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Record W2313697964 · doi:10.1103/physreva.86.023416

Characterization of laser cooling in a high-magnetic-field atom trap

2012· article· en· W2313697964 on OpenAlexfundno aff
Elise Paradis, Stefan Zigo, Kong‐Qiu Hu, Georg Raithel

Bibliographic record

VenuePhysical Review A · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCold Atom Physics and Bose-Einstein Condensates
Canadian institutionsnot available
FundersChemical Sciences, Geosciences, and Biosciences DivisionBasic Energy SciencesNatural Sciences and Engineering Research Council of CanadaOffice of Science
KeywordsPhysicsAtomic physicsAtom (system on chip)TrappingLaser coolingMagnetic trapMagneto-optical trapMagnetic fieldSpectral lineTrap (plumbing)Doppler coolingField (mathematics)LaserOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

We describe cooling and trapping of both ${}^{85}$Rb and ${}^{87}$Rb in a range of magnetic fields up to 2.6 T. Atoms are injected from a low-field pyramidal magneto-optical trap and recaptured in a high-magnetic-field atom trap. The atoms are cooled and trapped by a six-beam optical molasses via the $5{S}_{1/2}|{m}_{I},{m}_{J}=$ 1/2$\ensuremath{\rangle}$$\ensuremath{\rightarrow}$ $5{P}_{3/2}|{m}_{I},{m}_{J}=$ 3/2$\ensuremath{\rangle}$ transition (${m}_{I}=$ 5/2 for ${}^{85}$Rb and ${m}_{I}=$ 3/2 for ${}^{87}$Rb). We study the trap fluorescence spectra, atom temperatures, density distributions, and lifetimes as a function of magnetic field and detuning parameters. The trap fluorescence spectra are both narrow and asymmetric, as is characteristic for laser cooling of atoms in an external trapping potential. The trap is modeled using a Monte Carlo trajectory simulation technique.

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 score0.388
Threshold uncertainty score0.476

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 head0.012
GPT teacher head0.270
Teacher spread0.258 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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