Semiconductor laser simulations using non-equilibrium Green’s functions
Bibliographic record
Abstract
We present a novel method to simulate quantum well, edge-emitting semiconductor lasers in non-equilibrium steady-state. Our method is based on non-equilibrium Green’s functions approach which allows for a fully quantum mechanical description of carrier and photon dynamics. This microscopic approach significantly reduces the number of phenomenological parameters needed to simulate laser. General equations for photon Green’s functions and polarizations are derived as well as their coupling to electron Green’s functions through self-energies. Series of approximations are done to photon Green’s function to allow for efficient numerical approach. All equations are written in the non-orthogonal basis suitable for numerical calculations. As an example, the theory is applied to analyze Al0.2Ga0.8As/GaAs quantum well laser with the effective mass Hamiltonian. Major laser characteristics such as material and modal gain, threshold parameters, carrier and current densities were determined.
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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".