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Record W2077431813 · doi:10.1103/physrevlett.95.106402

Dynamical Breakup of the Fermi Surface in a Doped Mott Insulator

2005· article· en· W2077431813 on OpenAlexaff
Marcello Civelli, Massimo Capone, S. S. Kancharla, Olivier Parcollet, Gabriel Kotliar

Bibliographic record

VenuePhysical Review Letters · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsRegroupement Québécois sur les Matériaux de PointeUniversité de Sherbrooke
Fundersnot available
KeywordsCondensed matter physicsMott insulatorQuasiparticleFermi surfacePhysicsHubbard modelScattering rateMetal–insulator transitionScatteringAntiferromagnetismMott transitionPseudogapRenormalizationDopingSuperconductivityQuantum mechanicsElectrical resistivity and conductivityCuprate

Abstract

fetched live from OpenAlex

The evolution from an anomalous metallic phase to a Mott insulator within the two-dimensional Hubbard model is investigated by means of the cellular dynamical mean-field theory. We show that approaching the density-driven Mott metal-insulator transition the Fermi surface is strongly renormalized and the quasiparticle description breaks down in a very anisotropic fashion. Regions where the quasiparticles are strongly scattered (hot spots) and regions where the scattering rate is relatively weak (cold spot) form irrespective of whether the parent insulator has antiferromagnetic long-range order, while their location is not universal and is determined by the interplay of the renormalization of the scattering rate and the Fermi surface shape.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.011
GPT teacher head0.262
Teacher spread0.251 · 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 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

Citations193
Published2005
Admission routes1
Has abstractyes

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