Documentation

mdopt is a Python package for discrete optimisation in the tensor-network language (MPS/MPO/DMRG). It targets problems such as quantum error-correction decoding with a code-agnostic workflow and is intended to be easily extensible to other applications.

For installation and a minimal working example, see Getting started. For a curated overview of notebooks, see Examples.

Getting started

• Getting started
  • Installation
  • Minimal example
  • Decoding a detector error model
  • Workflow at a glance
  • Platforms

Examples

• Examples
  • Decoding classical LDPC codes
  • Decoding 3-qubit repetition code
  • Decoding 5-qubit perfect code
  • Decoding Shor’s 9-qubit code
  • Decoding surface code
  • Ground state search for 1D quantum Ising model
  • Random quantum circuit simulation
  • Main component problem
  • MPS-MPO contraction schedule optimisation
  • GPU Backend Example
  • Campaign scripts

Testing & validation

• Testing
  • Tips

Contributing

• Contributing
  • Code of conduct

API reference

• API reference
  • Entry points
• mdopt
  • mdopt package

Project overview & references

• Project overview & references
  • Motivation
  • Intended users
  • References & related resources
• README
  • Installation
  • Minimal example
  • Decoding circuit-level noise from a detector error model
  • Package layout
  • Examples
  • Cite
  • Contribution guidelines
  • License
  • Documentation

Indices and tables

• Index

• Module Index

• Search Page