8 citations · 17 across the 25 of their papers we have counts for
28 papers
Identifiability in Quantum State, Process, and Network Tomography
Athira Kalavampara Raghunadhan, Matheus Guedes De Andrade, Don Towsley +3
Quantum State Tomography (QST), Quantum Process Tomography (QPT), and Quantum Network Tomography (QNT) are related parameter-estimation problems that aim to reconstruct different p…
Identifiability and Estimation Precision in Quantum Network Tomography with Imperfect Bell-State Measurements
Athira Kalavampara Raghunadhan, Matheus Guedes De Andrade, Don Towsley +3
We study Quantum Network Tomography (QNT) for end-to-end link-error characterization under imperfect Bell-state measurements (BSMs), where multiplicative coupling between link and…
Radio-Optical Confluence in Intelligent Edge Networks
Akshita Gupta, Devika Dass, Agastya Raj +4
Challenges associated with densification of radio access networks are motivating exploration of more efficient and scalable architectures. We examine recent progress in one directi…
Emulation of Entanglement Distribution Networks on a Quantum Computer
Ashley N. Tittelbaugh, Jerry Horgan, Rohan Bali +4
We investigate how quantum computers can be used to emulate quantum networks and study their performance under practical impairments. In particular, we evaluate how degraded entang…
OSNR/GSNR Prediction in Brownfield Links via a DLM-Anchored Hybrid Physics/ML Model
Agastya Raj, Venkata Virajit Garbhapu, Hiroyuki Ishihara +5
We present a DLM-anchored hybrid physics/ML framework for brownfield optical links that accurately predicts per-channel power, OSNR, and GSNR. Calibrating span/ILA boundaries via D…
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…
Learnability, Identifiability, and Monitor Placement in Quantum Network Tomography
Athira Kalavampara Raghunadhan, Matheus Guedes De Andrade, Don Towsley +3
Reliable quantum communication requires accurate characterization of the quantum links. This paper studies Quantum Network Tomography (QNT) under limited monitoring resources, wher…
Measurement Strategies and Estimation Precision in Quantum Network Tomography
Athira Kalavampara Raghunadhan, Matheus Guedes De Andrade, Don Towsley +3
This work investigates measurement strategies for link parameter estimation in Quantum Network Tomography (QNT), where network links are modeled as depolarizing quantum channels di…
Optical Network Digital Twin -- Practical Use Cases and Architecture
Hideki Nishizawa, Toru Mano, Kazuya Anazawa +17
With the widespread adoption of AI, machine-to-machine communications are rapidly increasing, reshaping the requirements for optical networks. Recent advances in Gaussian noise mod…
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…
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…
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,…
Heterogeneous Transmission of Analog Radio and Digital Coherent Signals Over Multi-Span Metro and PON for Bandwidth-Efficient Fronthaul in mmWave Centralized RAN Networks [Invited]
Devika Dass, Dan Kilper, Liam Barry +1
We experimentally investigate the transparent coexistence of heterogeneous Analog Radio-over-Fiber (ARoF) and Digital Coherent Optical (DCO) signals in a converged metro/PON networ…
Interference Detection in Spectrum-Blind Multi-User Optical Spectrum as a Service
Agastya Raj, Daniel C. Kilper, Marco Ruffini
With the growing demand for high-bandwidth, low-latency applications, Optical Spectrum as a Service (OSaaS) is of interest for flexible bandwidth allocation within Elastic Optical…
Coexistence of Digital Coherent, mmWave and sub-THz Analog RoF Services using OSaaS over converged access-metro live production network
Devika Dass, Amol Delmade, Agastya Raj +4
We demonstrate the end-to-end transmission of digital coherent and analog radio-over-fiber signals, at mmWave and sub-THz frequencies, over the HEAnet live production metro network…
Real-Time Streaming Telemetry Based Detection and Mitigation of OOK and Power Interference in Multi-User OSaaS Networks
Agastya Raj, Devika Dass, Daniel C. Kilper +1
We present a framework to identify and mitigate rogue OOK signals and user-generated power interference in a multi-user Optical-Spectrum-as-a-Service network. Experimental tests on…
Transfer Learning for EDFA Gain Modeling: A Semi-Supervised Approach Using Internal Amplifier Features
Agastya Raj, Dan Kilper, Marco Ruffini
The gain spectrum of an Erbium-Doped Fiber Amplifier (EDFA) has a complex dependence on channel loading, pump power, and operating mode, making accurate modeling difficult to achie…
Interference Identification in Multi-User Optical Spectrum as a Service using Convolutional Neural Networks
Agastya Raj, Zehao Wang, Frank Slyne +3
We introduce a ML-based architecture for network operators to detect impairments from specific OSaaS users while blind to the users' internal spectrum details. Experimental studies…
Multi-Span Optical Power Spectrum Evolution Modeling using ML-based Multi-Decoder Attention Framework
Agastya Raj, Zehao Wang, Frank Slyne +3
We implement a ML-based attention framework with component-specific decoders, improving optical power spectrum prediction in multi-span networks. By reducing the need for in-depth…
Modular and Integrated AI Control Framework across Fiber and Wireless Networks for 6G
Merim Dzaferagic, Marco Ruffini, Daniel Kilper
The rapid evolution of communication networks towards 6G increasingly incorporates advanced AI-driven controls across various network segments to achieve intelligent, zero-touch op…
Experimental Evaluation of an SDN Controller for Open Optical-circuit-switched Networks
Kazuya Anazawa, Takeru Inoue, Toru Mano +12
Open optical networks have been considered to be important for cost-effectively building and operating the networks. Recently, the optical-circuit-switches (OCSes) have attracted i…
Control Protocol for Entangled Pair Verification in Quantum Optical Networks
Vivek Vasan, Anuj Agrawal, Alexander Nico-Katz +4
We consider quantum networks, where entangled photon pairs are distributed using fibre optic links from a centralized source to entangling nodes. The entanglement is then stored (v…
Strategies for entanglement distribution in optical fiber networks
Hannah McAleese, Anuj Agrawal, Vivek Vasan +5
Distributing entanglement over long distances remains a challenge due to its fragility when exposed to environmental effects. In this work, we compare various entanglement distribu…
Decentralized Multi-Party Multi-Network AI for Global Deployment of 6G Wireless Systems
Merim Dzaferagic, Marco Ruffini, Nina Slamnik-Krijestorac +21
Multiple visions of 6G networks elicit Artificial Intelligence (AI) as a central, native element. When 6G systems are deployed at a large scale, end-to-end AI-based solutions will…