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Hybrid execution & backend adapters

How one passport moves between CPU simulation, GPU simulation and quantum hardware, and which adapters exist today.

PublishedUpdated 2026-10-14

QAISS keeps every provider behind an adapter. The Lab produces a Workload Passport; any adapter can run it and emit a new passport. Results then fall into two classes. Simulators that follow the sampling contract are checked bit-for-bit. Anything sampled by a provider's own service, including every quantum processor, can only be checked statistically.

Three execution classes

ClassWhat actually runsResult checkToday
Classical CPU simulationExact state vector or tensor network on an ordinary processorBit-for-bitBrowser, QAISS connector, Origin pyqpanda3 CPUQVM
GPU-accelerated classical simulationThe same mathematics on an NVIDIA GPU (cuStateVec, cuTensorNet). Faster, still classicalBit-for-bit (to fp64 rounding)Adapters written; never executed (no NVIDIA GPU)
Quantum hardwareA provider QPU, e.g. Origin Wukong, via its cloudStatistical (TVD vs the ideal distribution)Adapter written; never executed (no API key or access)

GPU simulation is never quantum hardware execution, and nothing here demonstrates quantum advantage.

Interchange formats

  • Workload Passport v0.1: the QAISS record (circuit, seed, shots, noise, backend, hashes).
  • OpenQASM 2.0: exported by the Lab and the connector (pyqpanda3 reads it with convert_qasm_string_to_qprog).
  • OriginIR: Origin Quantum's text format, exported by the Lab and the connector (convert_originir_string_to_qprog). The QPanda3 adapter loads exactly this text.
  • Bit order: QAISS count keys write qubit 0 first; pyqpanda3 keys write c[0] last. The connector reverses keys when it reads Origin results.

Platform components

ComponentPurposeWhereStatus
Circuit studioBuild or import circuits, see the diagram, Bloch spheres and phases/labLive (≤ 8 qubits × 20 steps in the visual builder)
Simulation engineExact fp64 state vector with seeded sampling/lab, connectorLive
GPU simulation backendcuStateVec / cuTensorNet adapters, code translator, memory planner/gpu, connectorUntested on GPU
Hardware execution adapterOrigin Quantum Cloud through the documented pyqpanda3.qcloud APIconnectorUntested: needs QPANDA_QCLOUD_API_KEY
Hybrid orchestratorChoose a backend per passport; same record format everywhere/lab#elsewhere, CLI --backendManual (CLI); no hosted scheduler
Results explorerHistogram vs exact, TVD, output hashes, verifier/labLive
Benchmark engineOne protocol for the browser and every connector backend (time, memory, accuracy vs reference); records compare at /benchmarks/benchmarks, CLI benchLive (browser, CPU, QPanda3); GPU runs pending
Experiment historySession history plus up to 20 saved passports; import OpenQASM / OriginIR/labLive (this browser only; no accounts or server storage)
AI assistantExplain concepts, draft circuits—Not built

Running a passport elsewhere

cd connectors/cuquantum
python -m qaiss_cuquantum run passport.json --backend qpanda3        # Origin pyqpanda3 CPUQVM
python -m qaiss_cuquantum export passport.json --format originir   # or qasm
export QPANDA_QCLOUD_API_KEY=…   # your own key; never commit it
python -m qaiss_cuquantum run passport.json --backend origin-cloud --origin-backend full_amplitude

Origin Quantum Cloud access needs your own account and API key. QAISS holds no key, runs nothing on Origin hardware and has no partnership with Origin Quantum or NVIDIA.

Release notes

Engineering updates,
not hype.

Research drafts, releases, and every change to a public claim. No price talk.

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