The final version of this project is released on a different repository. You can access it through this link.
Presented most recent results at Connecting The Dots 2020, talk is here. Proceeding is available as a preprint here
Latest updates are presented at CERN openlab Technical Workshop 2020. Presentation is here.
CHEP 2019 proceeding submitted and available as a preprint here.
Use train.py to train a model. Models are available in ./qnetworks folder. Choose the model and other hyperparameters using a configuration file (see ./configs folder for examples).
Execute the following to train the model.
python3 train.py [PATH-TO-CONFIG-FILE]
Note: 1 epoch takes ~1 week when a GPU is used to simulate quantum circuits.
All events are divided to 8 in
First the data is encoded via a IQC layer, then a PQC is applied to the circuit. Then, the measurements are taken and expectation values are calculated by taking averages of them.
Notice that this is a project in progress. Latest results are always updated and might be different from the proceeding.
The repository has many scripts which are not complete! Work in Progress!