{
  "title": "IBM Quantum 150Q experiment ledger",
  "canonical_repo_url": "https://github.com/sankalpsthakur/ibm-quantum-150q-ising",
  "kaggle_url": "{{KAGGLE_URL}}",
  "experiments": [
    {
      "id": "E00",
      "execution": "classical + statevector",
      "input": "Eight industrial assets; choose a subset that curtails exactly 12 MW with minimum disruption.",
      "inference": "Exhaust all 256 schedules; separately optimize one-layer QAOA on a seeded statevector sampler.",
      "outcome": "Exact score 10.4; QAOA recovered the same bitstring; exact-state probability 0.0034.",
      "learning": "An auditable baseline is essential; this small instance proves correctness, not acceleration.",
      "job_id": "\u2014",
      "quantum_seconds": 0,
      "status": "COMPLETED",
      "evidence": "outputs/results.json"
    },
    {
      "id": "E01",
      "execution": "IBM hardware",
      "input": "150-qubit GHZ preparation measured in Z and X bases; 1,024 shots per basis.",
      "inference": "Estimate ideal all-equal Z population and global X parity as a two-basis coherence diagnostic.",
      "outcome": "Ideal Z population 0.000977; X parity +0.046875.",
      "learning": "Allocating 150 qubits did not preserve a high-fidelity cat state; this is not entanglement certification.",
      "job_id": "d9gjobkhonhs73abnl3g",
      "quantum_seconds": 3,
      "status": "COMPLETED",
      "evidence": "outputs/hardware_results.json"
    },
    {
      "id": "E02",
      "execution": "IBM hardware",
      "input": "The same eight-asset, exactly-12-MW demand-response QUBO at the optimized statevector parameters.",
      "inference": "Sample the compiled one-layer QAOA circuit and score every schedule classically.",
      "outcome": "Feasible probability 0.1465; exact optimum sampled 0.0049 (5/1024).",
      "learning": "Hardware can return the correct schedule, but the exact classical search remains faster for eight variables.",
      "job_id": "d9gjobkhonhs73abnl3g",
      "quantum_seconds": 0,
      "status": "COMPLETED",
      "evidence": "outputs/hardware_results.json"
    },
    {
      "id": "E03",
      "execution": "local simulator",
      "input": "Compiled order finding for N=15 with base 2 on eight simulated qubits.",
      "inference": "Use phase estimation to infer period 4, then classical GCD post-processing.",
      "outcome": "Recovered factors 3 and 5 in 0.129s.",
      "learning": "This validates the educational workflow only; it is not general or RSA-scale factorization.",
      "job_id": "\u2014",
      "quantum_seconds": 0,
      "status": "COMPLETED",
      "evidence": "outputs/hardware_results.json"
    },
    {
      "id": "E04",
      "execution": "classical exact",
      "input": "150 binary variables, 167 weighted XOR constraints, total weight 873, deterministic seed 20260723.",
      "inference": "Linearize XORs and solve the 317-variable MILP with SciPy/HiGHS at zero requested MIP gap.",
      "outcome": "Exact 865/873 (0.9908); 161/167 constraints; MIP gap 0.0; 3.287s.",
      "learning": "This is the production-quality answer and the truth baseline for every QPU sample.",
      "job_id": "\u2014",
      "quantum_seconds": 0,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_benchmark.json"
    },
    {
      "id": "E05",
      "execution": "IBM hardware",
      "input": "One-layer 150Q QAOA; 100 beta/gamma points; 1,024 shots each; zero SWAPs.",
      "inference": "Score 102,400 sampled 150-bit assignments and rank parameters by mean weighted objective.",
      "outcome": "Best mean ratio 0.6733; best sample ratio 0.8035.",
      "learning": "A broad hardware parameter sweep finds a useful region, but remains far below the exact classical optimum.",
      "job_id": "d9gk5gchonhs73abo5ag",
      "quantum_seconds": 30,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_benchmark.json"
    },
    {
      "id": "E06",
      "execution": "IBM hardware",
      "input": "Ten leading p=1 points with gate/measurement twirling and XpXm dynamical decoupling; 4,096 shots each.",
      "inference": "Re-score mitigated samples against the same exact optimum.",
      "outcome": "Best mitigated mean ratio 0.5563; best sample 0.7110.",
      "learning": "The combined mitigation stack degraded this circuit and required a controlled ablation.",
      "job_id": "d9gk64ogk0ls73f1mar0",
      "quantum_seconds": 14,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_benchmark.json"
    },
    {
      "id": "E07",
      "execution": "IBM hardware",
