This repository contains scripts, notebooks and data for the paper Quantum Optimal Control via Semi-Automatic Differentiation.
The methods described in the paper are implemented are implemented in GRAPE.jl and Krotov.jl, which are part of the JuliaQuantumControl framework.
This repository assumes a Linux system with a basic development environment. The make command must be available.
You should have the following installed before initializing this project
- Jupyter notebook
- Jupytext extension
- Julia 1.7 (old releases)
- DrWatson
- Revise
- IJulia
We recommend Miniforge to install Jupyter.
The Julia packages listed above should be installed in your base Julia environment. If they are not installed already, initializing the project will install them.
To work with this project, navigate to the project folder and run
make venv
The project is driven by the Makefile. Run make help to see all possible commands.
The notebooks in the notebooks subfolder are stored in .jl format via jupytext. In order to run the notebooks, you must have a Jupyter server installed independently, with the jupytext extension. Assuming you have the IJulia kernel installed globally, the notebook will automatically run within the correct project environment. Simply start the server with e.g.
make jupyter-notebook
From within the project folder, run
make plots
This will produce pdf files in the subfolder ./data/plots. This includes the file combined_benchmarks.pdf, which is Figure 2 in the paper.
Alternatively, run the jupyter server (make jupyter-notebook) and open and run the ./notebooks/Plots.py notebook.
The benchmark data is included in the notebook. To re-run the benchmarks, delete all files in the ./data/benchmarks folder. Then, run,
make semiad_sysimage.so benchmarks
This will take several days, possibly several weeks on smaller systems, and use all available cores. No other processes requiring significant CPU resources should be running, as this will skew the benchmarks.
Running
make distclean
removes all generated files and uninstalls the Jupyter project kernel from the user's global Jupyter installation.