Superconducting phase transition in planar fermionic models with Dirac cone tilting
Bibliographic record
Abstract
The chiral and superconducting gaps are studied in the context of a planar fermion model with four-fermion interactions. The effect of the tilt of the Dirac cone on both gaps is shown and discussed. Our results point to two different behaviors exhibited by planar fermionic systems. We show that there is a threshold value ${\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{t}}^{*}$ for the effective tilt parameter such that when $|\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{\mathbf{t}}|<{\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{t}}^{*}$, the superconducting phase persists for negative values of the superconducting coupling constant. For positive values of the superconducting coupling constant, the induction of a superconducting gap by a chemical potential exists, which is similar to the one seen in graphenelike systems. For $|\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{\mathbf{t}}|>{\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{t}}^{*}$ and a negative superconducting coupling constant, the superconducting phase can be present, but it is restricted to a smaller area in the phase portrait. Our analysis also shows that when $|\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{\mathbf{t}}|>{\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{t}}^{*}$ and for positive values for the superconducting coupling constant, the induction of a superconducting gap in the presence of a chemical potential is ruled out. In this case, the increase of the chemical potential works in favor of the manifestation of a metallic phase.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".