Python tools and demos for inferring quantum network topology.
QNetTI extends PennyLane and the Quantum Network Variational Optimizer (QNetVO) with variational quantum network inference functionality. The goal of which is to determine the entanglement/correlation structure of source nodes in a quantum network using variational quantum optimization of local measurements. Our methods are compatible with both quantum hardware and simulations thereof.
See our preprint titled "Inferring Quantum Network Topology using Local Measurements" for details https://arxiv.org/abs/2212.07987.
Please review the documentation for details regarding this project.
Install qNetTI:
$ pip install qnetti
Install PennyLane:
$ pip install pennylane==0.29.1
Install QNetVO:
$ pip install qnetvo==0.4.2
Import packages:
import pennylane as qml
import qnetvo
import qnetti
Note
For optimal use, QNetTI should be used with the compatible versions of PennyLane and QNetVO. Version compatiblity may change in a future release of QNetTI
./src/qnetti- Application code../test- Unit tests for application code../script- Scripts for numerical experiments, data collection, and plotting../data- Stored data from numerical experiments../demos- User oriented notebooks demoing the application of our code../docs- Source code for generating the static documentation pages.
We welcome outside contributions to qNetTI. Please see the Contributing page for details and a development guide.
See CITATION.bib for a BibTex reference to qNetVO.
QNetTI is free and open-source. The software is released under the Apache License, Version 2.0. See LICENSE for details.
This material is based upon work supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, and the Office of Advanced Scientific Computing Research, Accelerated Research for Quantum Computing program under contract number DE-AC02-06CH11357.