Superconducting correlations induced by charge ordering in cuprate superconductors and Fermi-arc formation
Bibliographic record
Abstract
We have developed a generalized electronic phase separation model of high-temperature cuprate superconductors that links the two distinct energy scales of the superconducting (SC) and pseudogap (PG) phases via a charge-density-wave (CDW) state. We show that simulated electronic-density modulations resembling the charge order modulations detected in cuprates intertwine the SC and charge orders by localizing charge and providing the energy scale for a spatially periodic SC attractive potential. Bulk superconductivity is achieved with the inclusion of Josephson coupling between nanoscale domains of intertwined fluctuating CDW and SC orders, and local SC phase fluctuations give rise to the Fermi arcs along the nodal directions of the SC gap. We demonstrate the validity of the model by reproducing the hole-doping dependence of the PG onset temperature ${T}^{*}$, and the SC transition temperature ${T}_{c}$ of ${\mathrm{YBa}}_{2}{\mathrm{Cu}}_{3}{\mathrm{O}}_{\mathrm{y}}$ and ${\mathrm{Bi}}_{2\ensuremath{-}\mathrm{y}}{\mathrm{Pb}}_{\mathrm{y}}{\mathrm{Sr}}_{2\ensuremath{-}\mathrm{z}}{\mathrm{La}}_{\mathrm{z}}{\mathrm{CuO}}_{6+\ensuremath{\delta}}$. The results show that the periodicity of the CDW order is controlled by the PG energy scale, and the hole-doping dependence of the SC energy gap is controlled by the charge ordering.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".