Quantum Expectations

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.

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.

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 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).

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?".

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.

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 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.

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.

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.

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.

Return the catalog of supported qLDPC codes (id, label, family, n, k, d, circuitLevelDistance, ancilla counts, roundsPerLogicalOp, threshold, prefactor [per block per syndrome cycle], logicalErrorExponent [= d_circ/2], source URLs). Use a code's `id` as the `errorCorrectionCode` input to `compute_expectation`.