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Record W4362607047 · doi:10.1103/physrevb.107.165302

Reanalysis of experimental determinations of polariton-polariton interactions in microcavities

2023· article· en· W4362607047 on OpenAlexaff
David W. Snoke, V. Hartwell, Jonathan Beaumariage, Shouvik Mukherjee, Yoseob Yoon, David Moffat Myers, Mark Steger, Zheng Sun, Keith A. Nelson, L. N. Pfeiffer

Bibliographic record

VenuePhysical review. B./Physical review. B · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStrong Light-Matter Interactions
Canadian institutionsPolytechnique Montréal
FundersNational Science Foundation
KeywordsPolaritonPhotonPhysicsResonance (particle physics)ExcitonBeam (structure)Transmission (telecommunications)Condensed matter physicsAtomic physicsComputational physicsQuantum mechanicsOpticsTelecommunications

Abstract

fetched live from OpenAlex

Inside solids, photons can become strongly interacting, which allows the possibility of optical transistors, in a which one light beam controls the transmission of another light beam. The strength of this interaction can be greatly increased in specially designed structures in which the photon frequency is near an electronic resonance known as an exciton. The exact value of this interaction strength has been much debated, ranging over orders of magnitude. This paper reviews a set of experiments and argues for a number well below some earlier estimates, but still large compared to the predictions of standard theory calculations.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.422
Teacher spread0.398 · 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 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

Citations21
Published2023
Admission routes1
Has abstractyes

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