A modeling and verification framework for optical quantum circuits
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Bibliographic record
Abstract
Abstract Quantum computing systems promise to increase the capabilities for solving problems which classical computers cannot handle adequately, such as integers factorization. In this paper, we present a formal modeling and verification approach for optical quantum circuits, where we build a rich library of optical quantum gates and develop a proof strategy in higher-order logic to reason about optical quantum circuits automatically. The constructed library contains a variety of quantum gates ranging from 1-qubit to 3-qubit gates that are sufficient to model most existing quantum circuits. As real world applications, we present the formal analysis of several quantum circuits including quantum full adders and the Grover’s oracle circuits, for which we have proved the behavioral correctness and calculated the operational success rate, which has never been provided in the literature. We show through several case studies the efficiency of the proposed framework in terms of the scalability and modularity.
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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 | 0.000 |
| 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