Heat transport as a probe of superconducting gap structure
Bibliographic record
Abstract
The structure of the superconducting gap provides important clues on the symmetry of the order parameter and the pairing mechanism. The presence of nodes in the gap function imposed by symmetry implies an unconventional order parameter, other than s-wave. Here, we show how measurements of the thermal conductivity at very low temperature can be used to determine whether such nodes are present in a particular superconductor, and shed light on their nature and location. We focus on the residual linear term at T →0. A finite value in zero magnetic field is strong evidence for symmetry-imposed nodes, and the dependence on impurity scattering can distinguish between a line of nodes or point nodes. Application of a magnetic field probes the low-energy quasiparticle excitations, whether associated with nodes or with a small value of the gap on some part of the Fermi surface, as in a multi-band superconductor. We frame our discussion around archetypal materials: Nb for s-wave, Tl-2201 for d-wave, Sr 2 RuO 4 for p-wave and NbSe 2 for multi-band superconductivity. In that framework, we discuss three heavy-fermion superconductors: CeIrIn 5 , CeCoIn 5 and UPt 3 .
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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 | 0.001 |
| 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 | 0.001 |
| 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".