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Record W1537774441 · doi:10.1103/physrevb.91.245127

Many-body effects in topological Kondo insulators

2015· article· en· W1537774441 on OpenAlexfundno aff
Jason Iaconis, Leon Balents

Bibliographic record

VenuePhysical Review B · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTopological Materials and Phenomena
Canadian institutionsnot available
FundersBasic Energy SciencesNatural Sciences and Engineering Research Council of CanadaU.S. Department of EnergyKavli Institute for Theoretical Physics, University of California, Santa BarbaraOffice of ScienceNational Science Foundation
KeywordsKondo insulatorPhysicsHamiltonian (control theory)Topological insulatorKondo effectCondensed matter physicsImpurityTheoretical physicsInvariant (physics)T-symmetryMean field theoryTopology (electrical circuits)Quantum mechanicsMathematicsSuperconductivity

Abstract

fetched live from OpenAlex

We study the effect of interactions on the properties of a model 2D topological Kondo insulator phase. Loosely motivated by recent proposals where graphene is hybridized with impurity bands from heavy adatoms with partially filled $d$ shells, we introduce a model Hamiltonian which we believe captures the essential physics of the different competing phases. We show that there are generically three possible phases with different combinations of Kondo screening and magnetic order. Perhaps the most dramatic example of many-body physics in symmetry-protected topological phases is the existence of the exotic edge states. We demonstrate that our mean-field model contains a region with a time-reversal-invariant bulk phase but where time-reversal symmetry is spontaneously broken at the edge. Such a phase would not be possible in a noninteracting model. We also comment on the stability of this phase beyond mean-field theory.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.314
Teacher spread0.292 · 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

Citations6
Published2015
Admission routes1
Has abstractyes

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