Impact of Excited States Transitions on Polarization Property of InAs/InP Quantum Dots
Bibliographic record
Abstract
Self-assembled InAs/InGaAsP/InP quantum dots (QD) have been investigated intensively, in which polarization property is a key performance indicator in some photonic devices, such as semiconductor QD optical amplifiers. Conventionally, increased transverse magnetic (TM) polarization is achieved by increased heavy-hole (HH) - light-hole (LH) mixing, such as using closely stacked QDs with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">large</i> stacking layer number (SLN), which was predicted by previous theoretical works and verified experimentally. However, high TM polarization in the closely stacked QDs with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">small</i> SLNs was not predicted by the current theory but confirmed experimentally. In this work, closely stacked InAs/InGaAsP/InP QDs with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">small</i> SLNs are investigated including strain, piezoelectricity and spin-orbit interaction. It is found that the high TM polarization in the closely stacked InAs/InP QDs with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">small</i> SLNs is attributed to strong first excited state transitions and thus more p-type wavefunctions involved, rather than the high HH-LH mixing. With increase of SLN, TM polarization contributed by first excited state transitions decreases, while it contributed by the HH-LH mixing increases.
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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) | 0.001 | 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".