Quantum state tomography with conditional generative adversarial networks
This version contains the code to reproduce https://arxiv.org/abs/2008.03240 (accepted in PRL on June 10, 2021). Some parts of the figures in the paper are generated here with the implementation of the CGAN in TensorFlow. In addition, check out the implementation of accelerated-project-gradient based maximum likelihood estimation (APG-MLE) from qMLE https://arxiv.org/abs/1609.07881 to have a fast MATLAB code that reconstructs density matrices from noisy data.
Installation and use
To run the code:
- clone this directory
- cd to the current folder `cd qst-cgan`
- make a local installation with `pip install -e .` which installs the necessary libraries such as tensorflow-cpu and qutip to run the code.
- cd to the folder paper-figures `cd paper-figures` and run the notebooks
Please note that the code works only with the CPU version of TensorFlow which
can be installed specifically with:
pip install tensorflow-cpu
Please send me an email if you face any trouble running the code at "[email protected]".