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Record W2912396945 · doi:10.1117/12.2523353

Generation and development of polarization speckle based on random walks of polarization phasor

2019· article· en· W2912396945 on OpenAlexaff
Wei Wang, Tim K. Lee, Steen G. Hanson, Mitsuo Takeda

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Polarization and Ellipsometry
Canadian institutionsUniversity of British Columbia
FundersUniversität StuttgartHeriot-Watt University
KeywordsPhasorPolarization (electrochemistry)Speckle patternPolarizerOpticsPhysicsPolarization rotatorStokes parametersRandom walkMathematicsScatteringQuantum mechanicsStatistics

Abstract

fetched live from OpenAlex

In this paper, we review our recent work on the statistical properties of polarization speckle with its unique properties of random polarization states fluctuating in space. From random walks of polarization phasor, we provide the origins of the polarization speckle by taking the vector nature into account for stochastic electric fields. Based on the random polarization phasor sum as an extension of conventional random phasor sum, the first and second moments of the Stokes parameters of the resultant polarization speckle have been examined. Two types of devices for polarization optics, i.e. rough-surfaced retardation plate and random polarizer array, will be introduced as the physical realization of the desired phenomena of polarization speckles. Some statistical properties of the stochastic electric fields are reviewed in order to understand the performance of these two polarization optics devices for generation and development of the polarization speckle.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.014
GPT teacher head0.213
Teacher spread0.199 · 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 designSimulation or modeling
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

Citations0
Published2019
Admission routes1
Has abstractyes

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