Valley polarization, magnetization, and superconductivity in bilayer graphene near the van Hove singularity
Bibliographic record
Abstract
The discovery of Mott insulators and superconductivity in twisted bilayer graphene has ignited intensive research into strong correlation effects in other stacking geometries. Bernal-stacked bilayer graphene (BBG), when subjected to a perpendicular electric field, exhibits phase transitions to a variety of broken-symmetry states. Notably, superconductivity emerges when BBG is in proximity to a heavy transition-metal dichalcogenide, highlighting the role of spin-orbit coupling (SOC). Here, we investigate the origin of Ising SOC and its role in the competition between superconductivity and spin- and valley-polarized states in BBG. Starting from strong electron-electron interactions on the BBG lattice, we derive a low-energy effective model near the valleys that incorporates both density-density and spin-spin interactions. Using self-consistent mean-field theory, we map out the BBG phase diagram. Our findings reveal that near the van Hove filling, a mixed spin- and valley-polarized phase dominates over superconductivity. Away from the van Hove filling, a spin-polarized, spin-triplet superconducting state arises, characterized by an in-plane orientation of the magnetic moment and an out-of-plane orientation of the $d$ vector. Contrary to previous proposals, we find that Ising SOC favors spin-valley order while suppressing superconductivity near the van Hove singularity. We discuss other potential proximity effects and suggest directions for future studies.
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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) | 0.001 | 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".