QuantumCrypto: A Web Framework for Quantum Cryptography Education
Bibliographic record
Abstract
Quantum cryptography protocols leverage fundamental quantum computing principles such as superposition and entanglement, making them valuable tools for quantum computing education. While existing web platforms offer interactive interfaces to experiment with these protocols, none of them exploits the context in which cryptographic tasks are conducted: real-time communication between parties. We introduce QuantumCrypto-an innovative framework designed to present quantum cryptography protocols as interactive experiences connecting multiple players. QuantumCrypto aims to bridge the gap between theoretical quantum concepts and practical understanding by enabling users to engage in real-time simulations of quantum cryptography protocols. Our solution is extensible, allowing for the integration of new protocols. We demonstrate the versatility of our framework by showcasing the implementation of the BB84 protocol. Through detailed descriptions of the framework's backend and frontend components, we provide insights into its design and implementation. We also elucidate the learning experience of learners who used QuantumCrypto to simulate the BB84 protocol, and provide suggestions for utilizing our tool in a learning environment. To conclude, we summarize our work and present ideas for integrating more quantum cryptography protocols in the future.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".