The repository contains four proof-of-principle realizations for algorithms applied for the post-processing procedure of sifted keys in quantum key distribution (QKD) setup designed in Russian Quantum Center. All the algorithms are realized in Python 2.7.

Includes simulation of symmetric blind reconciliation together with verification using universal polynomial hashing.

Performs estimation of the quantum bit error rate (QBER) using the result of the error correction procedure.

Performs distillation of secure key according to BB84 decoy state protocol using Toeplitz hashing.

Performs calculation and check of authentication hash-tag according to Toeplitz or GOST R 34.12-2015 hashing.

Here we briefly describe all the .py script presented in the repository. Please, use -h or --help for the detailed description of input and output data.

The folder contains .py scripts related to the authentication procedure.

• __init__.py Auxiliary file.
• au_input_generator.py Performs genereration of the input data for authentication.py script.
• authentication.py Performs calculation of the authentication hash-tag using Toeplitz or GOST R 34.12-2015 hashing.

The folder containts .py files with auxiliary functions used by different the algorithms.

• __init__.py Auxiliary file.
• files.py Contains functions related to input/output with files.
• funcs.py Contains mathmatical functions.
• generate.py Contains function related to operations with keys.
• parseargs.py Contains functions related to argument processing.

The folder contains .py scripts related to the error correction procedure.

• __init__.py Auxiliary file.
• codes.py Performs generation of the parity check matrices with improved progressive edge growing algorithm with particular distribuition polynomials. The set of code rates contains nine elements: {0.9, 0.85, ..., 0.5}. The algortithm also generates a set of symbol postions for the untainted puncturing technique
• ec_input_generator.py Performs genereration of the input data for error_correction.py script (except the set of parity check matrices).
• error_correction.py Performs a simulation of the error correction with symmetric blind reconciliation together with verification based on universal polynomial hashing.

The folder contains .py scripts related to the error estimation procedure.

• __init__.py Auxiliary file.
• ee_input_generator.py Performs generation of the input data for error_estimation.py script.
• error_estimation.py Performs estimation of the error in the quantum channel according to the result of error correction procedure.

The folder contains .py scripts related to the privacy amplification procedure.

• __init__.py Auxiliary file.
• pa_input_generator.py Performs genereration of the input data for privacy_amplification.py script.
• privacy_amplification.py Performs generation of the secure key according to BB84 decoy state protocol and Toeplitz hashing.

The storage of parity-check matrices is based on two variables: s_y_joins and y_s_joins. They contains positions of nonzero elements for each row and column correspondingly. For example, for the matrix

H =
1 1 0 1
1 0 1 1
0 1 1 0

one has

s_y_joins = [[0,1,3], [0,2,3],[1,2]]
y_s_joins = [[0,1],[0,2], [1,2],[0,1]]