Add PNA tutorial#5209
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Adapt the PNA tutorial from the QDC Challenges 2025 repo [1] into a documentation tutorial, updated for the stable Qiskit Runtime release and restructured to follow the standard tutorial template. New files: - docs/tutorials/propagated-noise-absorption.ipynb - public/docs/images/tutorials/propagated-noise-absorption/ (3 schematics + extracted cell outputs) Registered in docs/tutorials/_toc.json and docs/tutorials/index.mdx under "Error mitigation", excluded from notebook CI in scripts/config/notebook-testing.toml (consistent with other tutorials), and given an owner in qiskit_bot.yaml. Major changes from the original [1]: - API: migrated off the `executor_preview` branch to the released qiskit-ibm-runtime 0.47.0. `Executor`, `QuantumProgram`, and `NoiseLearnerV3` are now imported from the top-level package; noise-learner options are passed as a plain dict instead of importing `NoiseLearnerV3Options`. - Credentials: replaced the hardcoded `shared_service` (token + `instance` CRN) and the named `QiskitRuntimeService(name="qdc-2025")` with a plain `service = QiskitRuntimeService()` that reads saved credentials. - Live execution: removed all saved-job loading (the `shared_service.job(...)` IDs and the `load_saved_nl_result` / `load_exec_results_from_disk` branches). The noise learner and Executor now run live, and the job is tagged `TUT_PNA`. - Bug fix: the measurement basis-change input was hardcoded as `basis2`, which no longer matches the samplex interface (it expects `basis0` here). Replaced with a lookup over `samplex.inputs().get_specs(...)` so the name is discovered from the circuit's box structure rather than hardcoded. Also fixed the execution `shape` to be a real 1-tuple. - Structure: reformatted to the tutorial template (title/description frontmatter, learning outcomes, prerequisites, background, requirements, setup, next steps). The small-scale simulator section is kept but explains why simulation is skipped (PNA mitigates learned hardware noise), and the workflow is presented as the four-step large-scale hardware example. - Content: corrected the learned-noise-rates discussion, which had claimed two-qubit rates exceed one-qubit rates (the opposite of what the plot shows); rewrote it to be device-dependent.
Make the tutorial runnable on any backend instead of being tied to a hardcoded ibm_kingston chain. - Add a `find_qubit_chain` helper (defined in the Setup section) that walks the backend's coupling map and greedily builds a connected, low-error line of `num_qubits`. This replaces the hardcoded 30-qubit layout. Transpilation stays at optimization_level=0 with the chain pinned as `initial_layout`, so the mirrored two-qubit-gate layer structure that the boxing and noise-learning steps depend on is preserved exactly. - Select the backend dynamically with `service.least_busy(...)` rather than pinning ibm_kingston. - Make the learned-noise-rates commentary backend-agnostic; it no longer names a specific device. - Regenerate the extracted output figures from a fresh hardware run.
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Summary
Adds a new tutorial, "Improving expectation values with propagated noise absorption (PNA)." It is an updated, documentation-ready version of the PNA tutorial from the QDC Challenges 2025 repo: https://github.com/qiskit-community/qdc-challenges-2025/blob/main/day3_tutorials/Track_A/pna/propagated_noise_absorption.ipynb
PNA mitigates two-qubit gate noise by propagating the inverse of learned noise channels into the measured observable (using
samplomatic,NoiseLearnerV3, andqiskit-addon-pna), then sampling the randomized circuits with the newQuantumProgram/Executorclasses in Qiskit Runtime. The tutorial walks through the full four-step Qiskit pattern on a 30-site mirrored kicked-Ising circuit and compares PNA against PNA+TREX, PNA+PS, and PNA+PS+TREX.Major changes from the original
executor_previewbranch.Executor,QuantumProgram, andNoiseLearnerV3are now imported from the top-levelqiskit_ibm_runtime; noise-learner options are passed as a plain dict (noNoiseLearnerV3Optionsimport).shared_service(token +instanceCRN) and the namedQiskitRuntimeService(name="qdc-2025")with a plainQiskitRuntimeService()that reads saved credentials.shared_service.job(...)IDs andload_saved_*branches); the noise learner andExecutornow execute live, with the job taggedTUT_PNA.ibm_kingstonchain with afind_qubit_chainhelper that builds a connected, low-error line from the backend's coupling map, and selects the backend withleast_busy. Transpilation stays atoptimization_level=0with the chain pinned asinitial_layout, preserving the mirrored two-qubit-gate layer structure that boxing and noise learning rely on.basis2, which no longer matches the samplex interface; it now looks up the name fromsamplex.inputs().get_specs(...).Files
docs/tutorials/propagated-noise-absorption.ipynb+ images underpublic/docs/images/tutorials/propagated-noise-absorption/(3 schematics and the extracted cell outputs).docs/tutorials/_toc.jsonanddocs/tutorials/index.mdx(Error mitigation section), added to the notebook-CI exclude list inscripts/config/notebook-testing.toml, and given an owner inqiskit_bot.yaml.Testing
Ran on IBM Quantum hardware,
tox -e lint, the notebook normalizer, spelling, and internal-link checks all pass.