Tuning the electrically evaluated electron Landé<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>g</mml:mi></mml:math>factor in GaAs quantum dots and quantum wells of different well widths
Bibliographic record
Abstract
We evaluate the Land\'e $g$ factor of electrons in quantum dots (QDs) fabricated from GaAs quantum well (QW) structures of different well width. We first determine the Land\'e electron $g$ factor of the QWs through resistive detection of electron spin resonance and compare it to the enhanced electron $g$ factor determined from analysis of the magnetotransport. Next, we form laterally defined quantum dots using these quantum wells and extract the electron $g$ factor from analysis of the cotunneling and Kondo effect within the quantum dots. We conclude that the Land\'e electron $g$ factor of the quantum dot is primarily governed by the electron $g$ factor of the quantum well suggesting that well width is an ideal design parameter for $g$-factor engineering QDs.
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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 | 0.001 |
| 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".