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Record W3042323557 · doi:10.1021/acs.jpclett.0c02000

Entropy Reorders Polariton States

2020· article· en· W3042323557 on OpenAlexfundno aff
Gregory D. Scholes, Courtney A. DelPo, Bryan Kudisch

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStrong Light-Matter Interactions
Canadian institutionsnot available
FundersDivision of Graduate EducationCanadian Institute for Advanced ResearchGordon and Betty Moore Foundation
KeywordsPolaritonPhysicsExcited stateCoherence (philosophical gambling strategy)Statistical physicsEntropy (arrow of time)Quantum decoherencePhotonQuantum mechanicsCondensed matter physicsQuantum

Abstract

fetched live from OpenAlex

The main result is that the long-range phase coherence of the polariton states formed by strong coupling between a photon mode in a cavity and an ensemble of molecules leads to exceptionally low entropy of the upper and lower polariton states, starkly contrasting with the dark states. That result means that spectroscopy does not correctly order the free energy of the excited states because there is a significant entropic contribution to the free energy, which turns out to comparable to the electronic energy gap between the lower polariton state and the dark-state manifold. The reordered states, according to their free energy, is important to predict the potential of polariton states for reactivity, to predict spontaneous photophysical dynamics, or to understand their decoherence. The entropic contribution adds to the polariton electronic gap, rendering states surprisingly more reactive than anticipated from the input excitation energy. This apparently "additional" reactivity, evident from the thermodynamics, suggests how the low entropy of highly coherent states can be exploited as a resource.

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)0.002
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.007
GPT teacher head0.232
Teacher spread0.225 · 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

Citations96
Published2020
Admission routes1
Has abstractyes

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