Using a flux threaded composite loop to identify the pairing symmetry of iron based superconductors
Bibliographic record
Abstract
Identifying the correct order parameter structure of the iron based superconductors family will provide insight about the pairing mechanism in these materials. Due to their multi-orbital band structure, the proximity of the superconducting phase to an anti-ferromagnetic phase, and the fact that superconductivity on these materials is associated to the Fe-pnictide layer, most theories favour an unconventional pairing mechanism, and an s± pairing symmetry, which changes signs between the electron and hole Fermi pockets. However, as most experiments are only sensitive to the magnitude of the order parameter and theoretical proposals for phase sensitive experiments are challenging, the s± structure remains unconfirmed. In 2010, Chen et al. performed a phase sensitive experiment that showed evidence of integer flux quantum and half integer flux quantum jumps in a Nb- NdFeAsO_0.88F_0.12 composite loop (Chen et al., 2010). This experiment has been interpreted as evidence of the predicted s± pairing symmetry. Inspired by these results, we present a microscopic lattice model to study the energy dependence on flux for an iron-pnictide/s-wave superconductor composite loop.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".