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Many-body approximations to the superfluid gap and critical temperature in pure neutron matter

2022· article· en· W4280539827 on OpenAlexafffund
M. Drissi, Arnau Rios

Bibliographic record

VenueThe European Physical Journal A · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCold Atom Physics and Bose-Einstein Condensates
Canadian institutionsTRIUMF
FundersAgencia Estatal de InvestigaciónScience and Technology Facilities CouncilTRIUMF
KeywordsSuperfluidityPhysicsPairingAnsatzCondensed matter physicsFermi gasNeutronNuclear matterConstant (computer programming)Fermi Gamma-ray Space TelescopeRange (aeronautics)Quantum mechanicsSuperconductivityNuclear physicsMaterials scienceNucleon

Abstract

fetched live from OpenAlex

Abstract We compute singlet pairing gaps and critical temperatures in pure neutron matter with different many-body approximations. Medium effects tend to reduce gaps and critical temperatures compared to the standard BCS ansatz. In the mean-field approximation, the ratio of these two quantities remains constant across a wide range of densities. This constant ratio is close to the universal prediction of BCS theory, whether three-neutron interactions are included or not. Using a more sophisticated many-body approach that incorporates the effect of short-range correlations in pairing properties, we find that the gap to critical temperature ratio in the low-density regime is substantially larger than the BCS prediction, independently of the interaction. In this region, our results are relatively close to experiments and theoretical calculations from the unitary Fermi gas. We also find evidence for a different density dependence of zero-temperature gaps and critical temperatures in neutron matter.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.325
Threshold uncertainty score0.650

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.241
Teacher spread0.232 · 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

Citations13
Published2022
Admission routes2
Has abstractyes

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