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Record W4415061389 · doi:10.1103/x1m7-bs95

Inhomogeneity, fluctuations, and gap filling in disordered overdoped cuprates

2025· preprint· en· W4415061389 on OpenAlexafffund
Miguel Antonio Sulangi, Willem Farmilo, Andreas Kreisel, Mainak Pal, W. A. Atkinson, P. J. Hirschfeld

Bibliographic record

VenuePhysical Review Research · 2025
Typepreprint
Languageen
FieldMathematics
TopicMathematical Dynamics and Fractals
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of CanadaDivision of Materials ResearchShared Hierarchical Academic Research Computing NetworkAlliance de recherche numérique du CanadaNational Science Foundation
KeywordsCupratePairingSuperconductivityCoherence (philosophical gambling strategy)Phase (matter)Quantum tunnellingThermal fluctuationsSpectral line

Abstract

fetched live from OpenAlex

Several recent experiments have challenged the premise that cuprate high-temperature superconductors approach conventional Landau-BCS behavior in the high-doping limit. We argue, based on an analysis of their superconducting spectra, that anomalous properties seen in the most-studied overdoped cuprates require a pairing interaction that is strongly inhomogeneous on nm length scales. This is consistent with recent proposals that the “strange-metal” phase above <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"> <a:msub> <a:mi>T</a:mi> <a:mi>c</a:mi> </a:msub> </a:math> in the same doping range arises from a spatially random interaction. We show, via mean-field Bogoliubov-de Gennes (BdG) calculations and time-dependent Ginzburg-Landau (TDGL) simulations, that key features of the observed tunneling spectra are reproduced when both inhomogeneity and thermal phase fluctuations are accounted for. In accord with experiments, BdG calculations find that low- <b:math xmlns:b="http://www.w3.org/1998/Math/MathML"> <b:mi>T</b:mi> </b:math> spectra are highly inhomogeneous and exhibit a low-energy spectral shoulder and broad coherence peaks. However, the spectral gap in this approach becomes homogeneous at high <c:math xmlns:c="http://www.w3.org/1998/Math/MathML"> <c:mi>T</c:mi> </c:math> , in contrast to experiments. This is resolved when thermal fluctuations are included within TDGL; in this case, global phase coherence is lost at the superconducting <d:math xmlns:d="http://www.w3.org/1998/Math/MathML"> <d:msub> <d:mi>T</d:mi> <d:mi>c</d:mi> </d:msub> </d:math> via a broadened BKT transition, while robust phase-coherent superconducting islands persist well above <e:math xmlns:e="http://www.w3.org/1998/Math/MathML"> <e:msub> <e:mi>T</e:mi> <e:mi>c</e:mi> </e:msub> </e:math> . The local spectrum remains inhomogeneous at <f:math xmlns:f="http://www.w3.org/1998/Math/MathML"> <f:msub> <f:mi>T</f:mi> <f:mi>c</f:mi> </f:msub> </f:math> , and the gap is found to fill instead of close with increasing temperature.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.257
GPT teacher head0.531
Teacher spread0.274 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations3
Published2025
Admission routes2
Has abstractyes

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