Robust power control of single sink optical networks with time-delays
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Bibliographic record
Abstract
We study the stability of game-theoretic based power control algorithms on multi-link optical networks in the presence of time-delays and uncertainties. The control algorithms, originally developed in the absence of time-delays and uncertainties, adjust the signal powers at the transmitters to solve the optical signal-to-noise ratio (OSNR) optimization problem. This minimizes the bit error rate of the signal channels. We apply the game-theoretic framework to a perturbed OSNR model in the presence of time-delays. Uncertainties in the OSNR model appear as norm-bounded uncertainties in the noise powers, system gains, and channel powers. The time-delays are due to signal propagation between the channel sources and OSNR output. We restrict our analysis to single sink network topologies. A primal-dual control scheme ensures convergence to the Nash equilibrium, and OSNR optimization. The resultant closed-loop system has two time-scales. Robust stability in the presence of time-delays is established via singular perturbation theory modified for Lyapunov-Krasovskii theory.
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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 | 0.000 |
| 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