Phenomenological description of competing antiferromagnetism and d-wave superconductivity in high $T_{c}$ cuprates
Bibliographic record
Abstract
In this paper the phase diagram of high $T_{c}$ cuprates is {\it qualitatively} studied in the context of competing orders: antiferromagnetism, d-wave superconductivity and $d$-density wave. {\it Local} correlation functions are estimated from a mean-field solution of the $t-J$ Hamiltonian. With decreasing doping the superconducting mean-field $T^{MF}_{c}$ and order parameter $d$ begin to decrease below some characteristic doping $x_{c} \simeq 0.2$ where short-range antiferromagnetic correlations begin to develop. {\it Dynamical} properties that involve the energy spectrum, such as the normal state pseudogap, are calculated from effective interactions that are consistent with the above-mentioned local correlation functions. The total excitation gap $Δ_{tg}$ (in the superconducting state) and the normal state pseudogap $Δ_{pg}$ are in good agreement with experimental results. Properties of the condensate are estimated using an effective pairing interaction $V_{eff}$ which takes into account (pair breaking) antiferromagnetic correlations. These condensate properties include condensation energy U(0), coherence gap $Δ_{cg}$ and critical field $H_{c2}$. The calculated coherence gap closely follows the doping dependence of $T_{c}$ or $d$, and is approximately given as $Δ_{cg} \sim Δ_{tg}-Δ_{pg}$ within our numerical uncertainties. The systematic decrease of superfluidity ($d$, U(0), $Δ_{cg}$, $H_{c2}$), and systematic increase of $Δ_{pg}$ and $Δ_{tg}$ with decreasing doping below $x_{c}$ have their natural explanation in our approach. The overall description is however qualitative since it does not appear possible to obtain results that are in quantitative agreement with experiment for all physical quantities.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".