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Record W3022530209 · doi:10.1103/physrevb.66.054522

Anomalous temperature dependence of spin susceptibility around a nonmagnetic impurity in high-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow><mml:mrow><mml:mi>c</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>cuprate superconductors

2002· article· lv· W3022530209 on OpenAlexaff
Yoji Ohashi

Bibliographic record

VenuePhysical review. B, Condensed matter · 2002
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCondensed matter physicsImpuritySuperconductivitySpin (aerodynamics)CuprateAntiferromagnetismPhysicsMagnetic susceptibilityKnight shiftMagnetic impurityQuantum mechanicsThermodynamics

Abstract

fetched live from OpenAlex

Local magnetic properties around a nonmagnetic impurity are investigated in the superconducting state of high-${T}_{c}$ cuprates. We consider a model two-dimensional ${d}_{{x}^{2}\ensuremath{-}{y}^{2}}$-wave superconductor with strong antiferromagnetic (AF) spin fluctuations and calculate the spin susceptibility around the impurity. We show that the uniform susceptibility, which is usually suppressed in spin-singlet superconductivity, increases with decreasing temperature around the impurity when the impurity scattering is in the unitarity limit. This anomalous temperature dependence is more remarkable when the impurity potential is extended spatially and the AF spin fluctuations are stronger. Our results agree with the anomalous temperature dependence of the Knight shift on Li that was recently observed in ${\mathrm{YBa}}_{2}({\mathrm{Cu}}_{1\ensuremath{-}x}{\mathrm{Li}}_{x}{)}_{3}{\mathrm{O}}_{6+y}.$

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.003
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.6140.004

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 head0.017
GPT teacher head0.252
Teacher spread0.235 · 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; both teacher heads agree on what is shown here.

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
Published2002
Admission routes1
Has abstractyes

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