qkdSim, a Simulation Toolkit for Quantum Key Distribution Including Imperfections: Performance Analysis and Demonstration of the B92 Protocol Using Heralded Photons
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Quantum key distribution (QKD) is one of the most important aspects of quantum cryptography. Using laws of quantum mechanics as the basis for security, the key-distribution process makes information theoretically secure in QKD. With the advancement and commercialization of QKD, an end-to-end QKD simulation software is required that can include experimental imperfections. Software of this kind will ensure that resources are invested only after prior performance analysis, and is faithful to experimental capacities and limitations. In this work, we introduce our QKD simulation toolkit qkdSim, which is ultimately aimed at being developed into such a software package that can precisely model and analyze any generic QKD protocol. We present the design, implementation, and testing of a prototype of qkdSim that can accurately simulate our own experimental demonstration of the B92 protocol. The simulation results match well with experiment; a representative key rate and the quantum bit error rate from experiment is $51\ifmmode\pm\else\textpm\fi{}0.5$ kbit/sec and $4.79\mathrm{%}\ifmmode\pm\else\textpm\fi{}0.01\mathrm{%}$ respectively, wherein the simulation yields $52.83\ifmmode\pm\else\textpm\fi{}0.36$ kbit/sec and $4.79\mathrm{%}\ifmmode\pm\else\textpm\fi{}0.01\mathrm{%}$, respectively.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it