Bibliographic record
Abstract
The phase coherent properties of electrons in low temperature graphene are measured and analyzed. I demonstrate that graphene is able to coherently transport spin-polarized electrons over micrometer distances, and prove that magnetic defects in the graphene sheet are responsible for limiting spin transport over longer distances. It is shown that these magnetic defects are also partly responsible for the high decoherence (phase loss) observed at low temperature, and that another (as yet unknown) non-magnetic mechanism is required to explain the remainder. Similar measurements are used to probe and characterize the size scales of the roughness of the graphene sheet. The effects of an in-plane magnetic field threading through the rough graphene sheet are analogous to the effects of the built-in strain; I argue that the observed large valley-dependent scattering rates are a consequence of this built-in strain. I also describe an original, robust technique for extracting coherence information from conductance fluctuations. The technique is demonstrated in experiments on graphene, used to efficiently detect the presence of magnetic defects. This new approach to studying phase coherence can be easily carried over to other mesoscopic semiconducting systems.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".