SPDX-License-Identifier: AGPL-3.0-or-later¶
Commercial license available¶
© Concepts 1996–2026 Miroslav Šotek. All rights reserved.¶
© Code 2020–2026 Miroslav Šotek. All rights reserved.¶
ORCID: 0009-0009-3560-0851¶
Contact: www.anulum.li | protoscience@anulum.li¶
scpn-quantum-control — Pipeline Performance Benchmarks¶
Pipeline Performance Benchmarks¶
Every module in scpn-quantum-control is verified as wired into the pipeline
(not decorative) by tests/test_pipeline_wiring_performance.py (113 tests) and
per-module pipeline tests embedded in each test file. This page documents the
measured wall-time performance for every subsystem.
Test infrastructure¶
pytest tests/test_pipeline_wiring_performance.py -v -s # 113 tests, prints benchmarks
pytest tests/test_rust_path_benchmarks.py -v -s # 51 tests, Rust parity + timing
Hardware: ML350 Gen8, 2× Xeon E5-2650v2, 128 GB RAM, Ubuntu 24.04. Python: 3.12.3 with Qiskit 1.4.5, Aer 0.17.2. Rust: scpn-quantum-engine 0.2.0 (PyO3 + rayon).
1. Bridge Layer¶
The bridge compiles SCPN coupling matrices (K_nm) into quantum objects.
Knm to Hamiltonian¶
| System size | Compilation time | Output |
|---|---|---|
| L=2 (4×4 Hilbert) | <0.1 ms | SparsePauliOp, 2 qubits |
| L=4 (16×16 Hilbert) | <0.1 ms | SparsePauliOp, 4 qubits |
| L=8 (256×256 Hilbert) | <0.1 ms | SparsePauliOp, 8 qubits |
| L=16 (65536×65536 Hilbert) | ~6.7 ms | SparsePauliOp, 16 qubits, 256 Pauli terms |
Rust path: build_xy_hamiltonian_dense matches Qiskit SparsePauliOp.to_matrix()
to machine precision (atol=1e-10). Dense matrix construction in Rust takes 0.02 ms
for 3-qubit systems.
Knm to Ansatz¶
| System size | Reps | Parameters | Time |
|---|---|---|---|
| L=2 | 2 | 8 | <0.1 ms |
| L=4 | 2 | 16 | <0.1 ms |
| L=8 | 2 | 32 | <0.1 ms |
| L=16 | 1 | 32 | <0.1 ms |
The Knm-informed ansatz uses coupling topology to determine entanglement gates, producing fewer parameters than generic two_local (12 vs 18 for 3 qubits). Benchmark: knm_informed E=-3.19 beats two_local E=-2.68 at equal iterations.
Knm Construction (Rust)¶
| Function | Input | Time | Speedup |
|---|---|---|---|
build_knm(16, 0.45, 0.3) |
16×16 matrix | 0.02 ms | 4.7× vs Python |
Rust build_knm includes paper27 overrides (L1-L2, L3-L5, L1-L16 boosted
couplings) — exact parity with Python build_knm_paper27.
2. Phase Solvers¶
QuantumKuramotoSolver¶
The core solver maps Kuramoto dynamics to Trotterised XY Hamiltonian evolution.
| Operation | System | Time | Output |
|---|---|---|---|
run(t_max=0.3, dt=0.1) |
4 qubits | 16.5 ms | R trajectory: 0.806 → 0.796 → 0.766 |
evolve(t=0.5, trotter_steps=3) |
4 qubits | ~5 ms | QuantumCircuit, depth ~45 |
energy_expectation(sv) |
4 qubits | <1 ms | float |
Quantum-classical agreement: R(quantum)=0.702 vs R(classical)=0.700 at t=0.2, dt=0.1, trotter_per_step=5 — 0.3% deviation.
Trotter convergence: Error decreases as O(t²/n) for first-order, O(t³/n²) for second-order Suzuki-Trotter. At 4 qubits, second-order produces strictly lower Frobenius error than first-order at equal step count.
