L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Productivité · SKILL.md

transformers-and-compilation

transformers-and-compilation

Use Cirq transformers, target gatesets, and routing workflows to compile circuits to gate and topology constraints.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: transformers-and-compilation description: "Use Cirq transformers, target gatesets, and routing workflows to compile circuits to gate and topology constraints." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Cirq transformers and compilation

Use this sub-skill when a task needs Cirq circuit transformations rather than raw circuit construction, simulation, provider submission, or algorithm design.

Use this when

  • Applying or composing @cirq.transformer functions/classes.
  • Configuring cirq.TransformerContext, transformer logging, ignored tags, or deep CircuitOperation handling.
  • Cleaning or rewriting circuits with built-in transformers such as drop_empty_moments, merge_single_qubit_gates_to_phxz, eject_z, expand_composite, or optimize_for_target_gateset.
  • Compiling to cirq.CompilationTargetGateset implementations such as cirq.CZTargetGateset, cirq.SqrtIswapTargetGateset, or offline cirq_google.SycamoreTargetGateset.
  • Routing circuits with cirq.RouteCQC, cirq.LineInitialMapper, hard-coded initial mappings, named topologies, or physical device graphs.

Route elsewhere

  • Circuit construction, qubits, gates, measurements, custom gates, or JSON/QASM basics: core-circuits-and-ops.
  • Running local simulators, sweeps, noise, histograms, or performance studies: simulation-study-and-noise.
  • Provider credentials, cloud jobs, samplers, serializers, or device submission: hardware-providers-and-serialization.
  • Algorithm-level motivation and observable expectation workflows: algorithms-and-observables.

Reference map

  • Start with API reference for signatures, target gatesets, and routing objects.
  • Use Transformer workflows for pass ordering, custom transformers, no-compile tags, and deep subcircuits.
  • Use Routing and targets for device graphs, RouteCQC, named topologies, placements, and provider-gateset cross-links.
  • Use Troubleshooting when transformed circuits still contain unsupported gates, tags are not honored, routing fails, or moment structure changes unexpectedly.

Bundled safe helper

Run the deterministic helper when you need a quick offline sanity check of the installed Cirq transformer stack:

python scripts/inspect_transformer_pipeline.py --help
python scripts/inspect_transformer_pipeline.py --target cz
python scripts/inspect_transformer_pipeline.py --target sycamore

The helper builds a tiny local circuit, applies a short transformer pipeline, compiles to a target gateset, and performs a local unitary equivalence check. It never contacts provider services.

Operating guardrails

  • Treat compilation as a pipeline: choose target constraints first, order passes deliberately, and validate after each major boundary when possible.
  • Prefer ignore_failures=False while debugging target-gateset conversion so unsupported operations do not remain silently.
  • Use TransformerContext(tags_to_ignore=...) for protected/no-compile operations and TransformerContext(deep=True) only when nested CircuitOperation bodies must be transformed.
  • Route topology first, then compile routed gates to the target gateset required by the physical device or provider workflow.
  • For live hardware submission or credentialed provider validation, stop here and route to hardware-providers-and-serialization after offline compilation checks.
Skills enregistrées