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Record W2275345686 · doi:10.1103/physrevb.93.235130

Theory of triplon dynamics in the quantum magnet<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>BiCu</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi>PO</mml:mi><mml:mn>6</mml:mn></mml:msub></mml:mrow></mml:math>

2016· article· lv· W2275345686 on OpenAlexaff
Kyusung Hwang, Yong Baek Kim

Bibliographic record

VenuePhysical review. B./Physical review. B · 2016
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsCanadian Institute for Advanced ResearchUniversity of Toronto
Fundersnot available
KeywordsValence (chemistry)PhysicsHamiltonian (control theory)AnisotropyValence bond theoryNeutron scatteringScatteringStatistical physicsCondensed matter physicsChemistryQuantum mechanicsMoleculeMathematics

Abstract

fetched live from OpenAlex

We provide a theory of triplon dynamics in the valence bond solid ground state of the coupled spin ladders modeled for ${\mathrm{BiCu}}_{2}{\mathrm{PO}}_{6}$. Utilizing the recent high-quality neutron scattering data [K. W. Plumb et al., Nat. Phys. 12, 224 (2016)] as guides and a theory of interacting triplons via the bond operator formulation, we determine a minimal spin Hamiltonian for this system. It is shown that the splitting of the low-energy triplon modes and the peculiar magnetic field dependence of the triplon dispersions can be explained by including substantial Dzyaloshinskii-Moriya and symmetric anisotropic spin interactions. Taking into account the interactions between triplons and the decay of the triplons to the two-triplon continuum via anisotropic spin interactions, we provide a theoretical picture that can be used to understand the main features of the recent neutron scattering experimental data.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research 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 score0.913
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0000.002
Science and technology studies0.0010.003
Scholarly communication0.0010.003
Open science0.0040.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1770.005

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 head0.020
GPT teacher head0.273
Teacher spread0.253 · 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

Citations16
Published2016
Admission routes1
Has abstractyes

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