Numerical Implementation of Wavelength-Dependent Photonic Spike Timing Dependent Plasticity Based on VCSOA
Bibliographic record
Abstract
We propose to realize photonic spike timing dependent plasticity (STDP) by using a vertical-cavity semiconductor optical amplifier (VCSOA) subject to dual optical pulse injections. The computational model of the photonic STDP is presented for the first time based on the well-known Fabry-Pérot approach. Through numerical simulations, the dependences of photonic STDP on the bias current of VCSOA and the input powers are analyzed carefully. Besides, the effect of the initial wavelength detuning on the photonic STDP is also explored. It is found that, the current scheme requires much lower bias current and input power to obtain controllable STDP curve when compared with the previously reported photonic STDP circuits; the initial wavelength detuning is an effectively controllable parameter to realize wavelength-dependent photonic STDP. The computational model of the photonic STDP based on a VCSOA is interesting and valuable for numerically simulating of large-scale photonic spiking neural network, and provides a guideline to design low power consumption photonic neuromorphic systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".