      "input": "p=2 QAOA; 50 transferred/jittered parameter schedules; 4,096 shots each; 668 two-qubit gates; zero SWAPs.",
      "inference": "Measure the mean and best-sample approximation ratios at a controlled circuit depth.",
      "outcome": "Best mean ratio 0.6903; best sample ratio 0.8208; usage 57s.",
      "learning": "Depth improves mean quality through p=6, then saturates/declines; isolated best samples are noisier than replicated means.",
      "job_id": "d9gk9kjsbqfc73eoops0",
      "quantum_seconds": 57,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_depth_and_mitigation.json"
    },
    {
      "id": "E08",
      "execution": "IBM hardware",
      "input": "p=3 QAOA; 50 transferred/jittered parameter schedules; 4,096 shots each; 1002 two-qubit gates; zero SWAPs.",
      "inference": "Measure the mean and best-sample approximation ratios at a controlled circuit depth.",
      "outcome": "Best mean ratio 0.7048; best sample ratio 0.8439; usage 57s.",
      "learning": "Depth improves mean quality through p=6, then saturates/declines; isolated best samples are noisier than replicated means.",
      "job_id": "d9gkajl0k0jc738gsv80",
      "quantum_seconds": 57,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_depth_and_mitigation.json"
    },
    {
      "id": "E09",
      "execution": "IBM hardware",
      "input": "p=4 QAOA; 50 transferred/jittered parameter schedules; 4,096 shots each; 1336 two-qubit gates; zero SWAPs.",
      "inference": "Measure the mean and best-sample approximation ratios at a controlled circuit depth.",
      "outcome": "Best mean ratio 0.7263; best sample ratio 0.8578; usage 57s.",
      "learning": "Depth improves mean quality through p=6, then saturates/declines; isolated best samples are noisier than replicated means.",
      "job_id": "d9gkj98gk0ls73f1mspg",
      "quantum_seconds": 57,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_extended_depth.json"
    },
    {
      "id": "E10",
      "execution": "IBM hardware",
      "input": "p=5 QAOA; 50 transferred/jittered parameter schedules; 4,096 shots each; 1670 two-qubit gates; zero SWAPs.",
      "inference": "Measure the mean and best-sample approximation ratios at a controlled circuit depth.",
      "outcome": "Best mean ratio 0.7357; best sample ratio 0.8925; usage 58s.",
      "learning": "Depth improves mean quality through p=6, then saturates/declines; isolated best samples are noisier than replicated means.",
      "job_id": "d9gkle3sbqfc73eop9tg",
      "quantum_seconds": 58,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_extended_depth.json"
    },
    {
      "id": "E11",
      "execution": "IBM hardware",
      "input": "p=6 QAOA; 50 transferred/jittered parameter schedules; 4,096 shots each; 2004 two-qubit gates; zero SWAPs.",
      "inference": "Measure the mean and best-sample approximation ratios at a controlled circuit depth.",
      "outcome": "Best mean ratio 0.7390; best sample ratio 0.8775; usage 58s.",
      "learning": "Depth improves mean quality through p=6, then saturates/declines; isolated best samples are noisier than replicated means.",
      "job_id": "d9gknv4honhs73abouig",
      "quantum_seconds": 58,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_extended_depth.json"
    },
    {
      "id": "E12",
      "execution": "IBM hardware",
      "input": "p=7 QAOA; 50 transferred/jittered parameter schedules; 4,096 shots each; 2338 two-qubit gates; zero SWAPs.",
      "inference": "Measure the mean and best-sample approximation ratios at a controlled circuit depth.",
      "outcome": "Best mean ratio 0.7362; best sample ratio 0.8647; usage 58s.",
      "learning": "Depth improves mean quality through p=6, then saturates/declines; isolated best samples are noisier than replicated means.",
      "job_id": "d9gkq3ogk0ls73f1n5tg",
      "quantum_seconds": 58,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_final_depth.json"
    },
    {
      "id": "E13",
      "execution": "IBM hardware",
      "input": "p=8 QAOA; 50 transferred/jittered parameter schedules; 4,096 shots each; 2672 two-qubit gates; zero SWAPs.",
      "inference": "Measure the mean and best-sample approximation ratios at a controlled circuit depth.",
      "outcome": "Best mean ratio 0.7354; best sample ratio 0.8798; usage 58s.",
      "learning": "Depth improves mean quality through p=6, then saturates/declines; isolated best samples are noisier than replicated means.",
      "job_id": "d9gkrnjsbqfc73eopi3g",
      "quantum_seconds": 58,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_final_depth.json"
