Optically Controlled P–Cu<sub><i>x</i></sub>O-Based Artificial Synaptic Device for Neuromorphic Applications
Why this work is in the frame
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Bibliographic record
Abstract
Memristor-based optoelectronic artificial synapses have a great potential to enhance the efficiency of future neuromorphic computing. Like neurons of the retina, they have the potential to enable real-time visual preprocessing. This highlights the growing importance of improving optoelectronic artificial synapses for next-generation neuromorphic computing and neuromorphic visual systems. These artificial synapses can enhance neuromorphic visual systems, extending their capabilities beyond visible light. This study introduces a P-type copper oxide-based optical memristor device that exhibits fundamental biosynaptic characteristics like long-term potentiation (LTP) and long-term depression (LTD), which can be tuned using optical stimuli. These LTP/LTD characteristics were used as weights in a single-layer perceptron neural network to classify the MNIST data set using an off-chip training algorithm. We also demonstrated light-induced short-term plasticity and optical paired-pulse facilitation, which are the two important characteristics of neurons of the human retina that help in image preprocessing. We also implemented Pavlovian conditioning on the device using a combination of electrical and optical stimuli. These results indicate the possibility of using this device as an optically controlled artificial synaptic device for neuromorphic vision sensor applications.
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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) | 0.001 | 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 | 0.000 |
| 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