suehtyp 1.2.3

Theseus, a highly-efficient inverse-design algorithm for quantum optical experiments

Theseus

Theseus, a highly-efficient inverse-design algorithm for quantum optical experiments

Installation

When published it will be possible to install via pip install. Untill then, install from source (after cloning the repository):

python setup.py install

Running Theseus

To list the included examples, type

theseus list

To run one of the included examples, type e.g.

theseus run --example ghz_346

To run your own input file, type

theseus run PATH_TO_YOUR_INPUT_FILE

Output of optimization is saved to a directory called output. Names of the subdirectorie are specified by the name and content of the config file.

To plot the graph corresponding to one result saved as a json file, execute

theseus plot PATH_TO_RESULT_FILE

To analyze a subdirectory corresponding to one run, type

theseus analyze -d outputs/ghz_346/ghz_346 

or just

theseus analyze  

then an overview of all available folders that can be selected is given. After that one can choose which run (if there exists different run-folders having different summary files) one wants to analyze. When you have decided on a state, an overview plot is created that shows the graph, the development of the loss function and various properties that can be declared via -i. With -pm a pdf can be created that shows all perfect matchings. When one wants to set all weights to plus minus one one can choose the option -one. Everthing together:

theseus analyze -d your/directory -one -pm -i 'norm' -i 'ent' -i 'k'  

norm shows the normalization of the state, ent gives information about entanglement for the different bipartitions and k gives information if there is a k-uniform state and which bipartitions are maximally entangled (=1) or separable (=0).

To get help, add the --help option to any command. For instance

> theseus run --help

Usage: theseus run [OPTIONS] FILENAME

  Run an input file.

Options:
  --example  Load input file from examples directory.
  --help     Show this message and exit.

Development

Clone repository

git clone https://github.com/artificial-scientist-lab/Theseus.git

Create virtual environment

From the project root directory, submit

python -m venv venv

This will create a subfolder with your virtual environment.

To activate, type

. venv/bin/activate

Note the leading point!

Local development installation

Submit

python setup.py develop

from the project root directory (where setup.py is located). Any changes in the code will now automatically be reflected in your local package installation.

Tests

Run test suite

Running all tests

python -m unittest discover tests

Running only the fast tests

python -m unittest discover -s tests/fast

Test coverage

Install coverage, if you have not yet done so:

pip install coverage

Then run coverage scan:

coverage run --source=theseus -m unittest discover tests 

After that, create the coverage report:

coverage report -m