Installation instructions

The package is currently developed and maintained only for Linux. It can either be executed on the native OS of the user, if SageMath is installed, or within a Docker container, as detailed below.

Installation with Docker

1. If Docker is not installed, follow the instructions at https://docs.docker.com/install/ (choose the server installation instructions corresponding to your distribution) and https://docs.docker.com/engine/installation/linux/linux-postinstall/ to install Docker and run Docker commands without using sudo.

2. Build the Docker image (all Docker commands are encapsulated in Makefile entries):

    make docker-build
   

   Warnings: The Docker image is a large file, its construction can be very long. A network connection is required. If you already have a Docker image with this name, either remove it or change the image name in Makefile.

3. At this point, you have several choices, you can either run the scripts that generated the results in the article [BJH+19], or open an interactive session to try out the tools from the module mermin_eval.

   • If you want to run the scripts, you can simply use:

     make grover or make qft.

   • If you want to open an interactive session, use:

     make interactive
     

     This will start a container and a SageMath interactive session. See in the Execution section how to run the tools.

4. Finally, to quit the container:

   exit a first time will close the SageMath interactive session and exit a second time will quit the container.

Successfully tested in October 2018 under Linux Ubuntu 16.04, with Docker
18.03.1-ce.

Direct Installation

To install Sagemath without going through docker, please follow the instructions from SageMath installation page.

Execution instructions

Once the installation over, you can enter a SageMath interactive session using the command sage in your terminal.

Once in the sage session (either in the Docker container or directly on your computer), you can import the modules, as in the following example. From this point, you need some basic knowledges on Python since SageMath is built on Python 2.7.

For specific function uses, see the documentation provided in pdf format or as a more complete website.

Example of usage:

You can run the Grover’s algorithm as well as the Mermin evaluation process with the following commands once in the sage environment:

>>> from mermin_eval.grover import *
>>> v = target_state_ket_string_to_vector("0000")
>>> grover(v)
[0.0963683533242808,1.21302328780365,0.909118107915599,-0.530436080194821]