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20242026
most citedA Multilevel Framework for Partitioning Quantum Circuits

6 citations · 14 across the 10 of their papers we have counts for

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quant-ph2026

Architecture-Aware Reinforcement Learning for Communication-Efficient Distributed Quantum Circuit Compilation

Chien-Tung Kuo, Felix Burt, Samuel Yen-Chi Chen +2

Distributed quantum computing provides a scalable route for executing quantum circuits beyond the capacity limits of a single quantum processing unit (QPU), but it introduces a com…

quant-ph2026

Photonic Quantum-Enhanced Knowledge Distillation

Kuan-Cheng Chen, Shang Yu, Chen-Yu Liu +10

Photonic quantum processors naturally produce intrinsically stochastic measurement outcomes, offering a hardware-native source of structured randomness that can be exploited during…

quant-ph2026

Consensus Protocols for Entanglement-Aware Scheduling in Distributed Quantum Neural Networks

Kuan-Cheng Chen, Samuel Yen-Chi Chen, Mahdi Chehimi +2

The realization of distributed quantum neural networks (DQNNs) over quantum internet infrastructures faces fundamental challenges arising from the fragile nature of entanglement an…

quant-ph2025

Adaptive Resource Orchestration for Distributed Quantum Computing Systems

Kuan-Cheng Chen, Felix Burt, Nitish K. Panigrahy +1

Scaling quantum computing beyond a single device requires networking many quantum processing units (QPUs) into a coherent quantum-HPC system. We propose the Modular Entanglement Hu…

quant-ph20254 cited

Entanglement-Efficient Distribution of Quantum Circuits over Large-Scale Quantum Networks

Felix Burt, Kuan-Cheng Chen, Kin K. Leung

Quantum computers face inherent scaling challenges, a fact that necessitates investigation of distributed quantum computing systems, whereby scaling is achieved through interconnec…

quant-ph2025

Distributed Quantum Neural Networks on Distributed Photonic Quantum Computing

Kuan-Cheng Chen, Chen-Yu Liu, Yu Shang +2

We introduce a distributed quantum-classical framework that synergizes photonic quantum neural networks (QNNs) with matrix-product-state (MPS) mapping to achieve parameter-efficien…