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Record W4297846629 · doi:10.21203/rs.3.rs-1407116/v1

A spatial beam property analyzer based on dispersive crystal diffraction for low-emittance X-ray light sources

2022· preprint· en· W4297846629 on OpenAlexafffund
Nazanin Samadi, Xianbo Shi, Cigdem Ozkan Loch, Juraj Krempaský, Michael Boege, Dean Chapman, Marco Stampanoni

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsUniversity of Saskatchewan
FundersBasic Energy SciencesNatural Sciences and Engineering Research Council of CanadaUniversity of SaskatchewanPaul Scherrer InstitutU.S. Department of Energy
KeywordsMonochromatorOpticsBeamlineWigglerDiffractionThermal emittanceSynchrotronBeam (structure)Beam divergenceSynchrotron radiationCrystal (programming language)Characterization (materials science)Advanced Photon SourceMaterials scienceSynchrotron Radiation SourceLaser beam qualityPhysicsLaserCathode rayElectronComputer science

Abstract

fetched live from OpenAlex

Abstract The advent of low-emittance synchrotron x-ray sources and free-electron lasers urges the development of novel diagnostic techniques for measuring and monitoring the spatial source properties, especially the source sizes. This work introduces an x-ray beam property analyzer based on a multi-crystal diffraction geometry, including a crystal-based monochromator and a Laue crystal in a dispersive setting to the monochromator. By measuring the flat beam and the transmitted beam profiles, the system can provide a simultaneous high-sensitivity characterization of the source size, divergence, position, and angle in the diffraction plane of the multi-crystal system. Detailed theoretical modeling predicts the system’s feasibility as a versatile characterization tool for monitoring the x-ray source and beam properties. The experimental validation was conducted at a bending magnet beamline at the Swiss Light Source by varying the machine parameters. A measurement sensitivity of less than 10% of a source size of around 12 μm is demonstrated. The proposed system offers a compact setup with simple x-ray optics and can also be utilized for monitoring the electron source.

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)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.027
GPT teacher head0.360
Teacher spread0.333 · 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
GenreMethods

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

Citations0
Published2022
Admission routes2
Has abstractyes

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