PhaseVQE¶
| Operation | System | Time | Output |
|---|---|---|---|
solve(maxiter=20, seed=42) |
2 qubits | ~150 ms | E=-3.94, exact=-3.94 |
solve(maxiter=30, seed=0) |
3 qubits | ~200 ms | E, exact_energy, gap, params |
Variational principle verified: VQE energy >= exact ground energy (within 0.5 tolerance for short optimisation).
VarQITE (Imaginary Time Evolution)¶
| Operation | System | Time | Output |
|---|---|---|---|
varqite_ground_state(tau=0.5, n_steps=5) |
3 qubits | 196.8 ms | E=-4.783 vs exact=-4.783 |
0.0% error — VarQITE achieves exact ITE convergence on 3-qubit system. Energy trajectory: -4.753 → -4.783 (monotonic decrease).
QuantumUPDESolver (Trotter UPDE)¶
| Operation | System | Time | Output |
|---|---|---|---|
run(n_steps=5, dt=0.05) |
4 qubits | 20.5 ms | R: 0.806 → 0.804 → 0.796 → 0.783 → 0.765 → 0.743 |
step(dt=0.1) |
3 qubits | ~4 ms | R_global, theta |
Second-order Trotter (trotter_order=2) passes through correctly to underlying
solver. Reset reinitialises state exactly (first step after reset matches first
step from fresh solver).
Adiabatic State Preparation¶
| Operation | System | Time | Output |
|---|---|---|---|
adiabatic_ramp(K_target=3.0, T=5.0, n_steps=15) |
3 qubits | 54.4 ms | min_gap=0.0012 at K=2.80 |
Fidelity degrades through the BKT transition where the gap closes. The gap minimum at K=2.80 confirms the transition location.
Floquet-Kuramoto (Time Crystal)¶
| Operation | System | Time | Output |
|---|---|---|---|
floquet_evolve(K=1.0, amp=0.5, freq=2.0) |
2 qubits | 0.6 ms | R(t), subharmonic ratio |
scan_drive_amplitude(5 amplitudes) |
2 qubits | ~3 ms | subharmonic ratio per amplitude |
DTC candidate detection via subharmonic_ratio > threshold. Drive signal oscillates between K_base(1-amp) and K_base(1+amp) as expected.
3. Hardware Layer¶
HardwareRunner (Simulator)¶
| Operation | System | Time | Output |
|---|---|---|---|
connect() |
AerSimulator | ~50 ms | Backend ready |
transpile(GHZ circuit) |
4 qubits | ~10 ms | ISA circuit, depth ~10 |
run_sampler(shots=1000) |
4 qubits | ~100 ms | counts dict |
circuit_stats() |
— | <1 ms | depth, n_qubits, ECR count |
Fractional gates: With use_fractional_gates=True, Kuramoto circuit depth
reduces from ~80 to ~60 (25% reduction) for 4 qubits, 2 Trotter steps.
RZZ gates remain native instead of decomposing to ECR+RZ.
Noise Model (Heron r2)¶
| Operation | System | Time | Output |
|---|---|---|---|
heron_r2_noise_model() |
— | <1 ms | NoiseModel |
| Noisy Bell pair (10k shots) | 2 qubits | ~150 ms | non-ideal counts |
| Noisy Kuramoto R comparison | 3 qubits | 1349 ms | R_clean=0.734, R_noisy=0.734 |
At default Heron r2 parameters (CZ error=0.005), noise degradation is minimal (R_clean ≈ R_noisy). Higher CZ error (0.1) produces measurable non-ideal counts.
Trapped-Ion Backend¶
| Operation | System | Time | Output |
|---|---|---|---|
transpile_for_trapped_ion() |
4 qubits | ~5 ms | All-to-all connectivity, no SWAPs |
Kuramoto circuits transpile without SWAP gates (ion trap all-to-all). Unitarity preserved (Operator equivalence verified).
Circuit Depth Regression¶
| System | Trotter reps | Transpiled depth | Gate count |
|---|---|---|---|
| 2q, 1 rep | 1 | <50 | <100 |
| 4q, 1 rep | 1 | <100 | <300 |
| 4q, 3 reps | 3 | 134 | ~200 |
| 8q, 1 rep | 1 | <300 | <600 |
| 16q, 1 rep | 1 | <1000 | ~1500 |
Depth scales sub-linearly with reps (3 reps < 4× depth of 1 rep due to gate cancellation in transpilation).
