Arbitrary Phase Access for Stable Fiber Interferometers
Bibliographic record
Abstract
Abstract Well‐controlled yet practical systems that give access to interference effects are critical for established and new functionalities in ultrafast signal processing, quantum photonics, optical coherence characterization, etc. Optical fiber systems constitute a central platform for such technologies. However, harnessing optical interference in a versatile and stable manner remains technologically costly and challenging. Here, degrees of freedom native to optical fibers, i.e., polarization and frequency, are used to demonstrate an easily deployable technique for the retrieval and stabilization of the relative phase in fiber interferometric systems. The scheme gives access (without intricate device isolation) to <1.3 × 10−3 π rad error signal Allan deviation across 1 ms to 1.2 h integration times for all tested phases, ranging from 0 to 2π. More importantly, the phase‐independence of this stability is shown across the full 2π range, granting access to arbitrary phase settings, central for, e.g., performing quantum projection measurements and coherent pulse recombination. Furthermore, the scheme is characterized with attenuated optical reference signals and single‐photon detectors, and extended functionality is demonstrated through the use of pulsed reference signals (allowing time‐multiplexing of both main and reference signals). Finally, the scheme is used to demonstrate radiofrequency‐controlled interference of high‐dimensional time‐bin entangled states.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".