https://github.com/krastanov/qevo

Optimization algorithm for the creation of quantum entanglement purification (distillation) circuits.
https://github.com/krastanov/qevo

entanglement genetic-algorithm optimization quantum-circuit quantum-computing

Last synced: 3 months ago
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Optimization algorithm for the creation of quantum entanglement purification (distillation) circuits.

• Host: GitHub
• URL: https://github.com/krastanov/qevo
• Owner: Krastanov
• License: gpl-3.0
• Created: 2017-12-28T06:47:12.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2020-05-31T21:02:50.000Z (over 4 years ago)
• Last Synced: 2023-10-20T21:03:41.627Z (about 1 year ago)
• Topics: entanglement, genetic-algorithm, optimization, quantum-circuit, quantum-computing
• Language: Python
• Homepage: https://qevo.krastanov.org
• Size: 47.2 MB
• Stars: 8
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
Optimized Quantum Entanglement

`qevo.py` provides a small python library for the creation and optimization of

quantum entanglement purification circuits.

`Clifford.jl` is a higly-optimized julia library for enumerating and studying

the Clifford group of multiple qubits.

`examples` contains multiple notebooks showcasing the use of these libraries.

Some of these files were used in the writing of the related paper.

- `Example` shows how to run a simple optimization for the creation of

  purification circuits.

- `Compare_Regimes` shows that for different parameter regimes (i.e. error

  models) different circuits are better.

- `HotCold` shows how to augment the library to work with custom error models

  and hardware architectures. In this case we optimize for a register that has

  only one "hot" qubit (a communication qubit capable of establishing initial remote

  entanglement).

- `OptimizeHashingYield` shows how to optimize for the hashing yield (defined

  only for perfect local operations). It is of great theoretical interest in

  the study of assymptotic circuits, but it is less useful in our case of small

  circuits optimized for operational errors.

- `Structure_ParallelNaiveCoarseDividing` and `julia-subgroup` are used to

  enumerate and study the group structure of the Clifford/Permutation

  operations used in the purification circuits.

See [qevo.krastanov.org](https://qevo.krastanov.org) for visualizations and

comparisons of circuits generated by this software.