QASM Export¶
| Operation | System | Time | Output |
|---|---|---|---|
export_trotter_qasm(K, omega, t=0.5, reps=3) |
4 qubits | 3.4 ms | 1903 chars, 48 gates |
Exports OpenQASM 3.0 with qubit declarations and gate definitions.
4. Error Mitigation¶
Zero-Noise Extrapolation (ZNE)¶
| Operation | System | Time | Output |
|---|---|---|---|
| Fold at scales [1,3,5] + extrapolate | 3 qubits | 34.4 ms | R_ZNE estimate |
Folded circuits preserve unitarity (norm=1.0 at all odd scales). Fit residual >= 0. On noiseless simulator, all scale values are identical (folding is identity).
Probabilistic Error Cancellation (PEC)¶
| Operation | System | Time | Output |
|---|---|---|---|
pauli_twirl_decompose(0.05) |
1 qubit | <0.01 ms | 4 coefficients |
pec_sample(circuit, p=0.05, n=200) |
1 qubit | 160.9 ms | mitigated |
Rust path: pec_coefficients(p) matches Python pauli_twirl_decompose(p) to
machine precision (atol=1e-10). Rust pec_sample_parallel(100k samples) takes
49-91 ms using rayon parallelism.
Quasi-probability invariant: identity coefficient > 1, error coefficients < 0, sum = 1.0 (trace preservation).
5. Quantum Error Correction¶
ControlQEC (Surface Code)¶
| Operation | System | Time | Output |
|---|---|---|---|
ControlQEC(distance=3) |
18 data qubits | <0.1 ms | Decoder ready |
get_syndrome() + decode() |
d=3 | 0.6 ms | correction vector |
Below-threshold correction: >80% success at p=0.01. Above-threshold: significant failure at p=0.3. Zero-error syndrome is all-zero (verified).
FaultTolerantUPDE (Repetition Code)¶
| Operation | System | Time | Output |
|---|---|---|---|
build_step_circuit(dt=0.1) |
2 osc, d=3 | <0.1 ms | 10-qubit circuit |
step_with_qec(dt=0.1) |
3 osc, d=3 | 0.3 ms | syndromes, errors_detected |
Qubit layout: n_osc × (2d-1) physical qubits. Contains RZZ (transversal coupling), CX (encoding + syndrome), RZ (field terms).
SurfaceCodeUPDE¶
| Operation | System | Time | Output |
|---|---|---|---|
SurfaceCodeUPDE(n_osc=4, code_distance=3) |
4 oscillators | <1 ms | Resource model |
Total physical qubits = n_osc × (2d²-1). For d=3: 4 × 17 = 68 physical qubits.
6. QSNN (Quantum Spiking Neural Network)¶
QuantumSynapse¶
| Operation | Time | Output |
|---|---|---|
apply(circuit, pre, post) |
<0.01 ms | CRy gate appended |
theta = pi × (w - w_min) / (w_max - w_min). Effective weight = sin²(theta/2). Pre=|1> → post rotates; pre=|0> → post stays |0> (controlled rotation).
QuantumLIFNeuron¶
| Operation | Time | Output |
|---|---|---|
step(input_current=1.5) |
~1 ms | spike ∈ |
Membrane equation: v(t+1) = v(t) - (dt/tau)(v(t) - v_rest) + RIdt. Quantum mapping: P(spike) = sin²(theta/2) where theta encodes membrane potential.
QuantumSTDP¶
| Operation | Time | Output |
|---|---|---|
update(syn, pre=1, post=1) |
<0.01 ms | weight updated |
Hebbian LTP: pre+post fire → weight increases. LTD: pre fires, post doesn't → weight decreases. No pre spike → no change (verified).
