User guide

PyQBench can be used in two different ways:

• As a library. This is a more extensible, but also more laborious way of using PyQBench. Most importantly, this way allows for more advanced scripting defining your own measurements scheme.

• As a CLI tool. This mode of operation trades extensibility for simplicity of usage, as it allows only for running Fourier-discrimination experiments defined with simple YAML input files.

Refer to the guides below for in-depth walkthroughs.

• Usage as a library
  • Setting the stage
  • What do we need?
  • Our toy model
  • Decomposing circuit components into gates
  • Defining needed instructions using Qiskit
  • Running simulations in the simplest scenario
  • Gaining more control over the benchmarking process
    • Assembling circuits
    • Running the circuits
    • Computing probabilities
• Usage as a CLI tool
  • Overview of CLI workflow
  • Defining the experiment
  • Defining the backend
    • IBMQ backends
  • Backends obtainable from simple providers
  • Backends constructed from a simple function call
  • Notes on using the asynchronous flag
  • Running the experiment and collecting measurements data
    • Starting the experiment
    • (Optional) Getting status of asynchronous jobs
    • Resolving asynchronous jobs
  • Computing probabilities