Installation Guide

To obtain the library, clone the repository to your local machine by executing the following command in your terminal:

Clone the repository to your local machine by running the following command in your terminal:

git clone https://github.com/erdemeray/IR_for_CVQKD.git

or

git clone git@github.com:erdemeray/IR_for_CVQKD.git

There are multiple methods to utilize the library, depending on the programming language you intend to use. The installation steps may vary accordingly.

• If you plan to use the library in C++, you can compile it using CMake and integrate it into your C++ projects. Ensure that CMake and a C++ compiler are installed on your system. Python is not required for using the library in C++.

• If you plan to use the library in Python and MATLAB, configure your system so that CMake can locate the Python installation. The recommended method is to use a Conda environment or a Docker container to install all dependencies in an isolated environment.

Using the Library in C++

Prerequisites include CMake and a C++ compiler. You can download CMake from here . Use any C++ compiler that supports the C++11 standard and the OpenMP library, such as GCC, Clang, or MSVC.

After installing the prerequisites, you can compile the library and integrate it into your C++ projects. To compile the library, navigate to the IR_lib/cpp directory within the cloned repository. Then, create a directory named build and change your directory to this folder. Execute the following commands:

cd IR_lib/cpp
mkdir build
cd build

Now, execute CMake to configure and generate the build files, and compile the library by running the following commands:

cmake ..
make

The compiled library can be utilized in C++ projects by linking the information_reconciliation library found in the build directory. Example usage of the library in C++ is provided in the IR_lib/cpp/tests directory.

Using the Library in Python and MATLAB

Using Conda

The simplest method to install the library is to create an environment in Conda and compile it. For this, ensure that Conda is installed on your system. If Conda is not installed, you can download it from here .

First, create a Conda environment and then compile the C++ code with Python bindings, allowing it to be used in Python by importing the information_reconciliation module.

Steps:

1. Create a Conda Environment Change directory to the conda folder within the cloned repository. Open the environment.yml file in a text editor and comment/uncomment the lines based on your operating system. Save the file.

   Then, run the following command to create a Conda environment with the required dependencies:

   conda env create -f environment.yml
   

   Now, you have all the dependencies installed in the Conda environment named IR_lib.

2. Activate the Conda Environment by running the following command:

   conda activate IR_lib
   

3. Navigate to the `IR_lib` directory and create a directory named build, then change your directory to this folder. Execute the following commands:

   cd IR_lib
   mkdir build
   cd build
   

4. Compile the Library by running the following commands.

   For Linux /MacOS:

   cmake ..
   cmake --build . --target install
   

   For Windows:

   cmake -G "MinGW Makefiles" -DCMAKE_C_COMPILER=gcc -DCMAKE_CXX_COMPILER=g++ ..
   cmake --build . --target install
   

The compiled library can be used in Python/MATLAB by importing the information_reconciliation module found in the build directory. Examples in Python are provided in the IR_lib/tests directory.

Using Docker

Another method to use the library is to utilize the Docker container. Use the provided Dockerfile in the docker folder to build the Docker image and run the container. Ensure that Docker is installed on your system. If Docker is not installed, you can download it from here .

To use the Docker container, build the image by running the following command in the root directory of the cloned repository:

docker build -t IR_lib -f docker/Dockerfile .

After building the image, run the container by executing the following command:

docker run --rm -it --mount "type=bind,src=${PWD},target=/developer" IR_lib

Now, you can compile the library and use it in the running container. First, connect to the running container. Then, navigate to the IR_lib directory and open the CMakeLists.txt file. Comment out the lines between 29 and 34, which are related to the Conda environment. The lines should look like this:

# Detect conda environment - COMMENT IF YOU DON'T USE CONDA
# if(DEFINED ENV{CONDA_PREFIX})
#   set(CMAKE_PREFIX_PATH $ENV{CONDA_PREFIX})
#   message(STATUS "Conda environment detected: $ENV{CONDA_PREFIX}")
# else()
#   message(WARNING "Conda environment not detected. You may need to activate your environment.")
# endif()

Then, follow steps 3 and 4 in the previous section to compile the library. The compiled library can be used in Python/MATLAB by importing the information_reconciliation module found in the build directory.