QSNNTrainer¶
| Operation | System | Time | Output |
|---|---|---|---|
train(X, y, epochs=3) |
2×2 layer | 47.6 ms | loss history |
Parameter-shift gradient: g = (L(+pi/2) - L(-pi/2)) / 2. Gradient sign flips for opposite targets (antisymmetry). Zero learning rate → zero weight change (verified to 1e-14). Forward probabilities bounded [0,1].
SNNQuantumBridge¶
| Operation | System | Time | Output |
|---|---|---|---|
forward(spike_history) |
4→3 neurons | 2.2 ms | output currents |
Spike-to-rotation: firing_rate × pi ∈ [0, pi]. Higher rate → larger angle (monotonic). Measurement-to-current: P(|1>) × scale.
7. Identity Layer (Arcane Sapience)¶
IdentityAttractor¶
| Operation | System | Time | Output |
|---|---|---|---|
solve(maxiter=30, seed=42) |
3 qubits | 108.4 ms | E_0=-4.749, gap=1.383 |
Robustness gap = E_1 - E_0. Gap=1.383 provides strong identity protection. Eigenvalues sorted ascending. Variational bound: E_vqe >= E_exact. Stronger coupling → larger gap (verified).
Identity Fingerprint¶
| Operation | System | Time | Output |
|---|---|---|---|
identity_fingerprint(K, omega) |
4 qubits | ~150 ms | commitment (SHA-256 hex) |
Returns dict with commitment, spectral data (fiedler, eigenvalues), ground_energy, n_parameters. Different K → different commitment. Spectral data deterministic.
Challenge-Response Protocol¶
| Operation | System | Time | Output |
|---|---|---|---|
prove_identity(K, challenge) |
3 qubits | <1 ms | response bytes |
verify_identity(K, challenge, response) |
3 qubits | <1 ms | True/False |
Wrong K produces wrong response → verification fails. Different challenges → different responses (no replay).
Robustness Certificate¶
| Operation | System | Time | Output |
|---|---|---|---|
compute_robustness_certificate(K, omega) |
3 qubits | 0.9 ms | gap=1.383, P_transition=5.2e-5 |
P_transition = 5.2×10⁻⁵ — probability of identity confusion under noise. Fidelity at depth: deeper circuits → lower fidelity (decoherence monotonicity).
8. Cryptographic Layer¶
Key Hierarchy¶
| Operation | System | Time | Output |
|---|---|---|---|
key_hierarchy(K, phases, R, nonce) |
4 layers | 0.11 ms | master (32 bytes) + 4 layer keys |
All layer keys unique. Master key differs from all layer keys. Same inputs →
same keys (deterministic). Different R or nonce → different keys.
verify_key_chain() detects tampered master, tampered layer keys, wrong nonce.
Topology Commitment¶
| Operation | System | Time | Output |
|---|---|---|---|
topology_commitment(K) |
4×4 matrix | <0.1 ms | 32-byte SHA-256 |
Deterministic hash of coupling topology. Combined pipeline (hierarchy + fingerprint + commitment): 0.46 ms.
SCPN-QKD Protocol¶
| Operation | System | Time | Output |
|---|---|---|---|
scpn_qkd_protocol(K, omega, alice, bob) |
4 qubits | 692 ms | QBER, raw keys, Bell |
QBER ∈ [0, 1]. Ground energy < 0. Raw key shapes match qubit allocation. Secure key length >= 0.
Evolving Key Phases¶
| Operation | System | Time | Output |
|---|---|---|---|
evolve_key_phases(K, omega, theta_0, t=0.5) |
4 layers | ~1 ms | (n_layers, n_samples) trajectory |
Kuramoto ODE integration via solve_ivp(RK45). Initial condition preserved at t=0.
All values finite. ODE failure → RuntimeError with message.
9. Analysis Layer¶
Finite-Size Scaling¶
| Operation | System | Time | Output |
|---|---|---|---|
finite_size_scaling(sizes=[2,3,4]) |
3 sizes | 0.8 ms | K_c per size + extrapolation |
K_c values finite. gap_min > 0. Extrapolation via BKT or power-law fit.
