Vertical-Cavity Surface-Emitting Lasers Specifically Designed for Integration with Electronic Circuits
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.
Bibliographic record
Abstract
Several of the authors of this chapter have worked, at various times, on developing what is called “optoelectronic-VLSI” (OE-VLSI) technology, the intimate integration of photonic devices with VLSI electronics. The general purpose is to give the electronics the option of communicating through optical interconnects. Most of that work, thus far, has focused on using the multiple quantum well electro- absorption (MQWEA) diode as the photonic device, primarily because the MQWEA diode can serve both as a detector and as a modulator, for data reception and for data transmission, respectively. In a monolithic integration approach, the MQWEA diodes were cofabricated with GaAs field-effect transistors (FETs) to produce optoelectronic circuits. This technology produced several system demonstrators and was the basis of a multiproject foundry shuttle of optoelectronic chips to research groups around the world. It was obvious from the start that this monolithic approach would have needed a huge development effort to become a VLSI technology, on the scale of the one that produced the silicon CMOS VLSI technology. Funds for such a large effort could not be justified. However, since the system demonstrators produced encouraging results, attention turned to a hybrid approach, whereby arrays of MQWEA diodes are flip-chip solder-bump bonded to CMOS chips, arguably the most advanced electronic VLSI technology. Soon thereafter, this hybrid technology produced many more system demonstrators and was the basis of several multiproject foundry shuttles of optoelectronic chips to research groups around the world. A true OE-VLSI technology was emerging, just as strong arguments developed for the advantages of OE-VLSI technology in general; these were summarized in.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it