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Record W2517214291 · doi:10.1038/srep31903

All-optical analog comparator

2016· article· en· W2517214291 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsOptech (Canada)
FundersTaiyuan University of TechnologyNational Natural Science Foundation of China
KeywordsComparatorComputer scienceSIGNAL (programming language)Analog signalElectronic engineeringOptoelectronicsPhysicsComputer hardwareDigital signal processingVoltageEngineering

Abstract

fetched live from OpenAlex

An analog comparator is one of the core units in all-optical analog-to-digital conversion (AO-ADC) systems, which digitizes different amplitude levels into two levels of logical '1' or '0' by comparing with a defined decision threshold. Although various outstanding photonic ADC approaches have been reported, almost all of them necessitate an electrical comparator to carry out this binarization. The use of an electrical comparator is in contradiction to the aim of developing all-optical devices. In this work, we propose a new concept of an all-optical analog comparator and numerically demonstrate an implementation based on a quarter-wavelength-shifted distributed feedback laser diode (QWS DFB-LD) with multiple quantum well (MQW) structures. Our results show that the all-optical comparator is very well suited for true AO-ADCs, enabling the whole digital conversion from an analog optical signal (continuous-time signal or discrete pulse signal) to a binary representation totally in the optical domain. In particular, this all-optical analog comparator possesses a low threshold power (several mW), high extinction ratio (up to 40 dB), fast operation rate (of the order of tens of Gb/s) and a step-like transfer function.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.016
GPT teacher head0.230
Teacher spread0.215 · 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