H1 Persistence¶
| Operation | System | Time | Output |
|---|---|---|---|
scan_h1_persistence(omega, n_points=10) |
4 osc | 14.9 ms | K_critical, p_h1 |
K_critical > 0. p_h1 ∈ [0, 1]. Vortex densities bounded. K values sorted.
OTOC Synchronisation Probe¶
| Operation | System | Time | Output |
|---|---|---|---|
otoc_sync_scan(K, omega, n_K=6, n_t=8) |
3 qubits | 7.6 ms | Lyapunov, R_classical |
R_classical bounded [0, 1]. Lyapunov values finite. OTOC detects transition: True.
Berry Phase¶
| Operation | System | Time | Output |
|---|---|---|---|
berry_phase_scan(omega, T, k_range) |
3 qubits | 6.6 ms | curvature peak at K=0.75 |
Fidelity ∈ [0, 1]. Spectral gap > 0. Curvature finite. Fidelity susceptibility chi_F peaks near BKT transition (max chi_F = 0.005).
Loschmidt Echo / DQPT¶
| Operation | System | Time | Output |
|---|---|---|---|
loschmidt_quench(K_i=0.5, K_f=3.0) |
3 qubits | 0.8 ms | 3 cusps detected |
|G(0)| = 1 exactly. Rate function r(0) = 0. Times monotonic. No-quench: |G(t)| = 1 for all t. Large quench: amplitude oscillations.
Krylov Complexity¶
| Operation | System | Time | Output |
|---|---|---|---|
krylov_complexity(H, Z0, t_max=5.0) |
3 qubits | 155 ms | peak K(t) = 3.031 |
K(0) = 0 (operator starts in first basis element). K(t) >= 0. K(t) <= d² (bounded by Hilbert space dimension). Lanczos b_n decay for finite dimension.
Rust path: lanczos_b_coefficients produces same coefficients as Python
(verified to atol=1e-6 on first few b_n).
Entanglement Entropy¶
| Operation | System | Time | Output |
|---|---|---|---|
entanglement_at_coupling(omega, T, K=2.0) |
4 qubits | 0.3 ms | S=0.928, gap=0.224 |
S ∈ [0, log₂(d)] where d = 2^(n/2). Schmidt gap ∈ [0, 1]. Weak coupling → S ≈ 0 (product state). Strong coupling → S > 0. Schmidt gap closes near BKT.
QFI Criticality¶
| Operation | System | Time | Output |
|---|---|---|---|
qfi_vs_coupling(omega, T, k_range) |
3 qubits | 8.5 ms | peak QFI=0.225 at K=3.07 |
QFI >= 0. Total QFI >= max single-generator QFI. Peak at K=3.07 confirms criticality-enhanced quantum correlations.
Quantum Speed Limit¶
| Operation | System | Time | Output |
|---|---|---|---|
compute_qsl(K, omega, t=1.0) |
3 qubits | 10.4 ms | tau_MT, tau_ML bounds |
Mandelstam-Tamm bound tau_MT >= 0. Margolus-Levitin bound tau_ML >= 0. Actual time tau_actual >= both bounds (QSL is a lower bound).
Spectral Form Factor¶
| Operation | System | Time | Output |
|---|---|---|---|
compute_sff(K, omega, n_times=20) |
4 qubits | 1.2 ms | r_bar=0.488, gap=1.132 |
K(t=0) = 1 exactly (trace identity). SFF ∈ [0, 1]. Times monotonic. Level spacing ratio r_bar = 0.488 (near GOE Wigner-Dyson 0.536 — quantum chaotic).
Magic (Non-stabilizerness)¶
| Operation | System | Time | Output |
|---|---|---|---|
magic_vs_coupling(omega, T, k_range) |
3 qubits | ~5 ms | SRE peak |
SRE (stabiliser Renyi entropy) M₂ >= 0. Weak coupling → M₂ ≈ 0 (stabiliser ground state). Strong coupling → M₂ > 0 (magic resource). Berry curvature F_μν is antisymmetric (traceless).
Lindblad NESS¶
| Operation | System | Time | Output |
|---|---|---|---|
compute_ness(omega, T, K=2.0, gamma=0.1) |
2 qubits | ~1 ms | R_ness, purity |
Purity ∈ [1/d, 1]. R_ness ∈ [0, 1]. gamma=0 → NESS = ground state (R_ness ≈ R_ideal). Purity decreases with noise (generally).
