Nodal pair density waves from a quarter-metal in crystalline graphene multilayers
Bibliographic record
Abstract
Crystalline graphene heterostructures, namely, Bernal bilayer graphene (BBLG) and rhombohedral trilayer graphene (RTLG), for example, subject to perpendicular electric displacement fields, display a rich confluence of competing orders, resulting in a valley-degenerate, spin-polarized half-metal at moderate doping, and a spin- and valley-polarized (nondegenerate) quarter-metal at lower doping. Here we show that such a quarter-metal can be susceptible toward the nucleation of a unique spin- and valley-polarized superconducting ground state, accommodating odd-parity (dominantly $p$ wave in BBLG and $f$ wave in RTLG) interlayer Cooper pairs that break the translational symmetry, giving rise to a Kekule (in BBLG) or columnar (in RTLG) pair density wave. Due to the trigonal warping in the normal state, the superconducting ground state produces threefold rotationally symmetric isolated Fermi rings of normal fermions, which can manifest via linear in temperature scaling of the specific heat. We present scaling of the zero-temperature pairing amplitude and the transition temperature of such pair density wave in the presence of trigonally warped disconnected, annular, and simply connected Fermi rings in the normal state, subject to an effective attractive interaction within a mean-field approximation.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".