This is official repository for the paper "Deep learning-based variational autoencoder for classification of quantum and classical states of light" by Mahesh Bhupati, Abhishek Mall, Anshuman Kumar, and Pankaj K. Jha Paper
- Clone the repository
- Install the required packages using the following command:
pip install -r requirements.txt- Run the following command to train the model:
cd src
./train.sh # To train the model for SPAC & SPAT dataset
./train_spac_spat_coherent_thermal.sh # To train the model for mixSPAC, mixSPAT coherent and thermal states
./train_moe_spac_spat_coherent_thermal.sh # To train the model for mixSPAC, mixSPAT coherent and thermal states using Mixture of Experts an upgraded model which performes better in some cases (not included in the paper)- Run the following command to generate tentative plots of the paper:
cd src
python fig_4.py # To generate the plot for Fig. 4
python fig_5.py # To generate the plot for Fig. 5
python fig_6.py # To generate the plot for Fig. 6
python fig_7.py # To generate the plot for Fig. 7If you find this code useful in your research, please consider citing the paper:
@misc{bhupati2024deep,
title={Deep learning-based variational autoencoder for classification of quantum and classical states of light},
author={Mahesh Bhupati and Abhishek Mall and Anshuman Kumar and Pankaj K. Jha},
year={2024},
eprint={2405.05243},
archivePrefix={arXiv},
primaryClass={quant-ph}
}
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