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Pinch-points to half-moons and up in the stars: The kagome skymap

2023· article· en· W4321783087 on OpenAlexaff
Dominik Kiese, Francesco Ferrari, Nikita Astrakhantsev, Nils Niggemann, Pratyay Ghosh, Tobias Müller, Ronny Thomale, Titus Neupert, Johannes Reuther, Michel J. P. Gingras, Simon Trebst, Yasir Iqbal

Bibliographic record

VenuePhysical Review Research · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Condensed Matter Physics
Canadian institutionsUniversity of Waterloo
FundersLeibniz-RechenzentrumGauss Centre for SupercomputingNational Research Center "Kurchatov Institute"Forschungszentrum JülichNational Science FoundationIndo-French Centre for the Promotion of Advanced ResearchIndian Institute of Technology MadrasAbdus Salam International Centre for Theoretical PhysicsDeutsche ForschungsgemeinschaftSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungLeibniz-GemeinschaftRussian Science FoundationRussell Sage FoundationInternational Centre for Theoretical SciencesAlexander von Humboldt-StiftungFreie Universität BerlinDepartment of Science and Technology, Ministry of Science and Technology, IndiaSimons Foundation
KeywordsPhysicsGround stateRenormalization groupCondensed matter physicsAntiferromagnetismSpin (aerodynamics)CoulombQuantum mechanicsElectron

Abstract

fetched live from OpenAlex

In frustrated magnetism, pinch point singularities are telltale signatures of Coulomb spin liquids. A discussion of nonanalytic features like half-moons in the static structure factor of Kagome antiferromagnets relates them to real-space pinwheel states and includes the effect of quantum fluctuations.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0020.004
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.110
GPT teacher head0.470
Teacher spread0.360 · 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 designSimulation or modeling
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

Citations34
Published2023
Admission routes1
Has abstractyes

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