Family of multilayer graphene superconductors with tunable chirality: Momentum-space vortices nucleated by a ring of Berry curvature
Bibliographic record
Abstract
Recent experiments in rhombohedrally stacked multilayer graphene heterostructures have reported signatures of chiral superconductivity, emerging from a spin- and valley-polarized normal state with broken time-reversal symmetry and an associated anomalous Hall effect. These findings bring into focus the role of the electronic Bloch wave function and the quantum geometric tensor in determining the superconducting pairing channel. In this work, we examine superconducting instabilities of a model of $N$-layer rhombohedral graphene that possesses an enhanced Berry curvature distribution on an extended ring in momentum space, that we dub the ``Berry ring of fire,'' in the presence of an isotropic attractive interaction with a parametrically controlled spatial range. We determine that local interactions favor a $N$-fold winding in the order parameter phase for odd-$N$ layered systems, with even-$N$ layers requiring a spatially extended attraction range to achieve pairing. For generic interaction lengths, we discover a family of chiral superconductors and, remarkably, momentum-space vortices nucleated on the Berry ring of fire. The existence of these vortices can be traced to a momentum-space flux quantization condition involving the Berry curvature, with the phase winding dictated by a combination of the Berry flux and a ``statistical flux'' to enforce Fermi-Dirac statistics. Such an order-parameter structure allows for the possibility of in situ tuning between various chiral superconducting phases through changes in the electron density or the displacement field. We discuss ways in which these predictions can be experimentally tested and potentially exploited in future devices.
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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) | 0.000 | 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".