A quantum error rate estimates how often a particular quantum operation deviates from its intended behavior under a stated measurement method. It is not a free-standing prediction that a complete quantum program will fail—or succeed—with the same probability. To interpret a reported rate, identify the operation, benchmark protocol, device, and error mechanisms the result includes.
What does quantum error rate mean?
A quantum error rate is an estimate tied to a defined operation or benchmark. Depending on the source, it may be reported as an error probability, an infidelity, or a value derived from a benchmark’s decay fit. These are related quantities, but they are not automatically interchangeable: check the reported definition and protocol.
For a plain-language example, the National Academies explains that a 1% error rate for a given type of gate means that operation produces the correct measured result, on average, 99 times out of 100 (National Academies, Quantum Computing: Progress and Prospects, Chapter 3). The qualifier matters: it describes an average for the specified gate type, not the chance that an entire algorithm succeeds.
A circuit applies many gates, and errors can accumulate or interact. A gate-level percentage therefore cannot be converted directly into a whole-program success probability without considering the circuit, device, and error behavior.
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Randomized benchmarking
Randomized benchmarking estimates performance by applying random sequences of gates, then adding a recovery operation intended to undo each sequence. The experiment measures how often the system returns to its initial state and repeats the process for sequences of different lengths. As errors accumulate, the measured success decays with sequence length; fitting that decay yields a benchmark estimate.
The method is useful partly because it reduces dependence on perfectly prepared starting states and perfectly measured outcomes. NIST’s 2007 paper describes randomized benchmarking as estimating computationally relevant errors without relying on accurate state preparation and measurement, in contrast with limitations that can affect process tomography (NIST, “Randomized Benchmarking of Quantum Gates,” 2007).
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That does not make the result a complete inventory of every error. The value depends on the chosen protocol and its assumptions, and an aggregate estimate may not reveal each error mechanism separately. IBM’s explanation of layer fidelity, for example, describes examining errors across increasing numbers of random gates and fitting an exponential decay (IBM Quantum, “Updating how we measure quantum quality and speed,” 20 November 2023).
Why a 1% gate rate is not a 1% program-failure rate
For the specified gate type, 1% is a useful shorthand for roughly one error per hundred relevant trials on average. A program containing many operations has many opportunities for errors, and interactions can spread or compound them. The rate alone does not say whether the program’s final answer will be correct.
Which quantum error metrics are different?
| Metric | What it describes | What to watch for |
|---|---|---|
| Single-qubit gate error | Performance for a particular one-qubit gate set or pulse protocol. | Do not assume it applies to other gates or to the processor as a whole. |
| Two-qubit gate or Clifford error | Performance for entangling operations or a specified group of gates. | Confirm which operation grouping was tested; the value may differ from an individual gate’s result. |
| Readout error | Whether the measured state is assigned correctly. | It is distinct from an error in carrying out a gate. |
| Leakage | Population leaving the computational subspace used to encode qubits. | It may need separate characterization. IBM Research discusses leakage and seepage rates alongside average gate fidelity for gates with leakage (IBM Research, “Quantification and characterization of leakage errors,” 8 March 2018). |
| Crosstalk | Unintended influence of an operation or signal on another qubit or control line. | A favorable average gate figure may not capture errors caused by simultaneous or nearby operations. IBM’s learning material discusses how two-qubit interactions can allow errors to spread (IBM Quantum Learning, “Noise and errors”). |
| Layer or system benchmark | Behavior of collections of gates and qubits in circuit-like patterns. | It can reveal processor-level effects, including information about qubits, gates, and crosstalk, but its scope differs from a single-gate measurement. |
IBM describes layer fidelity as a benchmark that captures a processor’s ability to run circuits while also exposing information about individual qubits, gates, and crosstalk (IBM Quantum, “Updating how we measure quantum quality and speed,” 20 November 2023).
Are quantum error rates the same as fidelity?
No—not as terms to use interchangeably without checking definitions. Fidelity measures agreement with a target state or operation under a specified definition; an error rate may be defined as a probability or derived from a benchmark. They can be mathematically related in a particular setting, but the relationship depends on the quantity and protocol. Preserve the name the source uses rather than relabeling a fidelity result as an error probability.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What do published quantum error-rate numbers tell you?
Published figures are meaningful only within the experiment and operation they describe. For example, NIST’s 2007 paper reports an error probability of 0.00482(17) per randomized one-qubit π/2 pulse in its experimental setup (NIST, “Randomized Benchmarking of Quantum Gates,” 2007). It is a historical experimental result, not a current cross-platform benchmark.
NIST’s 2012 multiqubit work reports 0.162 ± 0.008 error per randomized two-qubit Clifford and 0.069 ± 0.017 per phase gate in its trapped-ion experiment (NIST, “Randomized Benchmarking of Multiqubit Gates,” 2012). Those figures describe different operation groupings in that particular procedure, so they are not directly comparable to one another as if they measured the same gate.
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NIST’s educational overview says that “the best quantum computers today” contain hundreds of interconnected qubits and make an error roughly once in every thousand operations (NIST, “Quantum Computing Explained”). This is broad educational context, not a device-specific specification; it should not be treated as a uniform rate across hardware or operation types.
How to compare two reported error rates
Before deciding that one device or result is better, check whether the figures answer the same question:
- Operation: Is each number for the same gate, gate class, or benchmark?
- Definition and protocol: Does each source report the same kind of error quantity, measured with a comparable method and assumptions?
- Scope: Is the result for one gate, a layer, or a broader processor benchmark?
- Included effects: Does it include readout error, crosstalk, or leakage, or are those characterized separately?
- Device and date: Which hardware and experimental setup produced the result, and when was it measured?
A lower gate-level number alone does not establish that a computer is more useful for a particular workload. System size, connectivity, gate speed, circuit depth, and other operational constraints also matter; a benchmark with a broader scope may answer a different practical question.
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