Hamiltonian Learning¶
| Operation | System | Time | Output |
|---|---|---|---|
measure_correlators + learn_hamiltonian |
3 qubits | 34.6 ms | loss=0, corr_error=0 |
Correlator matrix symmetric, zero diagonal, bounded [-2, 2]. Learned K symmetric, non-negative. Perfect recovery for 3-qubit system (loss=0). Self-consistent: true K as init → near-zero error.
Hamiltonian Self-Consistency¶
| Operation | System | Time | Output |
|---|---|---|---|
self_consistency_from_exact(K, omega) |
2 qubits | 10.9 ms | Frobenius=1.81, loss=0 |
2-qubit inverse problem is degenerate: loss=0 but Frobenius error=1.81 because different K values produce identical correlators.
XXZ Phase Diagram¶
| Operation | System | Time | Output |
|---|---|---|---|
anisotropy_phase_diagram(3δ × 6K) |
3 qubits | 36.1 ms | K_c(Δ=0)=0.5, K_c(Δ=0.5)=1.2 |
XY (Δ=0) and Heisenberg (Δ=1) produce different gap structure. All gaps > 0.
QRC Phase Detector¶
| Operation | System | Time | Output |
|---|---|---|---|
qrc_phase_detection(8 train, 2 test) |
3 qubits | 39.3 ms | accuracy=100%, 36 features |
Self-probing: reservoir features from ground state observables. Linear readout achieves perfect phase classification on well-separated data.
10. Application Layer¶
Quantum Reservoir Computing¶
| Operation | System | Time | Output |
|---|---|---|---|
reservoir_ridge_regression(12 samples) |
3 qubits | 33.9 ms | MSE=0.022 |
Feature matrix has non-trivial rank (expressive reservoir). Higher weight → more features. Ridge regression produces actionable predictions.
Quantum Kernel¶
| Operation | System | Time | Output |
|---|---|---|---|
compute_kernel_matrix(5 samples) |
3 qubits | 16.1 ms | PSD Gram matrix |
Mercer conditions verified: symmetric, PSD (min eigenvalue=0.028 > 0), diagonal=1. K(x,x) = 1. Close inputs → high overlap (>0.95). Different Knm → different kernel.
Disruption Classifier¶
| Operation | System | Time | Output |
|---|---|---|---|
run_disruption_benchmark(10+5) |
3 qubits | 297 ms | accuracy=80% |
Kernel Gram matrix symmetric + PSD. Binary predictions. Accuracy bounded [0, 1].
Quantum Disruption (ITER)¶
| Operation | System | Time | Output |
|---|---|---|---|
predict(features) |
5 qubits | 4.6 ms | risk=0.495 |
DisruptionBenchmark(20+10, 2 epochs) |
5 qubits | 11.9 s | accuracy=70% |
Feature normalisation clamps to [0, 1]. Prediction deterministic for same params. Circuit depth > 0. Training updates parameters.
FMO Photosynthetic Benchmark¶
| Operation | System | Time | Output |
|---|---|---|---|
fmo_benchmark(K, omega) |
7 sites | 1.4 ms | topology ρ=0.304 |
SCPN vs FMO topology correlation ρ=0.304 (weak positive). FMO self-comparison: ρ=1.0. FMO coupling: symmetric, non-negative, zero diagonal, 7×7.
Quantum Advantage Scaling¶
| Operation | System | Time | Output |
|---|---|---|---|
run_scaling_benchmark(sizes=[3,4]) |
3-4 qubits | 101 ms | timing comparison |
n=3: classical=23 ms, quantum=11 ms (quantum wins). n=4: classical=26 ms, quantum=34 ms (classical wins). Crossover near n=4.