    },
    {
      "id": "E14",
      "execution": "IBM hardware",
      "input": "Fixed best p=1 parameters; No mitigation; 10 replicates of 8,192 shots.",
      "inference": "Estimate replicate mean, variance and best-sample quality under one isolated mitigation mode.",
      "outcome": "Mean ratio 0.6733; best sample 0.8474; usage 24s.",
      "learning": "DD-only slightly helped; twirling slightly hurt; the combined stack strongly hurt, so mitigation interactions cannot be assumed additive.",
      "job_id": "d9gke4bsbqfc73eoovq0",
      "quantum_seconds": 24,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_depth_and_mitigation.json"
    },
    {
      "id": "E15",
      "execution": "IBM hardware",
      "input": "Fixed best p=1 parameters; XpXm dynamical decoupling only; 10 replicates of 8,192 shots.",
      "inference": "Estimate replicate mean, variance and best-sample quality under one isolated mitigation mode.",
      "outcome": "Mean ratio 0.6792; best sample 0.8520; usage 24s.",
      "learning": "DD-only slightly helped; twirling slightly hurt; the combined stack strongly hurt, so mitigation interactions cannot be assumed additive.",
      "job_id": "d9gkekggk0ls73f1mlsg",
      "quantum_seconds": 24,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_depth_and_mitigation.json"
    },
    {
      "id": "E16",
      "execution": "IBM hardware",
      "input": "Fixed best p=1 parameters; Gate and measurement twirling only; 10 replicates of 8,192 shots.",
      "inference": "Estimate replicate mean, variance and best-sample quality under one isolated mitigation mode.",
      "outcome": "Mean ratio 0.6653; best sample 0.8231; usage 25s.",
      "learning": "DD-only slightly helped; twirling slightly hurt; the combined stack strongly hurt, so mitigation interactions cannot be assumed additive.",
      "job_id": "d9gkf4t0k0jc738gt5hg",
      "quantum_seconds": 25,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_depth_and_mitigation.json"
    },
    {
      "id": "E17",
      "execution": "IBM hardware",
      "input": "Fixed best p=1 parameters; XpXm DD plus gate/measurement twirling; 10 replicates of 8,192 shots.",
      "inference": "Estimate replicate mean, variance and best-sample quality under one isolated mitigation mode.",
      "outcome": "Mean ratio 0.5557; best sample 0.7549; usage 25s.",
      "learning": "DD-only slightly helped; twirling slightly hurt; the combined stack strongly hurt, so mitigation interactions cannot be assumed additive.",
      "job_id": "d9gkg04honhs73aboj8g",
      "quantum_seconds": 25,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_depth_and_mitigation.json"
    },
    {
      "id": "E18",
      "execution": "IBM hardware",
      "input": "Best p=5 and p=6 schedules; 22 independent PUBs each; 4,096 shots per PUB.",
      "inference": "Estimate high-stat replicate means, standard errors and extreme sample quality head-to-head.",
      "outcome": "p5 mean 0.73663; p6 mean 0.74227; strongest p6 sample 0.91561.",
      "learning": "The replicated result confirms p=6 as the mean-quality winner and raises the strongest observed sample to 91.56% of exact.",
      "job_id": "d9gl69t0k0jc738gu9mg",
      "quantum_seconds": 51,
      "status": "COMPLETED",
      "evidence": "outputs/ising150_quota_finale.json"
    }
  ],
  "totals": {
    "documented_experiments": 19,
    "successful_hardware_jobs": 15,
    "quantum_seconds": 599,
    "allowance_seconds": 600,
    "remaining_seconds": 1
  },
  "failed_workloads": [
    {
      "job_id": "d9glaishonhs73abprjg",
      "status": "ERROR",
      "usage": 0,
      "reason": "IBM error 1305: one-second max_execution_time was too small; no result and no billed usage."
    },
    {
      "job_id": "d9glbkshonhs73abpt5g",
      "status": "CANCELLED",
      "usage": 0,
      "reason": "150-qubit 128-shot control remained account-queued with one second left; cancelled unbilled."
    },
    {
      "job_id": "d9gli80gk0ls73f1oae0",
      "status": "CANCELLED",
      "usage": 0,
      "reason": "One-qubit 128-shot control on ibm_fez remained account-queued; cancelled unbilled."
    },
    {
      "job_id": "d9glklggk0ls73f1odu0",
      "status": "CANCELLED",
      "usage": 0,
      "reason": "One-qubit 128-shot control on ibm_kingston also remained account-queued; cancelled unbilled."
    }
  ],
  "claim_boundary": {
    "hardware_execution": "verified",
    "exact_classical_baseline": "verified",
    "quantum_acceleration": "not measured",
    "quantum_advantage": "not claimed"
  }
}