Development of a Compact, Fiber-based, Hyper-entangled Photon Pair Source
Bibliographic record
Abstract
This thesis explores a method to enhance the practical utility of hyper-entangled photons generatedin periodically poled silica fiber for quantum communication applications. Hyper-entanglement, which involves quantum correlations in multiple degrees of freedom simultaneously, offers increased information capacity per particle compared to single-degree entanglement. Periodically poled sil- ica fiber has shown promise in generating high-quality, broadband polarization-frequency hyper- entangled photon pairs collinearly through type-II spontaneous parametric down-conversion. How- ever, the collinear nature of these photon pairs poses a challenge for applications requiring hyper- entanglement, as they occupy the same spatial mode. This research develops a technique for sep- arating these photon pairs while preserving their information capacity, measures the resulting en- tanglement quality degradation, and discusses potential improvements. This work contributes to the development of efficient fiber-based hyper-entanglement sources, advancing the field of practical quantum technologies and long-distance quantum communication.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".