Bright quantum photon sources from a topological Floquet resonance
Bibliographic record
Abstract
Abstract Entanglement, a fundamental concept in quantum mechanics, plays a crucial role as a valuable resource in quantum technologies. The practical implementation of entangled photon sources encounters obstacles arising from imperfections and defects inherent in physical systems and microchips, resulting in a loss or degradation of entanglement. The topological photonic insulators, however, have emerged as promising candidates, demonstrating an exceptional capability to resist defect-induced scattering, thus enabling the development of robust entangled sources. Despite their inherent advantages, building bright and programmable topologically protected entangled sources remains challenging due to intricate device designs and weak material nonlinearity. Here we present an advancement in entanglement generation achieved through a non-magnetic and tunable resonance-based anomalous Floquet insulator, utilizing an optical spontaneous four-wave mixing process. Our experiment demonstrates a substantial enhancement in entangled photon pair generation compared to devices reliant solely on topological edge states and outperforming trivial photonic devices in spectral resilience. This work marks a step forward in the pursuit of defect-robust and bright entangled sources that can open avenues for the exploration of cascaded quantum devices and the engineering of quantum states. Our result could lead to the development of resilient quantum sources with potential applications in quantum technologies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".