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Record W2515120116 · doi:10.1021/acs.jpclett.6b01551

Impact of Vibrational Coherence on the Quantum Yield at a Conical Intersection

2016· article· en· W2515120116 on OpenAlexaff
Hong-Guang Duan, R. J. Dwayne Miller, Michael Thorwart

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsUniversity of Toronto
FundersDeutsche ForschungsgemeinschaftMax-Planck-GesellschaftJoachim Herz Stiftung
KeywordsConical intersectionWave packetCoherence (philosophical gambling strategy)Conical surfacePhysicsQuantumExcited stateQuantum mechanicsMathematicsGeometry

Abstract

fetched live from OpenAlex

We study the vibrationally coherent quantum dynamics of an electronic wave packet in the vicinity of a conical intersection within a three-state two-mode model. By transforming the coherent tuning and coupling modes into the bath, the underdamped dynamics of the resulting effective three-state model is solved efficiently by the numerically exact hierarchy equation of motion approach. The transient excited-state absorption and two-dimensional spectra reveal the impact of vibrational coherence on the relaxation pathways of the wave packet. We find that both the quantum yield and the isomerization rate are crucially influenced by the vibrational coherence of the wave packet. A less coherent wave packet can traverse the conical intersection more rapidly, while the resulting quantum yield is smaller. Finally, we show that repeated passages of the wave packet through the conical intersection can lead to measurable interference effects in the form of Stueckelberg oscillations.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.015
GPT teacher head0.267
Teacher spread0.251 · 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

Citations34
Published2016
Admission routes1
Has abstractyes

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