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Record W2037464397 · doi:10.1117/12.625007

Extend focal depth of a tracking lens by phase apodizers

2005· article· en· W2037464397 on OpenAlexaff
Xianyang Cai, Shoude Chang, Costel Flueraru

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrbital Angular Momentum in Optics
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsLens (geology)Focal lengthCardinal pointOpticsTracking (education)Focal pointComputer sciencePoint spread functionPhase (matter)Depth of fieldDiffractionEntrance pupilField of viewPhysicsPupil

Abstract

fetched live from OpenAlex

In a conventional particle tracking system, the depth of field is usually very small because of the use of high power imaging lens. The tracking accuracy may also be affected by the smearing of spot image, caused by focal shift. Increasing the focal depth and keeping uniform spot size in the focal region is highly desirable for a high accurate tracking system. In this report, we study the design of phase apdodizer that could be used to increase the focal depth of a tracking lens. The design is based on the requirements by highly accurate tracking that the point-spread function (PSF) of the lens keep an even and concentrated energy distribution when the lens is defocused. To achieve this purpose, a pure phase-shifting apodizer is introduced on the pupil plane of the lens. The function of the apodizer is to control the energy distribution of the 3D diffraction pattern near the focal region and make the effective spot size uniform or minimum variation along optical axis. The pattern of the 3D PSF of the lens with the apodizer shapes closed to a cylinder. New method used to search and optimize the design of the phase apodizer that meet the requirements of a particle tracking system will be studied. Theoretical analysis and numerical simulation are given in support of the method.

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 categoriesMeta-epidemiology (narrow)
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 score0.394
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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 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

Citations0
Published2005
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicOrbital Angular Momentum in OpticsFrench-language works237,207