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Record W2079087127 · doi:10.1063/1.4904102

Time-dependent quantum chemistry of laser driven many-electron molecules

2014· article· en· W2079087127 on OpenAlexafffund
T. T. Nguyen‐Dang, Étienne Couture-Bienvenue, Jérémy Viau-Trudel, Amaury Sainjon

Bibliographic record

VenueThe Journal of Chemical Physics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversité Laval
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsElectronLaserQuantum chemistryMoleculeChemical physicsQuantumChemistryPhysicsAtomic physicsQuantum mechanics

Abstract

fetched live from OpenAlex

A Time-Dependent Configuration Interaction approach using multiple Feshbach partitionings, corresponding to multiple ionization stages of a laser-driven molecule, has recently been proposed [T.-T. Nguyen-Dang and J. Viau-Trudel, J. Chem. Phys. 139, 244102 (2013)]. To complete this development toward a fully ab-initio method for the calculation of time-dependent electronic wavefunctions of an N-electron molecule, we describe how tools of multiconfiguration quantum chemistry such as the management of the configuration expansion space using Graphical Unitary Group Approach concepts can be profitably adapted to the new context, that of time-resolved electronic dynamics, as opposed to stationary electronic structure. The method is applied to calculate the detailed, sub-cycle electronic dynamics of BeH2, treated in a 3-21G bound-orbital basis augmented by a set of orthogonalized plane-waves representing continuum-type orbitals, including its ionization under an intense λ = 800 nm or λ = 80 nm continuous-wave laser field. The dynamics is strongly non-linear at the field-intensity considered (I ≃ 10(15) W/cm(2)), featuring important ionization of an inner-shell electron and strong post-ionization bound-electron dynamics.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.022
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.234
Teacher spread0.229 · 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 teacher head, 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

Citations17
Published2014
Admission routes2
Has abstractyes

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