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Record W4282827566 · doi:10.1139/cjp-2021-0335

The transition from the classical to the quantum regime for rubidium-87 (<sup>87</sup>Rb) vapor in terms of the second virial coefficient and the scattering length

2022· article· en· W4282827566 on OpenAlexvenueno aff
Abeer A. Al Ajaleen, A. S. Sandouqa, H. B. Ghassib

Bibliographic record

VenueCanadian Journal of Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCold Atom Physics and Bose-Einstein Condensates
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsVirial coefficientScattering lengthQuantum mechanicsFeynman diagramScatteringQuantumAtomic physicsBosonBose–Einstein condensateCondensed matter physics

Abstract

fetched live from OpenAlex

This work focuses on two major properties of 87 Rb gas for a very broad temperature range of ∼nK–3000 K. The first is the second virial coefficient B, encompassing both classical ( B cl ) and quantum ( B q ) regimes as well as, in between, the classical coefficient plus the first quantum correction ( B qcl ). The transition from the classical to the quantum regime in this system is explored. The second property is the s-wave scattering length a 0 for both singlet [[Formula: see text]] and triplet [[Formula: see text]] states. The medium is incorporated into the picture via the Galitskii–Migdal–Feynman formalism. Its main output is the medium phase shifts for the system, using the “best” available interatomic potential. These are plugged into the Beth–Uhlenbeck formula to give B q , whereas B c l and B qcl are readily calculated from standard expressions, the only input needed being the binary potential. Our results show that B q exhibits clear demarcation from B cl , especially at nK temperatures where Bose–Einstein condensation (BEC) manifests itself. Comparison to other calculations in the literature is made only for B cl ; B q for this gas is computed here for the first time, as are [Formula: see text] and [Formula: see text] for the medium. It turns out that these scattering lengths are larger than their vacuum counterparts at BEC temperatures.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.203
Teacher spread0.193 · 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 designTheoretical or conceptual
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

Citations2
Published2022
Admission routes1
Has abstractyes

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