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Record W2969195235 · doi:10.1103/physreva.101.033601

Pairing in two-dimensional Fermi gases with a coordinate-space potential

2020· article· en· W2969195235 on OpenAlexafffund
Tash Zielinski, Bernard Ross, Alexandros Gezerlis

Bibliographic record

VenuePhysical review. A/Physical review, A · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCold Atom Physics and Bose-Einstein Condensates
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceCanada Foundation for Innovation
KeywordsPairingPhysicsDiffusion Monte CarloCrossoverStatistical physicsSpace (punctuation)Coordinate spaceFermi Gamma-ray Space TelescopeRange (aeronautics)Fermi gasMonte Carlo methodWork (physics)Ground stateQuantum mechanicsMathematicsGeometryMonte Carlo molecular modelingComputer science

Abstract

fetched live from OpenAlex

In this work we theoretically study pairing in two-dimensional Fermi gases, a system which is experimentally accessible using cold atoms. We start by deriving the mean-field pairing gap equation for a coordinate-space potential with a finite interaction range and proceed to solve this numerically. We find that for sufficiently short effective ranges the answer is identical to the zero-range one. We then use diffusion Monte Carlo to evaluate the total energy for many distinct particle numbers; we employ several variational parameters to produce a good ground-state energy and then use these results to extract the pairing gap across a number of interaction strengths in the strongly interacting two-dimensional crossover. Extracting the gap via the odd-even energy staggering, our microscopic results can be used as benchmarks for other theoretical approaches.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.326
Teacher spread0.311 · 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.

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

Citations8
Published2020
Admission routes2
Has abstractyes

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