when population leaves the computational subspace used to encode qubits. IBM Research’s 2018 work treats leakage and seepage rates alongside average gate fidelity to characterize gates with leakage.
- Crosstalk: is an unintended influence of an operation or signal on another qubit or control line. Errors can also spread through two-qubit interactions.
- Layer or system benchmark: evaluates collections of gates and qubits in circuit-like patterns. IBM describes layer fidelity as a benchmark that can reveal information about processor behavior, individual qubits and gates, and crosstalk.
Are quantum error rates the same as fidelity?
No—not as a rule. Fidelity measures how closely a prepared state or implemented operation matches a target under a stated definition. An error quantity may be mathematically related to a fidelity measure, but the relationship depends on which fidelity, error definition, and protocol are being used. A decay fit may also yield a fidelity-related quantity rather than an error probability directly. When reporting or comparing a result, use the quantity the source actually names and check how it was derived.
Does a 1% quantum error rate mean a program has a 1% chance of failing?
No. It means roughly one error per hundred relevant trials in the stated average for the specified operation or benchmark, not a 1% failure probability for a full algorithm. A program contains a sequence of operations, and its outcome depends on how many operations it uses, their interactions, and which error sources the reported measure includes. A gate-level percentage by itself cannot predict the program’s overall success probability.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you compare published quantum error rates?
Before treating two figures as comparable, check that they answer the same question:
- What operation or benchmark was tested? A one-qubit pulse, a two-qubit Clifford, readout, and a processor layer do not share the same scope.
- Which protocol and assumptions were used? The sequence design, fit, and definition affect what the reported value means.
- Which errors are included? Establish whether readout, crosstalk, leakage, or other effects are part of the measurement or require separate characterization.
- Which device and when? Calibration and hardware change, so a result needs its device context and reporting date.
Even matching gate-level results do not establish which computer is more useful for a particular task. A gate figure alone does not describe system size, connectivity, gate speed, or the circuit depth the machine can handle.
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Sources and further reading
- NIST: Randomized Benchmarking of Quantum Gates (2007)
- NIST: Randomized Benchmarking of Multiqubit Gates (2012)
- IBM Quantum: Updating how we measure quantum quality and speed (20 November 2023)
- NIST: Quantum Computing Explained
- IBM Quantum Learning: Noise and errors
- National Academies: Quantum Computing: Progress and Prospects, Chapter 3
- IBM Research: Quantification and characterization of leakage errors (8 March 2018)
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