MétaCan
Menu
Back to cohort
Record W2788707467 · doi:10.1088/1361-648x/aac500

Collective excitations in Weyl semimetals in the hydrodynamic regime

2018· article· en· W2788707467 on OpenAlexafffund
P. O. Sukhachov, É. V. Gorbar, I. A. Shovkovy, V. A. Miransky

Bibliographic record

VenueJournal of Physics Condensed Matter · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTopological Materials and Phenomena
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaDirectorate for Mathematical and Physical SciencesNational Academy of Sciences of Ukraine
KeywordsPhysicsChiral anomalyDispersion relationQuasiparticleQuantum electrodynamicsHall effectMagnetic fieldCondensed matter physicsMomentum (technical analysis)Electric fieldAnomaly (physics)Field (mathematics)Dispersion (optics)Quantum mechanicsFermionSuperconductivity

Abstract

fetched live from OpenAlex

Abstract The spectrum of collective excitations in Weyl materials is studied by using consistent hydrodynamics. The corresponding framework includes the vortical and chiral anomaly effects, as well as the dependence on the separations between the Weyl nodes in energy b 0 and momentum . The latter are introduced via the Chern–Simons contributions to the electric current and charge densities in Maxwell’s equations. It is found that, even in the absence of a background magnetic field, certain collective excitations (e.g. the helicon-like modes and the anomalous Hall waves) are strongly affected by the chiral shift . In a background magnetic field, the existence of the distinctive longitudinal and transverse anomalous Hall waves with a linear dispersion relation is predicted. They originate from the oscillations of the electric charge density and electromagnetic fields, in which different components of the fields are connected via the anomalous Hall effect in Weyl semimetals.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.567
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.259
Teacher spread0.246 · 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

Citations20
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Physics Condensed MatterSame topicTopological Materials and PhenomenaFrench-language works237,207