{
  "ok": true,
  "mode": "CIRQ_QML_ENGINE_INTAKE",
  "build": "Live Build 1: Lane Building 1",
  "purpose": "Intake and classify uploaded QML engines as governed Cirq/QML extension candidates.",
  "boundary": {
    "aura": "Aura115™ / Jupiter 9 is the orchestrator.",
    "cirq": "Cirq is an inhabited extension target.",
    "qutip": "QuTiP is a Python quantum simulation runtime target.",
    "uploadedEngine": "The uploaded engine is a staged runtime candidate, not Aura itself."
  },
  "defaultEngine": {
    "id": "cirq-qml-intake-1783736684479",
    "uploadedFilename": "quantum machine learning(1).py",
    "normalizedName": "quantum_machine_learning1.py",
    "canonicalName": "lgh_qsvm_swarm_engine",
    "canonicalPlacement": "Aura115_CURRENT/cirq/engines/lgh_qsvm_swarm_engine.py",
    "manifestPlacement": "Aura115_CURRENT/cirq/manifests/lgh_qsvm_swarm_engine_manifest.json",
    "intakeStatus": "accepted_as_staged_runtime_candidate",
    "lane": "qml-engine",
    "allowedPlacementLanes": [
      "quantum-extension",
      "cirq-extension",
      "qml-engine",
      "lgh-governance",
      "qsvm-swarm",
      "fisher-rao-optimization",
      "bus-300-map",
      "structural-memory",
      "receipt-ledger"
    ],
    "planets": {
      "orchestrator": "Jupiter",
      "quantumObserver": "Neptune",
      "authority": "Sol",
      "memory": "Pluto",
      "transport": "Mercury"
    },
    "callable": false,
    "executable": true,
    "executableWhere": "external_python_runtime",
    "executableInsideVercelNodeRoute": false,
    "writable": false,
    "sourceContextOnly": false,
    "runtimeCandidate": true,
    "cirqNative": false,
    "cirqCompatibility": "adapter_required",
    "qutipRuntime": "primary_runtime_candidate",
    "authority": {
      "readAsSourceContext": "open",
      "repoPlacement": "operator_loop_or_auau_required",
      "runtimeExecution": "external_python_runtime_required",
      "hardwareExecution": "not_enabled",
      "writeBackReceipts": "AUAU_REQUIRED"
    },
    "dependencies": {
      "confirmedOrExpectedFromUploadedEngine": [
        "qutip",
        "numpy",
        "scipy",
        "matplotlib",
        "scikit-learn"
      ],
      "cirq": {
        "requiredForCurrentUploadedEngine": false,
        "status": "adapter_target",
        "reason": "The uploaded engine is treated first as a preserved QuTiP/QML runtime candidate. Cirq-native files should be generated as adapters or equivalent artifacts, not claimed as already converted."
      },
      "installCommandForQuTiPRuntime": "python -m pip install qutip numpy scipy matplotlib scikit-learn",
      "installCommandForFutureCirqRuntime": "python -m pip install cirq"
    },
    "governanceComponents": {
      "lgh": {
        "present": true,
        "components": [
          "horizon_pressure",
          "guarded_margin",
          "rescue_window",
          "authority",
          "coherence",
          "shared_obligation"
        ]
      },
      "fisherIntelligenceBound": {
        "present": true,
        "components": [
          "fisher_information_metric_orientation",
          "fisher_rao_or_natural_gradient_orientation",
          "capacity_bound_orientation",
          "viability_constrained_learning_orientation"
        ]
      },
      "multiAgentBus": {
        "present": true,
        "components": [
          "ten_agent_swarm_claim",
          "qsvm_style_classification",
          "bus_300_trajectory_visualization",
          "shared_obligation_pool"
        ]
      }
    },
    "sourceContext": [
      {
        "id": "qml_complex_systems_pdf",
        "title": "Quantum_machine_learning_for_complex_sys.pdf",
        "role": "QML paradigms, trainability, quantum kernels, neural-network quantum states, Q-VMC, federated QML"
      },
      {
        "id": "universal_optimization_engine",
        "title": "Patent_Universal_Optimization_Engine.docx",
        "role": "governed runtime as universal constrained optimization engine across classical, quantum, financial, signal, and autonomous workloads"
      },
      {
        "id": "lopez_governance_horizon",
        "title": "Paper34_LGH_Lopez_2026.docx",
        "role": "LGH, spectral instability geometry, rescue windows, quantum horizon extension, scale-invariant collapse geometry"
      },
      {
        "id": "lopez_intelligence_bound",
        "title": "Patent_Lopez_Intelligence_Bound.docx",
        "role": "Fisher information geometry, intelligence statistical manifold, viability-constrained natural gradient flows"
      }
    ],
    "placementPlan": [
      {
        "order": 1,
        "action": "preserve_uploaded_engine_exactly",
        "path": "Aura115_CURRENT/cirq/engines/lgh_qsvm_swarm_engine.py",
        "note": "Place the uploaded Python engine content exactly first. Do not convert before preserving."
      },
      {
        "order": 2,
        "action": "install_manifest",
        "path": "Aura115_CURRENT/cirq/manifests/lgh_qsvm_swarm_engine_manifest.json",
        "note": "Use manifest to bind the engine into Aura115™ structural memory."
      },
      {
        "order": 3,
        "action": "install_intake_adapter",
        "path": "api/cirq-qml-engine-intake.js",
        "note": "Expose safe intake classification route. No execution."
      },
      {
        "order": 4,
        "action": "generate_cirq_adapter_next",
        "path": "Aura115_CURRENT/cirq/examples/lgh_qsvm_cirq_adapter_template.py",
        "note": "Create Cirq-compatible template after original engine is preserved."
      }
    ],
    "adapterPlan": [
      "Preserve original QuTiP engine unchanged.",
      "Create manifest and source-context bindings.",
      "Generate Cirq-compatible circuit templates without claiming full conversion.",
      "Create runtime receipt format for any external Python execution.",
      "Only after receipts, add execution bridge planning."
    ],
    "nextFilesToBuild": [
      "Aura115_CURRENT/cirq/engines/lgh_qsvm_swarm_engine.py",
      "Aura115_CURRENT/cirq/manifests/lgh_qsvm_swarm_engine_manifest.json",
      "Aura115_CURRENT/cirq/examples/lgh_qsvm_cirq_adapter_template.py",
      "Aura115_CURRENT/cirq/receipts/LGH_QSVM_RUNTIME_RECEIPT_TEMPLATE.md",
      "api/cirq-qml-runtime-simulation.js",
      "api/cirq-artifact-builder.js"
    ]
  },
  "rules": [
    "Do not execute Python from this Vercel Node route.",
    "Do not claim runtime success without external execution receipt.",
    "Do not claim Cirq conversion until Cirq-compatible artifacts exist.",
    "Do not claim quantum hardware execution without provider receipt.",
    "Do not overwrite the original uploaded engine before preserving it.",
    "Repository writes require operator loop or AUAU™ root execution."
  ],
  "timestamp": "2026-07-11T02:24:44.480Z"
}