qbalance documentation

qbalance is a workflow toolkit for balancing quantum compilation, noise-suppression, and error-mitigation strategy choices over datasets of Qiskit circuits.

Documentation map

• Getting started: installation, a minimal Python workflow, and the equivalent CLI flow.

• Strategy configuration: StrategySpec fields, validation rules, default candidates, and JSON strategy files.

• CLI guide: command-by-command reference for dataset, adjust, matrix, report, plugins, and compile.

• Artifacts and reports: dataset layouts, balanced workload outputs, matrix JSON, and report generation.

• API reference: public Python API, lower-level modules, extension points, and validation behavior.

User guide

• Getting started
  • Install
  • Python quickstart
  • CLI quickstart
  • Use a custom strategy file
• Strategy configuration
  • Fields
  • Default candidate generation
  • Explicit strategy sets
  • Strategy JSON formats
• CLI guide
  • dataset
  • adjust
  • matrix
  • report
  • plugins
  • compile
• Artifacts and reports
  • Dataset layout
  • Balanced workload output
  • Matrix JSON
  • Reports
• API reference
  • Package root: qbalance
  • Strategies: qbalance.strategies
  • Workflow: qbalance.workflow.workload
  • Benchmarking: qbalance.benchmarking
  • Search: qbalance.search
  • Transpilation: qbalance.transpile
  • Execution and mitigation
  • Backend plugins
  • Reports

Core flow

CircuitDataset
  -> Workload.from_dataset(...) or Workload.from_path(...)
  -> set_target("fake:generic:5" | "aer:..." | custom plugin)
  -> adjust(...)
  -> BalancedWorkload.save(...) or BalancedWorkload.to_download(...)
  -> load_balanced_workload(...) for saved-directory reloads

For fixed cross-product experiments, use qbalance.benchmarking.run_matrix(...) or the qbalance matrix CLI command.