Alignment-free dispersion measurement with interfering biphotons
Bibliographic record
Abstract
Measuring the dispersion of photonic devices with small dispersion-length products is challenging due to the phase-sensitive and alignment-intensive nature of conventional methods. In this Letter, we demonstrate a quantum technique to extract the second- and third-order chromatic dispersion of a short single-mode fiber using a fiber-based quantum nonlinear interferometer. The interferometer consists of two cascaded fiber-based biphoton sources, with each source acting as a nonlinear beam splitter. A fiber under test is placed between these two sources and introduces a frequency-dependent phase that is imprinted on the biphoton spectrum (interferogram) at the output of the interferometer. This interferogram contains the dispersion properties of the test fiber. Our technique has three novel features: (1) the broadband nature of the biphoton sources used in our setup allows accurate dispersion measurements on test devices with small dispersion-length products; (2) our all-fiber common-path interferometer requires no beam alignment or phase stabilization; and (3) multiple phase-matching processes supported in our biphoton sources enable dispersion measurements at different wavelengths, which yields the third-order dispersion achieved for the first time, to the best of our knowledge, using a quantum optical technique.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".