From the 2 of 22 linked papers with an AI index.
1 citations · 1 across the 7 of their papers we have counts for
14 papers · 1 filter
OSNR/GSNR Prediction in Brownfield Links via a DLM-Anchored Hybrid Physics/ML Model
Agastya Raj, Venkata Virajit Garbhapu, Hiroyuki Ishihara +5
The paper proposes a hybrid physics‑based and machine‑learning model anchored by a digital line model (DLM) to accurately predict per‑channel power, OSNR, and GSNR in existing (bro…
Spectrum Configuration Framework for Throughput Maximization in Open Systems with Roll-Off-Based QoT Optimization
Peyman Pahlevanzadeh, Venkata Virajit Garbhapu, Agastya Raj +3
We propose a spectrum-configuration framework for open and disaggregated optical systems that maximizes throughput while guaranteeing the quality of transmission (QoT) margins. The…
A Zero Added Loss Multiplexing (ZALM) Source Simulation
Jerry Horgan, Alexander Nico-Katz, Shelbi L. Jenkins +6
Zero Added Loss Multiplexing (ZALM) offers broadband, per channel heralded EPR pairs, with a rich parameter space that allows its performance to be tailored for specific applicatio…
Beyond Redundancy: Toward Agile Resilience in Optical Networks to Overcome Unpredictable Disasters
Toru Mano, Hideki Nishizawa, Takeo Sasai +9
Resilience in optical networks has traditionally relied on redundancy and pre-planned recovery strategies, both of which assume a certain level of disaster predictability. However,…
Entanglement Purification With Finite Latency Classical Communication in Quantum Networks
Vivek Vasan, Alexander Nico-Katz, Boulat A. Bash +2
Quantum networks rely on high fidelity entangled pairs distributed to nodes, but maintaining their fidelity is challenged by environmental decoherence during storage. Entanglement…
Generalized few-shot transfer learning architecture for modeling the EDFA gain spectrum
Agastya Raj, Zehao Wang, Tingjun Chen +2
Accurate modeling of the gain spectrum in Erbium-Doped Fiber Amplifiers (EDFAs) is essential for optimizing optical network performance, particularly as networks evolve toward mult…