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Record W2036824778 · doi:10.1364/oe.16.000567

A photonic analog-to-digital conversion scheme using Mach-Zehnder modulators with identical half-wave voltages

2008· article· en· W2036824778 on OpenAlexafffund
Hao Chi, Jianping Yao

Bibliographic record

VenueOptics Express · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsVoltageMach–Zehnder interferometerBiasingPhotonicsPhysicsOpticsQuantization (signal processing)Electro-optic modulatorOptical modulatorComputer scienceInterferometryPhase modulationAlgorithm

Abstract

fetched live from OpenAlex

A novel photonic analog-to-digital conversion scheme implemented using an array of Mach-Zehnder modulators (MZMs) with identical half-wave voltages is proposed and demonstrated. It is different from the scheme proposed by Taylor where the MZMs should have geometrically scaled half-wave voltages; the proposed scheme here uses MZMs with identical half-wave voltages, which eliminates the need for the MZMs to have very low half-wave voltages. By properly biasing the MZMs, the transfer functions of the MZMs are laterally shifted, which leads to the generation of a linear binary code to represent the analog input signal. The use of the MZMs with identical half-wave voltages simplifies greatly the design and implementation, which provides a high potential for integration. A proof-of-concept experiment for analog-to-digital conversion with a quantization level of 16 is demonstrated.

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 score0.003

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.032
GPT teacher head0.242
Teacher spread0.210 · 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

Citations47
Published2008
Admission routes2
Has abstractyes

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