Interplay between hole superconductivity and quantum critical antiferromagnetic fluctuations in electron-doped cuprates
Bibliographic record
Abstract
Antiferromagnetic spin fluctuations are the most promising candidate as the pairing glue of high critical temperature (Tc) superconductivity in cuprates. However, many-body states and intertwined orders have made it difficult to determine how electrons couple with fluctuating spins to form Cooper pairs. Recent experimental and theoretical studies have suggested spin fluctuation-driven quasiparticle band folding, but the relationship between the resultant Fermi pockets and superconductivity remains unclear. Here, using angle-resolved photoemission spectroscopy and numerical simulations, we show a proportional relationship between Tc and the quasiparticle weight of the incipient hole pocket near the nodal point in electron-doped Pr1−xLaCexCuO4±δ. Through complementary muon spin spectroscopy measurements, we uncover that the hole pocket forms only in the regime of the fluctuating antiferromagnetic ground state around a presumed quantum critical point. Our observations highlight the significance of the electron-spin fluctuation interaction in enhancing the hole pocket and consequently driving superconductivity. The authors study electron-doped cuprate superconductor Pr1−xLaCexCuO4-δ using ARPES and muon spin spectroscopy. They find that Tc is proportional to the quasiparticle weight of the hole pocket near the nodal points, which arises from Fermi-surface reconstruction associated with antiferromagnetic order.
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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 | 0.000 |
| 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".