Welcome to pyrauli’s documentation!

pyrauli is a high-performance Python package for quantum circuit simulation, powered by the C++ ProPauli library. It uses Pauli back-propagation to efficiently calculate the expectation values of observables.

This documentation is structured to help you succeed, whether you are learning the library for the first time or need a specific technical detail.

Tutorials

• Getting started: Your First Simulation
  • Installation
  • Simulating a Bell State
  • Next Steps

How-To Guides

• Build and Run Circuits
  • Construct a Basic Circuit
• Work with Observables
  • Manually Evolve an Observable
  • Manage Observable Complexity
• Manage Simulation Complexity
  • Remove small coefficients
  • Available truncators
  • Using a custom Truncator with your own logic
  • Controlling when truncation is applied
• Integrate with Qiskit
  • Convert Qiskit objects to pyrauli objects
  • Use pyrauli as a Qiskit-compatible backend
  • Use the PyrauliEstimator Qiskit Primitive
  • Qiskit and reverse qubit ordering
• Simulate Noisy Circuits
  • Apply Noise to a pyrauli Circuit
  • The Importance of Truncation with Noise
  • Use Noise Models with Qiskit Backends

Explanation

• Core Concepts
  • The Heisenberg Picture vs. The Schrödinger Picture
  • Pauli Back-Propagation
  • The pyrauli + ProPauli Architecture

API Reference

• API Reference
  • AlwaysAfterSplittingPolicy
  • AlwaysBeforeSplittingPolicy
  • Circuit
  • CliffordGate
  • CoefficientTruncator
  • CompressionResult
  • KeepNTruncator
  • LambdaPolicy
  • LambdaTruncator
  • MultiTruncator
  • NeverPolicy
  • NeverTruncator
  • Noise
  • NoiseModel
  • Observable
  • OperationType
  • PBackend
  • Pauli
  • PauliEnum
  • PauliGate
  • PauliTerm
  • PyrauliEstimator
  • QGate
  • SchedulingPolicy
  • SimulationState
  • Timing
  • Truncator
  • UnitalNoise
  • WeightTruncator
  • from_qiskit()

Performance

• Benchmarks

Indices and tables

• Index

• Module Index

• Search Page