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Record W1987206214 · doi:10.1063/1.1730156

Coarse-grained controllability of wavepackets by free evolution and phase shifts

2004· article· en· W1987206214 on OpenAlexafffund
E. A. Shapiro, Misha Ivanov, Yuly Billig

Bibliographic record

VenueThe Journal of Chemical Physics · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsCarleton UniversitySteacie Institute for Molecular Sciences
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsControllabilityWave packetDiscretizationStark effectPhysicsPhase (matter)Phase spaceHilbert spaceClassical mechanicsAction (physics)Field (mathematics)Orbit (dynamics)Quantum mechanicsMathematical analysisMathematicsElectric fieldApplied mathematicsPure mathematics

Abstract

fetched live from OpenAlex

We describe an approach to controlling wavepacket dynamics and a criterion of wavepacket controllability based on discretized properties of the wavepacket's localization on the orbit. The notion of "coarse-grained control" and the coarse-grained description of the controllability in infinite-dimensional Hilbert spaces are introduced and studied using the mathematical apparatus of loop groups. We prove that 2D rotational wavepackets are controllable by only free evolution and phase kicks by AC Stark shift implemented at fractional revivals. This scheme works even if the AC Stark shifts can have only a smooth coordinate dependence, correspondent to the action of a linearly polarized laser field.

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: Simulation or modeling · 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 studies0.0000.002
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 head0.008
GPT teacher head0.263
Teacher spread0.255 · 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

Citations7
Published2004
Admission routes2
Has abstractyes

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