Utils Module

This module provides utility functions and components that support key QKD operations such as entanglement generation, key rate analysis, and unit testing.

1. entanglement_manage.py

Provides tools for generating Bell pairs and distributing them between two quantum nodes.

Class: EntanglementManager

Handles the creation and distribution of entangled quantum states between two nodes.

Methods:

  • __init__()

  • Initializes an empty dictionary of entangled pairs.

  • create_bell_pair(node_a: Node, node_b: Node, bell_type='00')

  • Creates a Bell state (default Φ⁺) between node_a and node_b.

  • Applies Hadamard and CNOT to prepare the state.
  • Returns a pair ID and the shared quantum state.

Use case: Used in protocols like E91 to simulate entanglement-based QKD.

2. key_rate.py

Implements formulas for computing the theoretical key generation rate.

Function: binary_entropy(q)

Returns the Shannon binary entropy of probability q. If q is 0 or 1, returns 0.

Function: compute_key_rate(qber, sifted_rate=0.5)

  • Computes the asymptotic key rate for a given QBER (Quantum Bit Error Rate).
  • Applies the formula: key_rate = sifted_rate × max(0, 1 - 2 × H(qber))

Returns a rounded value to 6 decimal places.

Use case: Estimating secret key yield under noisy channels.

3. test.py

Test script to validate entanglement correlation between two nodes.

Purpose:

  • Verifies that Bell pairs created by EntanglementManager result in perfectly correlated measurement outcomes.
  • Performs 1000 trials and prints the count of matching outcomes.

Key Elements:

  • Uses a DummyEnv class to mock SimPy environment.
  • Creates two nodes (Alice and Bob).
  • Creates Bell pairs and measures in the Z-basis.
  • Uses Python’s Counter to analyze frequency of correlated outcomes.

Use case: Demonstrates entanglement fidelity and correlation statistics for Bell state Φ⁺ in the simulation.