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Record W2065434728 · doi:10.1063/1.1627752

Nonadiabatic reaction rates for dissipative quantum-classical systems

2003· article· en· W2065434728 on OpenAlexaff
Alessandro Sergi, Raymond Kapral

Bibliographic record

VenueThe Journal of Chemical Physics · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDissipative systemQuantumDegrees of freedom (physics and chemistry)Classical limitPhysicsClassical mechanicsQuantum dynamicsQuantum mechanics

Abstract

fetched live from OpenAlex

The dynamics of a quantum system which is directly coupled to classical degrees of freedom is investigated. The classical degrees of freedom are in turn coupled to a classical bath whose detailed dynamics is not of interest. The resulting quantum-classical evolution equations are dissipative as a result of coupling to the classical heat bath. The dissipative quantum-classical dynamics is used to study nonadiabatic chemical reactions and compute their rates. The reactive flux correlation formalism for the calculation of nonadiabatic rate constants is generalized to dissipative quantum-classical dynamics and implemented in terms of averages over surface-hopping Langevin trajectory segments. The results are illustrated for a simple quantum-classical two-state model. The techniques developed in this paper can be applied to complex classical environments encountered, for example, in proton and electron transfer processes in the condensed phase where local environmental degrees of freedom must be treated explicitly but the remainder of the environment can be treated simply as a heat bath.

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)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.298
Teacher spread0.278 · 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

Citations24
Published2003
Admission routes1
Has abstractyes

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