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Three Phase-Grating Moiré Neutron Interferometer for Large Interferometer Area Applications

2018· article· en· W2746108445 on OpenAlexafffund
Dusan Sarenac, D. A. Pushin, M. G. Huber, D. S. Hussey, Houxun Miao, M. Arif, D. G. Cory, Alex Cronin, B. Heacock, David L. Jacobson, Jacob M. LaManna, Han Wen

Bibliographic record

VenuePhysical Review Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsCanadian Institute for Advanced ResearchPerimeter InstituteUniversity of Waterloo
FundersNIST Center for Neutron ResearchNatural Sciences and Engineering Research Council of CanadaNational Institute of Standards and TechnologyCanada First Research Excellence FundU.S. Department of CommerceCanada Excellence Research Chairs, Government of CanadaU.S. Department of Energy
KeywordsInterferometryMoiré patternOpticsGratingAstronomical interferometerPhase (matter)NeutronPhysicsDiffraction gratingMaterials scienceNuclear physics

Abstract

fetched live from OpenAlex

We demonstrate a three phase-grating moiré neutron interferometer in a highly intense neutron beam as a robust candidate for large area interferometry applications and for the characterization of materials. This novel far-field moiré technique allows for broad wavelength acceptance and relaxed requirements related to fabrication and alignment, thus circumventing the main obstacles associated with perfect crystal neutron interferometry. We observed interference fringes with an interferometer length of 4 m and examined the effects of an aluminum 6061 alloy sample on the coherence of the system. Experiments to measure the autocorrelation length of samples and the universal gravitational constant are proposed and discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.334
Teacher spread0.305 · 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 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

Citations45
Published2018
Admission routes2
Has abstractyes

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