Simplified density-matrix model applied to three-well terahertz quantum cascade lasers
Bibliographic record
Abstract
A simplified density-matrix model describing the population and coherence terms of four states in a resonant phonon scattering based terahertz quantum cascade laser is presented. Despite its obvious limitations and with two phenomenological terms---called the pure dephasing time constants in tunneling and intersubband transition---the model agrees reasonably well with experimental data. We demonstrate the importance of a tunneling leakage channel from the upper lasing state to the excited state of the downstream phonon well. In addition, we identify an indirect coupling between nonadjacent injector and extractor states. The analytical expression of the gain spectrum demonstrates the strong broadening effect of the injection and extraction couplings. The gain is decomposed into three terms: a linear gain and two nonlinear components related to stimulated anti-Stokes scattering processes. The nonlinear gain is not negligible at high temperature. Under certain approximations, analytical forms of population and coherence terms are derived. This model is well suited for structures with only a few states involved. This model can simplify the optimization process for new laser designs; it is also convenient for experimentalists to adopt.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".