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Record W4383533460 · doi:10.1103/physreva.108.013703

Effects of environment correlations on the onset of collective decay in waveguide QED

2023· article· en· W4383533460 on OpenAlexafffund
Alberto Del Angel, Pablo Solano, P. Barberis-Blostein

Bibliographic record

VenuePhysical review. A/Physical review, A · 2023
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsCanadian Institute for Advanced Research
FundersFondo Nacional de Desarrollo Científico y TecnológicoDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoComisión Nacional de Investigación Científica y TecnológicaCanadian Institute for Advanced Research
KeywordsPhysicsDielectricLorentz transformationAtom (system on chip)Work (physics)WaveguideElectromagnetic fieldField (mathematics)Quantum electrodynamicsDielectric functionQuantum mechanicsStatistical physics

Abstract

fetched live from OpenAlex

We analyze the dynamics of one and two two-level atoms interacting with the electromagnetic field in the vicinity of an optical nanofiber without making either the Born or the Markov approximations. We model the dielectric response of the nanofiber with a constant dielectric function and the Drude-Lorentz model, observing deviations from the standard super- and subradiant decays. We discuss the validity of approximating the speed of atom-atom communication to the group velocity of the guided field in the presence of nontrivial environment correlations. Our work presents a deeper understanding of the validity of commonly used approximations in recent waveguide QED platforms.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.015
GPT teacher head0.314
Teacher spread0.299 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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