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quantum-expectations
Quantum error-correction feasibility: success probability, qubit overhead, records, trends.
Tools
12
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streamable-http
Last checked
28h ago
Tools & capabilities
12 toolsRead from the running server on 28h ago.
compare_hardware_scenarios
read-only
compDepth*numQubits*hardwareIdsuseErrorCorrectiondistanceSurfaceCodeerrorCorrectionCode
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 ent… 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.
compute_expectation
read-only
verbosecompDepth*numQubits*hardwareIdqubitErrorRateuseErrorCorrection
+2
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 resp… 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.
compute_fault_tolerant_resources
read-only
tCount*dataBlockhardwareIdqubitErrorRatecycleTimeSecondsnumLogicalQubits*
+1
Given an algorithm stated as (numLogicalQubits, tCount) and a physical error rate (or hardwareId), derive the full surface-code + magic-state-distillation footprint from the genera… Given an algorithm stated as (numLogicalQubits, tCount) and a physical error rate (or hardwareId), derive the full surface-code + magic-state-distillation footprint from the general laws of the Litinski lattice-surgery cost model (no per-scenario constants): distillation factory choice, tile layout, required code distance, total physical qubits, and wall-clock time. Results are reported under TWO published logical-error fits (conservative + optimistic) because they disagree by 13-268x (d=7 to d=25) - always state both. Returns an explicit `infeasible` block when no cataloged factory or code distance can satisfy the error budget. Computes numbers only: comparing against classical alternatives and concluding "should this run on a quantum computer" stays with you, the calling agent (state the caveats when you do).
compute_quantum_volume_rate
read-only
t2QSeconds*quantumVolume*tMeasurementSeconds*
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… 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).
compute_required_error_rate
read-only
compDepth*numQubits*acceptableErrorRatePercent*
Inverse of compute_expectation. Given a circuit (numQubits, compDepth) and an acceptable effective error rate, return the required per-gate logical error rate (requiredLogicalError… Inverse of compute_expectation. Given a circuit (numQubits, compDepth) and an acceptable effective error rate, return the required per-gate logical error rate (requiredLogicalErrorRatePerGate: a number, or null only when the target is genuinely unreachable; never 0) 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. An option whose inverse lands above the code threshold is capped at min(MAX_P, threshold) and carries a `note` (any sub-threshold p satisfies it); `unreachableReason` is reserved for genuinely unreachable options. Answers "what hardware do I need to run this algorithm?".
fit_historic_series
read-only
seriesType*targetValuehardwareType*
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_… 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.
get_agent_brief
read-only
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. 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.
get_historic_series
read-only
seriesType*
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 carrie… 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.
list_current_quantum_computers
read-only
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… 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.
list_example_algorithms
read-only
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… 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. Each entry carries a `provenance` field: 'published-circuit' means the figure is reproducible from the source, 'attested-estimate' means the source withholds the circuit and the figure rests on the authors' attestation, with a `provenanceNote` giving the specifics. Carry that caveat whenever you quote an attested figure; do not present it as equivalently sourced.
list_hardware_timings
read-only
Return per-platform gate-cycle timings (2Q gate time, readout time, in SI seconds) plus the testbed they were measured on (`representativeDevice`) and the native 2Q gate name, with… Return per-platform gate-cycle timings (2Q gate time, readout time, in SI seconds) plus the testbed they were measured on (`representativeDevice`) and the native 2Q gate name, with source URLs. Joins list_current_quantum_computers via `hardwareType`, but the numbers are BEST-CASE DEMONSTRATIONS from small testbeds, not measurements on the joined devices, which run their gates and array readout orders of magnitude slower. Use for ratio analysis or as optimistic lower-bound inputs to runtime estimates and compute_quantum_volume_rate, and say so when you quote a runtime.
list_qldpc_codes
read-only