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Record W1976440702 · doi:10.1103/physrevb.82.094523

Specific heat across the superconducting dome in the cuprates

2010· article· en· W1976440702 on OpenAlexaff
Adrien Borne, J. P. Ćarbotte, E. J. Nicol

Bibliographic record

VenuePhysical Review B · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsMcMaster UniversityCanadian Institute for Advanced ResearchUniversity of Guelph
Fundersnot available
KeywordsPseudogapCondensed matter physicsCuprateSuperconductivityFermi surfacePhysicsPhase diagramFermi liquid theoryQuantum critical pointDopingFermi energyQuantum mechanicsPhase (matter)Quantum phase transitionPhase transitionElectron

Abstract

fetched live from OpenAlex

The specific heat of the superconducting cuprates is calculated over the entire phase diagram. A $d$-wave BCS approach based on the large Fermi surface of Fermi liquid and band-structure theory provides a good description of the overdoped region. At underdoping it is essential to include the emergence of a second energy scale, the pseudogap and its associated Gutzwiller factor, which accounts for a reduction in the coherent piece of the electronic Green's function due to increased correlations as the Mott insulating state is approached. In agreement with experiment, we find that the slope of the linear in $T$ dependence of the low-temperature specific heat rapidly increases above optimum doping while it is nearly constant below optimum. Our theoretical calculations also agree with recent data on ${\text{Bi}}_{2}{\text{Sr}}_{2\ensuremath{-}\text{x}}{\text{La}}_{\text{x}}{\text{CuO}}_{6+\ensuremath{\delta}}$ for which the normal state is accessed through the application of a large magnetic field. A quantum critical point is located at a doping slightly below optimum.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.024
GPT teacher head0.329
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2010
Admission routes1
Has abstractyes

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