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Record W3013846719 · doi:10.1051/epjconf/201921906001

Overview of neutron interferometry at NIST

2019· article· en· W3013846719 on OpenAlexafffund
M. G. Huber, Shannon Fogwell Hoogerheide, M. Arif, R. Haun, F. E. Wietfeldt, T. C. Black, Chandra Shahi, B. Heacock, A. R. Young, Ivar Taminiau, Dusan Sarenac, David G. Cory, D. A. Pushin

Bibliographic record

VenueEPJ Web of Conferences · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsPerimeter InstituteUniversity of Waterloo
FundersRIKENNatural Sciences and Engineering Research Council of CanadaNational Institute of Standards and TechnologyCanada Excellence Research Chairs, Government of CanadaU.S. Department of EnergyCanada First Research Excellence FundNational Science Foundation
KeywordsNISTInterferometryCoherence (philosophical gambling strategy)NeutronOpticsFabricationPhysicsMachiningNuclear engineeringComputer scienceEngineeringNuclear physicsMechanical engineeringQuantum mechanics

Abstract

fetched live from OpenAlex

Neutron interferometry at the National Institute of Standards and Technology is a well-established program that performs experiments in a wide range of areas including materials science, quantum information, precision measurements of coherent and incoherent scattering lengths, and dark energy/fifth force searches. Central to the continued success of this program is the further understanding and elimination of instabilities and coherence-losses whether they are from thermal, vibrational, or dynamical sources. We have spent considerable effort in fabricating new interferometer crystals which have higher maximum fringe visibilities and that can be tailored to specific experiments. We describe the current facilities and a new post-machining fabrication process of crystal annealing.

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 categoriesInsufficient payload (model declined to judge)
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 score0.735
Threshold uncertainty score0.997

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)0.0040.000

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 head0.025
GPT teacher head0.279
Teacher spread0.254 · 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

Citations5
Published2019
Admission routes2
Has abstractyes

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