Optical signal infrastucture in a SPICE-based optoelectronic simulation framework
Bibliographic record
Abstract
In this paper, an optical signal infrastructure using a novel simulation framework is presented for self-consistent optoelectronic circuits and systems. This framework uses a formulation based on modified nodal analysis and can be used for transient and small-signal analysis. A flexible representation of optical signals and elements is developed that is appropriate for circuits/systems which incorporate both electrical and optical devices. With the correct choice of optical state variables it is found that optical interference, reflection and coupling can be modeled efficiently. Optical models for multi-mode fibers, optical connectors and cross-couplers are presented as examples of model development within the framework. To illustrate the use of the framework, results from a number of optoelectronic circuits are presented. These examples include optical links involving lasers, multi-mode fibers, optical connectors and photodiodes. Results from these examples highlight the ability of the framework to handle a wide variety of optical effects and to simulate mixed electrical/optical circuits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".