Efficient and widely tunable mid-infrared sources using GaAs and AlGaAs integrated platforms for second-order frequency conversion
Bibliographic record
Abstract
Integrated coherent mid-infrared (mid-IR) sources are crucial for spectroscopy and quantum frequency conversion (QFC) to facilitate scalable fiber-based application of single photons. Direct mid-IR emission with broad tunability poses fundamental challenges from the gain media and mirror components. This paper presents a characterization of a second-order nonlinear platform. It showcases a mid-IR parametric coherent source with a continuous tuning range exceeding 230 nm centered around 2425 nm, achieved through difference-frequency generation (DFG). The nonlinear coefficient d 14 of gallium arsenide (GaAs) and aluminum gallium arsenide (AlGaAs) on insulator is experimentally determined via second-harmonic generation (SHG) in waveguides of various lengths, and the tolerance of the process is investigated. These materials are explored for their high conversion efficiency, utilizing monolithic epitaxial quantum dots and integrated waveguides for QFC. The results demonstrate efficient and tunable mid-IR emission suitable for compact, scalable quantum emitters, with applications in environmental and health monitoring.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".