quantumspiritresearch-crypto/qkd-krylov-detector
Eavesdropper detection & quantum channel benchmarking for QKD — Physical Bridge, Lindblad extension, error diagnostics, Krylov complexity, one-way function property
What's novel
Eavesdropper detection & quantum channel benchmarking for QKD — Physical Bridge, Lindblad extension, error diagnostics, Krylov complexity, one-way function property
Code Analysis
5 files read · 2 roundsImplements a theoretical framework linking quantum many-body dynamics (via Krylov/Lanczos methods) to observable QBER statistics in Quantum Key Distribution to detect eavesdropping.
Strengths
The project demonstrates high innovation by bridging advanced quantum chaos theory (Lanczos coefficients) with practical QKD security monitoring. The code is well-structured, modular, and uses clear, physics-appropriate naming conventions. It avoids heavy external dependencies by implementing core algorithms like the Lanczos method in pure NumPy.
Weaknesses
Error handling is minimal, relying on standard library exceptions without specific validation for physical constraints (e.g., matrix dimensions, positivity of QBER). Test coverage appears non-existent or very basic, lacking edge case testing for numerical instability in the Lanczos algorithm. The lack of a `main.py` or CLI entry point suggests it might be more of a research script than a production-ready tool.
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
25
Contributors
1
Files
38
Active weeks
2
Repository
Language
Python
Stars
3
Forks
0
License
AGPL-3.0