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Cavity control of nonlinear phononics

2021· article· en· W2989989337 on OpenAlexfundno aff

Bibliographic record

VenuePhysical Review Research · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStrong Light-Matter Interactions
Canadian institutionsnot available
FundersDefense Advanced Research Projects AgencyDeutsche ForschungsgemeinschaftCanadian Institute for Advanced ResearchSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungGordon and Betty Moore FoundationU.S. Department of EnergyHarvard UniversityNational Science Foundation
KeywordsExcited statePhononRedistribution (election)Resonance (particle physics)Nonlinear systemScatteringDegrees of freedom (physics and chemistry)Normal mode

Abstract

fetched live from OpenAlex

Nonlinear interactions between phonon modes govern the behavior of vibrationally highly excited solids and molecules. Here we demonstrate theoretically control over the redistribution of energy from a highly excited coherent infrared-active phonon state into other vibrational degrees of freedom of the system using optical cavities. Specifically, we tune the polaritonic splitting of an infrared-active mode in the cavity so that it is pushed into resonance with other phonon modes of the system. This technique makes it possible to tune the efficiency of energy redistribution and even to change the underlying scattering mechanism, which possibly enables the creation of phonon-induced states in a broad scale of materials that do not naturally exhibit the required resonance conditions.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.462
Teacher spread0.393 · 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 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

Citations34
Published2021
Admission routes1
Has abstractyes

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