Finite-size security analysis for quantum protocols: A Python framework using the Entropy Accumulation Theorem with graphical interface

TL;DR

This paper introduces a Python-based software framework with a GUI for finite-size security analysis of quantum protocols like QRNG and QKD, automating entropy calculations and supporting practical, real-world security certification.

Contribution

It provides a comprehensive, user-friendly platform that automates entropy analysis using the Entropy Accumulation Theorem, facilitating protocol design and security certification under finite resources.

Findings

Automates min-tradeoff function construction via semi-definite programming

Supports various entropy measures and protocol configurations

Enables practical security bounds computation with minimal overhead

Abstract

We present a comprehensive software framework for the finite-size security analysis of quantum random number generation (QRNG) and quantum key distribution (QKD) protocols, based on the Entropy Accumulation Theorem (EAT). Our framework includes both a Python API and an intuitive graphical user interface (GUI), designed to support protocol designers and experimentalists in certifying randomness and key rates under realistic, finite-resource conditions. At its core, the framework automates the construction of min-tradeoff functions via semi-definite programming and integrates them into a full entropy analysis pipeline. Users can specify device configurations, Bell-type inequalities or probability constraints, and select entropy measures such as min-entropy or von Neumann entropy. The package further provides tools for setting test parameters, computing secure randomness rates, and exploring tradeoffs between statistical confidence, protocol duration, and randomness output. We demonstrate the framework showing how users can move from theoretical constraints to practical security bounds with minimal overhead. This work contributes a reproducible, modular, and extensible platform for certifying quantum protocols under finite-size effects, significantly lowering the skill barrier to rigorous quantum cryptographic analysis.