Collections of tools for quantum metasurface analysis using Python3.
To get started, download the latest Git, VSCode, and Docker (Optional).
Install VSCode extension Remote - Containers and verify the docker service is running.
git clone https://github.com/rstanuwijaya/pf32-python-analysis
code .
To install the dependencies locally, you can either use Miniconda to provide dependencies encapsulation or just install the dependencies directly by using pip.
pip install --user -r requirements.txt # Directly install the dependencies
If you are setting up for the first time, you can install the dependencies inside a virtual environement by using the following commands
python -m venv env # Create an virtual environment
source env/bin/activate # To activate the virtual environment
pip install --user -r requirements.txt # Install the dependencies inside the virtual environement
The container has its own local filesystem, thus the data must be mounted to the container. Modify the .devcontainer/devcontainer.json "mount" properties to mount required directory to the container.
Open command pallete by pressing F1 in VSCode and run Remote-Containers: Build Container to build the container. The VSCode will restart shortly and run in the dev container.
The notebooks can be used directly from the notebooks folder to reproduce the analysis.
To contribute, feel free to fork the project and open a pull request on Github. Contributions are greatly appreciated.
- Computational simulation for single-pixel ghost imaging. Live Demo
- Metasurface image processing tool to capture metasurface lattice constants.
- Iterative fitting model for coincidence count using LMFIT library.
- Vectorized coincidence count analysis tool for data produced by PF32.
Special thanks to the Professor Jensen and the group members of JensenLab @ HKUST.