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Record W4225368616 · doi:10.21203/rs.3.rs-1582812/v1

Energy cascades in polaritonic systems with energetic disorder observed by ultrafast two-dimensional white-light spectroscopy

2022· preprint· en· W4225368616 on OpenAlexfundno aff
Minjung Son, Zachary T. Armstrong, Ryan T. Allen, Abitha Dhavamani, Michael S. Arnold, Martin T. Zanni

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicStrong Light-Matter Interactions
Canadian institutionsnot available
FundersAir Force Office of Scientific ResearchPolytechnique Montréal
KeywordsSpectroscopyUltrashort pulsePhysicsWhite lightAtomic physicsMaterials scienceOpticsAstronomyLaser

Abstract

fetched live from OpenAlex

Abstract Exciton-polaritons are hybrid states formed when molecular excitons are strongly coupled to photons trapped in an optical cavity. These systems have many attractive properties, including large delocalization lengths, but questions regarding the role of energetic disorder remain unanswered. Here, we fabricate microcavities with two different layers of semiconducting carbon nanotubes as a way of controlling the energetic disorder and exploring its impact on energy transfer. Using ultrafast two-dimensional white-light spectroscopy, we observe a delayed growth of a cross peak between the upper- and lower-polariton states. Using Redfield theory, we assign the growth to cascading energy transfer down a manifold of new electronic states created by energetic disorder that is of comparable magnitude to the light-matter coupling. These results broaden our understanding of energy transfer dynamics in exciton-polariton systems beyond the Rabi contraction picture and enable control over how energy is transported in polaritonic systems.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.331
Teacher spread0.305 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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