Broadband optical coupling between microstructured fibers and photonic band gap circuits: Two-dimensional paradigms
Bibliographic record
Abstract
We demonstrate high efficiency, broadband coupling between photonic crystal waveguides and photonic crystal fibers (PCFs) using simple two-dimensional design models. We demonstrate an effective large-bandwidth small-footprint beam collimator for light exiting a two-dimensional subwavelength scale photonic crystal waveguide consisting of an air core. This collimator relies on destructive interference between diffracted light from the mouth of the waveguide and the light emitted by surface resonators. We demonstrate efficient coupling between air-core photonic crystal waveguides and various two-dimensional models of photonic crystal fibers. A hollow-core photonic crystal fiber, described by an air defect with a Bragg stack cladding on either side, yields a coupling efficiency of better than 94% over a bandwidth of 25% of the center frequency, with peak transmittance exceeding 98%. A small-mode-area PCF, consisting of a subwavelength solid core attached by spokes to the PCF cladding, is modeled by a slab waveguide. In this latter case, we demonstrate coupling efficiency better than 94% over a bandwidth of 17%, with peak transmittance exceeding 99%. Combining collimation at the photonic crystal exit port and a nonadiabatic taper in a small-mode-area PCF, we obtain over 98% coupling efficiency over a bandwidth of $135\phantom{\rule{0.3em}{0ex}}\mathrm{nm}$ centered at a wavelength of $1.5\phantom{\rule{0.3em}{0ex}}\ensuremath{\mu}\mathrm{m}$. These results provide valuable paradigms for efficient transfer of optical information between photonic band gap (PBG) microcircuits and PCF-enabled telecommunication networks.
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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".