11. Bridge Adapters¶
SSGF Adapter¶
| Operation | System | Time | Output |
|---|---|---|---|
| W→H→encode→decode | 4 oscillators | 1.5 ms | R_global=0.767 |
| SSGFQuantumLoop.quantum_step | 4 oscillators | ~9 ms | theta updated, R returned |
Encoding: 2 gates per oscillator (Ry + Rz). Normalisation preserved. Uniform phases → R ≈ 1. Opposite phases → R ≈ 0.
SSGF Spectral Bridge¶
| Operation | System | Time | Output |
|---|---|---|---|
spectral_bridge_analysis(K, omega) |
4 oscillators | 0.2 ms | fiedler=0.872, QPE=7 bits |
Fiedler > 0 for connected graph. Eigenvalues non-negative (Laplacian PSD). Disconnected graph → fiedler=0. QPE bits estimate for spectral resolution.
SSGF W Adapter¶
| Operation | System | Time | Output |
|---|---|---|---|
adapt_w_from_quantum(K, theta, lr=0.1) |
4 oscillators | 4.9 ms | max_update=0.027 |
W_updated symmetric, non-negative, zero diagonal. Correlators symmetric. lr=0 → no change. W changes with non-zero lr.
Orchestrator Adapter¶
| Operation | System | Time | Output |
|---|---|---|---|
from_orchestrator_state → to_scpn_control_telemetry |
3 layers | 0.07 ms | regime, R, stability |
Handles both dataclass and dict payloads. Legacy field names (locks, cross_alignment, stability, regime) resolved automatically.
Orchestrator Feedback¶
| Operation | System | Time | Output |
|---|---|---|---|
compute_orchestrator_feedback(K, omega) |
4 qubits | ~0.5 ms | action, confidence, R_global |
Actions: advance, hold, rollback. Confidence ∈ [0, 1]. R_global ∈ [0, 1]. Custom thresholds supported.
12. PGBO (Parameter-space Geometry Bridge)¶
| Operation | System | Time | Output |
|---|---|---|---|
compute_pgbo_tensor(K, omega) |
4 qubits | 6.7 ms | metric (6×6), curvature (6×6) |
Quantum Fisher metric: symmetric, PSD (det >= 0). Berry curvature: antisymmetric (traceless). Parameter count: C(n,2) upper-triangle couplings.
13. TCBO Observer¶
| Operation | System | Time | Output |
|---|---|---|---|
compute_tcbo_observables(K, omega) |
4 qubits | 4.6 ms | p_h1, TEE, string_order |
p_h1 ∈ [0, 1]. TEE finite. |string_order| <= 1. beta_0 + beta_1 ≈ 1 (connected components + loops = 1). Different coupling → different observables.
14. Trotter Error Analysis¶
Commutator Bounds¶
| Operation | System | Time | Output |
|---|---|---|---|
commutator_norm_bound + optimal_dt |
4 qubits | <0.1 ms | gamma=5.344, dt*=0.004, n_steps=268 |
Equal frequencies → gamma=0 (no Trotter error). Heterogeneous frequencies → larger gamma. Second-order bound < first-order. Optimal dt respects epsilon target.
Trotter Error Sweep¶
| Operation | System | Time | Output |
|---|---|---|---|
trotter_error_sweep(3t × 3reps) |
3 qubits | 483 ms | 2D error map |
Error at t=0: < 1e-10. Error decreases with reps. Error increases with time. Quadratic scaling: doubling t roughly quadruples error.
15. Experiment Registry¶
| Operation | Time | Output |
|---|---|---|
| List all experiments | 0.18 ms | 20 registered experiments |
Every experiment has: runner as first param, docstring > 10 chars, lowercase underscore name, no private experiments. At least half accept shots parameter.
16. Cutting Runner (Large-Scale)¶
| Operation | System | Time | Output |
|---|---|---|---|
run_cutting_simulation(n=16, max=8) |
16 oscillators | 39.3 ms | 2 partitions, R=1.0 |
run_cutting_simulation(n=24, max=8) |
24 oscillators | ~53 ms | 3 partitions |
run_cutting_simulation(n=32, max=8) |
32 oscillators | ~60 ms | 4 partitions |
Partitions: ceil(n/max_partition_size). R per partition bounded [0, 1]. Combined R bounded [0, 1]. Energy estimate finite.