Microwave conductivity in the ferropnictides with specific application to<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mtext>Ba</mml:mtext></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:mi>x</mml:mi></mml:mrow></mml:msub><mml:msub><mml:mtext>K</mml:mtext><mml:mi>x</mml:mi></mml:msub><mml:msub><mml:mrow><mml:mtext>Fe</mml:mtext></mml:mrow><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mrow><mml:mtext>As</mml:mtext></mml:mrow><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:math>
Bibliographic record
Abstract
We calculate the microwave conductivity of a two band superconductor with ${s}^{\ifmmode\pm\else\textpm\fi{}}$ gap symmetry. Inelastic scattering is included approximately in a BCS model augmented by a temperature-dependent quasiparticle scattering rate assumed, however, to be frequency independent. The possibility that the $s$-wave gap on one or the other of the electron or hole pockets is anisotropic is explored including cases with and without gap nodes on the Fermi surface. A comparison of our BCS results with those obtained in the two-fluid model is provided as well as with the case of the cuprates where the gap has $d$-wave symmetry and with experimental results in ${\text{Ba}}_{1\ensuremath{-}\ensuremath{\delta}}{\text{K}}_{\ensuremath{\delta}}{\text{Fe}}_{2}{\text{As}}_{2}$. The presently available microwave conductivity data in this material provides strong evidence for large anisotropies in the electron pocket $s$-wave gap. While a best fit favors a gap with nodes on the Fermi surface this disagrees with some but not all penetration-depth measurements which would favor a nodeless gap as do also thermal-conductivity and nuclear-magnetic-resonance data.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".