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Record W4317214308 · doi:10.1103/physreva.107.012610

Spin-induced multipartite steady-state entanglement of motional modes in hexagonal boron nitride membranes

2023· article· en· W4317214308 on OpenAlexaff
Nahid Yazdi, Vahid Salari, Roohollah Ghobadi

Bibliographic record

VenuePhysical review. A/Physical review, A · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsQuantum entanglementCondensed matter physicsSpin (aerodynamics)PhysicsBoron nitrideCoupling (piping)Quantum computerMagnetic fieldQuantum mechanicsMaterials scienceQuantumNanotechnology

Abstract

fetched live from OpenAlex

In this paper, we focus on a scheme in which three high-quality-factor mechanical modes of a hexagonal boron nitride (hBN) membrane monolayer are coupled to a common optically addressable spin defect present in the membrane via magnetic field interaction. We show that this coupling induces an effective phonon-phonon interaction in the dispersive regime and under appropriate magnetic field and microwave modulation. We derive the Langevin-Heisenberg equations of motion for vibrational modes to analyze optimal parameter regimes for reaching a physically stable system. We also investigate the effect of coupling strength on purity and entanglement. Our results demonstrate that bipartite and genuinely tripartite steady-state entanglement between different vibrational modes of hBN may be achieved in a broad spectrum of experimental parameters. This study has the potential to enable scalability to be implemented for the generation of two-dimensional continuous-variable cluster states for universal quantum computation.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.255
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.030
GPT teacher head0.374
Teacher spread0.343 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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