Generation of THz radiation through molecular modulation in hydrogen-filled hybrid anti-resonant fibers
Bibliographic record
Abstract
We study the generation of narrowband terahertz (THz) pulses by stimulated Raman scattering and molecular modulation in hydrogen-filled hybrid hollow-core fibers. Using a judicious combination of materials and transverse structures, this waveguide design enables simultaneous confinement of optical and THz signals with reasonably low attenuation, as well as high nonlinear overlap. The THz pulses are then generated as the second Stokes band of a ns-long near-infrared pump pulse, aided by Raman coherence waves excited in the gaseous core by the beat-note created by the pump and its first Stokes band. Optimization of the fiber characteristics facilitates phase matching between the corresponding transitions and coherence waves while avoiding coherent gain suppression, resulting in potential optical-to-THz conversion efficiencies up to 60%, as confirmed by rigorous numerical modelling under ideal zero-loss conditions. When the current optical material constraints are considered, however, the attainable efficiencies relax to 0.2%, a still competitive value compared to other systems. The approach is in principle power and energy scalable, as well as tunable in the 1-10 THz range without any spectral gaps, thereby opening new pathways to the development of fiber-based THz sources complementary to other mature technologies such as quantum cascade lasers.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".