This repository collects a set of examples which can be used to compare different numerical quantum optics frameworks. The aim is to create implementations for the following frameworks:

• Quantum Optics Toolbox (Matlab)
• QuTiP (Python)
• QuantumOptics.jl (Julia)
• C++QED (No example implemented at the moment)

To reduce noise use dedicated cpu core for the benchmarks. This can be done with cset:

sudo cset shield -k on -c 0
sudo cset shield --user=sebastian --group=users -e bash

Especially for julia, one still has to set the users home directory:

HOME=/home/sebastian

Now one can either manually run benchmarks of interest by simply executing the benchmark file or alternatively use the runall.py script to run them all automatically.

After the benchmarks have been performed simply run:

julia make.jl

Every single benchmark file has more or less the same structure. A setup function that is used to create objects that is needed to perform the actual benchmark. The execution time of this code is not measured. The benchmark function which is called repeatedly with the previously calculated objects. And code needed to configure and perform the benchmark and check that the output is correct. Depending on each example, the time is measured that it takes to evaluate a function a certain number of times. This process is repeated a few times and the minimal time is used as benchmark time.

• benchmarks-{framework}: where the benchmark files are.
• results: The results of the benchmarking is stored here as json files.
• checks: The output generated from QuantumOptics.jl is stored here and later on compared to QuTiP's output to make sure that the examples calculate the same things. At the moment the toolbox results are not checked.
• results-collected: All benchmarking results for each example are stored together in one json file.
• sourcecode: The source code of the different implementations of all examples is extracted and stripped from all boilerplate code. This makes it easy to present on the website what exactly was tested.

• runall.py: Benchmarks can be performed manually by executing the corresponding benchmark file or run automatically with the help of this script.
• collect_results.py: Collects the benchmarking results from the results directory, collects all benchmarks belonging to the same example into one file and writes the output as json into the results-collected directory.
• extract_code.py: Extracts the important benchmark code from all implementations and stores them in the sourcecode folder. Each file is executed to make sure that it really works.
• hardware_specs.py: Collects information about hardware and used software and stores it in the results directory.
• plot_results-py: Uses matplotlib to visualize the benchmark results stored in results-collected.
• make.jl: Runs collect_results.py, extract_code.py, hardware_specs.py and copies all files of interest into the correct website directories in ../QuantumOptics.jl-website.