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Record W2161481431 · doi:10.1109/ccece.2008.4564545

Programmable pulse shaping by using Liquid Crystal-Spatial Light Modulator (LC-SLM) for optical wireless communications

2008· article· en· W2161481431 on OpenAlexvenueno aff
S. You, M. Kavehrad

Bibliographic record

VenueConference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsSpatial light modulatorFemtosecond pulse shapingPulse shapingMultiphoton intrapulse interference phase scanUltrashort pulseOpticsMaterials scienceBandwidth-limited pulsePulse (music)Optical modulatorModulation (music)Optical wirelessLiquid crystal on siliconOptical modulation amplitudeOptical communicationWaveformElectronic engineeringPhase modulationLiquid crystalComputer scienceOptoelectronicsWirelessTelecommunicationsLaserPhysicsEngineeringPhase noiseOptical amplifierAcoustics

Abstract

fetched live from OpenAlex

We demonstrated programmable optical pulse shaping of femto-second laser pulse by using liquid crystal-spatial light modulator (LC-SLM). With a combination of amplitude and phase mask in LC-SLM, arbitrarily shaped ultra-short pulse waveforms could be synthesized by manipulating the frequency components which are spatially dispersed in the high-resolution zero-dispersion pulse shaping system. The specified shaped pulses, square root raised cosine (SRRC) and Meyer wavelet, are generated through the programmable pulse shaping system, which can potentially improve the performance of optical wireless communication system, for transmission through clouds.

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)0.000
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 score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.028
GPT teacher head0.228
Teacher spread0.200 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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