com.quantum-expectations/quantum-expectations

Official11 tools

Quantum Expectations

Quantum error-correction feasibility: success probability, qubit overhead, records, trends.

Analyzes quantum error correction feasibility and tracks success metrics over time.

quantum error correctionsuccess probabilityqubit overheadquantum computingfeasibility analysis

Captured live from the server via tools/list.

compute_expectation

Given a quantum circuit (2-qubit error rate p, qubit count n, depth d), compute the effective error rate, success probability, and optional surface-code or qLDPC overhead. The response is self-describing (formulas, assumptions, caveats, glossary, SOTA hardware, historic series with source URLs) so an agent can reason from one call. For the inverse ("what hardware do I need?") use compute_required_error_rate; to rank multiple platforms in one call use compare_hardware_scenarios.

Parameters (8)

qubitErrorRatenumber
Per-gate 2-qubit error rate p, in (0, 0.1]. Supply exactly one of qubitErrorRate or hardwareId.
hardwareIdstring
Alias for qubitErrorRate: resolves to the 2-qubit error rate of the given SOTA hardware entry from list_current_quantum_computers. Supply exactly one of qubitErrorRate or hardwareId.
numQubitsintegerrequired
compDepthintegerrequired
useErrorCorrectionboolean
errorCorrectionCodestring
Either "surface" (default when useErrorCorrection=true) or a qLDPC code id from list_qldpc_codes. "surface-code" is accepted as an alias for "surface".
distanceSurfaceCodeinteger
verboseboolean
When false, omits hardwareContext, formulas, assumptions, caveats, glossary, examples, and exampleProblems from the response — leaving only modelVersion, scenario, and result. Use for parameter sweeps where that context would repeat unchanged.

compute_required_error_rate

Inverse of compute_expectation. Given a circuit (numQubits, compDepth) and an acceptable effective error rate, return the required per-gate logical error rate and, for every EC option (no-EC, surface-code per distance, every qLDPC code), the required physical error rate plus the subset of current SOTA hardware that already qualifies. Answers "what hardware do I need to run this algorithm?".

Parameters (3)

numQubitsintegerrequired
Number of logical qubits n in the circuit.
compDepthintegerrequired
Circuit depth d (sequential 2-qubit gate layers). Accepts values up to 1e13.
acceptableErrorRatePercentnumberrequired
Upper bound on the effective error rate, as a percent. Default website convention is 33 (i.e. ≤33% effective error is "acceptable").

compare_hardware_scenarios

Run the same circuit against multiple current SOTA hardware entries in one call so an agent can rank platforms without N sequential compute_expectation calls. Defaults to every entry in list_current_quantum_computers when hardwareIds is omitted.

Parameters (6)

numQubitsintegerrequired
compDepthintegerrequired
useErrorCorrectionboolean
errorCorrectionCodestring
Either "surface" (default when useErrorCorrection=true) or a qLDPC code id. "surface-code" is accepted as an alias for "surface".
distanceSurfaceCodeinteger
Required when useErrorCorrection=true and errorCorrectionCode="surface" (odd integer).
hardwareIdsarray
Subset of QUANTUM_COMPUTERS ids to compare. Omit to compare every entry.

list_current_quantum_computers

Return the representative-entry table of current SOTA quantum computers (id, hardware type, physical qubit count, 2-qubit error rate). Same data that powers the website's "Current Quantum Computers" table.

No parameters.

list_hardware_timings

Return per-platform gate-cycle timings (2Q gate time, readout time, in SI seconds) plus the representative device and native 2Q gate name, with source URLs. Joins list_current_quantum_computers via `hardwareType`. Use for runtime estimates, ratio analysis, or as inputs to compute_quantum_volume_rate. Values are representative current-generation numbers, not records.

No parameters.

compute_quantum_volume_rate

Compute the Quantum Volume Rate (QV/second): QVR = V_Q / (log2(V_Q) * t_2Q + t_meas). First-order estimate of how fast a device prepares one QV-sized square circuit (one native 2Q gate per QV layer + one end-of-circuit measurement). OVERSTATES achievable rate: real compilation inflates the 2Q-gate count per layer; omits reset/SPAM, mid-circuit measurement, and classical-control latency. For a production throughput metric, see IBM's CLOPS (arXiv:2110.14108).

Parameters (3)

quantumVolumeintegerrequired
Quantum volume V_Q (integer ≥ 2, e.g. 64 for a depth-log2=6 square circuit).
t2QSecondsnumberrequired
Native 2-qubit gate time in seconds (e.g. 60e-9 for a 60 ns CZ).
tMeasurementSecondsnumberrequired
End-of-circuit measurement/readout time in seconds (e.g. 5e-3 for 5 ms).

fit_historic_series

Fit a log-linear trend (ln(value) = slope * year + intercept) to one historic series — fidelity or qubit-count — for one hardware type. Atomic primitive: compose with list_current_quantum_computers, compute_required_error_rate, or your own modelling to answer "when might hardware reach X?". residualStdDev is the BIASED (maximum-likelihood) RMS — divides by n, not (n - 2); on small series (n ≈ 3–5) inflate by √(n / (n - 2)) before building confidence intervals.

Parameters (3)

seriesTypestringrequired
Which historic series to fit: "fidelity" (2-qubit gate error rate) or "qubit-count" (physical qubits).
hardwareTypestringrequired
Hardware platform as used by get_historic_series.
targetValuenumber
Optional. When supplied, the response includes yearAtTargetValue — the extrapolated year the fit crosses this value (error rate for fidelity series, qubit count for qubit-count series). Null if slope is flat.

list_example_algorithms

Return the curated list of example quantum algorithms with published resource estimates (qubit count, depth/gate count, source paper URL). Useful for comparing what algorithms need vs. what hardware can deliver.

No parameters.

list_qldpc_codes

Return the catalog of supported qLDPC codes (id, label, family, n, k, d, threshold, prefactor, logicalErrorExponent, source URL). Use a code's `id` as the `errorCorrectionCode` input to `compute_expectation`.

No parameters.

get_historic_series

Return the full historic time series — either two-qubit gate error rates ("fidelity") or physical qubit counts ("qubit-count") — broken down by hardware type. Each datapoint carries a source URL. Use this to extrapolate trends — "when might hardware reach X?" — or pair with fit_historic_series for a log-linear fit on one hardware type.

Parameters (1)

seriesTypestringrequired
"fidelity" → 2-qubit gate error rates; "qubit-count" → physical qubit counts.

get_agent_brief

Return the plain-text site brief describing scope, assumptions, the honesty clause, and the API contract. Mirrors the /agent.txt document served by the website.

No parameters.

Install

claude_desktop_config.json

{
  "mcpServers": {
    "quantum-expectations": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://www.quantum-expectations.com/api/mcp"
      ]
    }
  }
}

Desktop config is stdio-only; this bridges via mcp-remote. Native remote: Settings > Connectors.