On Sparse Placement of Regenerator Nodes in Translucent Optical Network
Why this work is in the frame
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Bibliographic record
Abstract
Since the optical reach (the distance an optical signal can travel before its quality degrades to a level that necessitates regeneration) ranges from 500 to 2000 miles, regeneration of optical signals is essential to establish lightpaths of lengths greater than the optical reach. In a translucent optical network, the optical signal is regenerated at selected nodes of the network before the signal quality degrades below a threshold. Given the optical reach of the signal, to minimize the overall network design cost, the goal of the regenerator placement problem is to find the minimum number of regenerators necessary in the network, so that every pair of nodes is able to establish a lightpath (either transparent or translucent) between them. In this paper, we study the regenerator placement problem and prove that the problem is NP-complete. We formulate the regenerator placement problem as a connected dominating set problem in a labeled graph (LCDS) and provide a procedure for computing it. We evaluate the effectiveness of our approach using a number of networks.
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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