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Record W3027242299 · doi:10.1109/jlt.2020.2996188

800G DSP ASIC Design Using Probabilistic Shaping and Digital Sub-Carrier Multiplexing

2020· article· en· W3027242299 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

VenueJournal of Lightwave Technology · 2020
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsDigital signal processingApplication-specific integrated circuitMultiplexingTransmission (telecommunications)Computer scienceComputer hardwareElectronic engineeringEmbedded systemEngineeringTelecommunications

Abstract

fetched live from OpenAlex

The design of application-specific integrated circuits (ASIC) is at the core of modern ultra-high-speed transponders employing advanced digital signal processing (DSP) algorithms. This manuscript discusses the motivations for jointly utilizing transmission techniques such as probabilistic shaping and digital sub-carrier multiplexing in digital coherent optical transmissions systems. First, we describe the key-building blocks of modern high-speed DSP-based transponders working at up to 800G per wave. Second, we show the benefits of these transmission methods in terms of system level performance. Finally, we report, to the best of our knowledge, the first long-haul experimental transmission – e.g., over 1000 km – with a real-time 7 nm DSP ASIC and digital coherent optics (DCO) capable of data rates up to 1.6 Tb/s using two waves (2 × 800G).

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.051
GPT teacher head0.228
Teacher spread0.177 · 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