UNIVERSITY OF CALGARY Entanglement Swapping with Imperfect Sources and Detectors
Bibliographic record
Abstract
ii In an effort to overcome the distance limits of quantum key distribution (QKD), entan-glement swapping is used as a fundamental building block in quantum relays and quan-tum repeaters. Although entanglement swapping enables any distance to be achieved in principle, experimental realization suffers from imperfect sources of entangled pairs and detectors. Here, I incorporate the multi-photon nature of the source and imperfect detectors into a model of entanglement swapping. Specifically, I calculate the resultant entangled state given two parametric down conversion (PDC) sources where one mode of each PDC source meets at a beam splitter and is subjected to photon counting by inefficient detec-tors. I then calculate the entanglement fidelity of this resultant state. In addition, detectors used in quantum optical experiments occasionally produce dark counts and do not always detect incoming photons. These imperfections need to be taken into account when performing calculations involving such detectors. I have developed a thermal detector model that predicts the click probability for an inefficient detector sub-ject to dark counts. iii
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.052 | 0.009 |
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 source (direct Gemma or distilled Codex), 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".