13 papers
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…
Scalable Quantum Machine Learning via Multi-layer Fully-Connected Variational Quantum Circuits
Howard Su, Chen-Yu Liu, Samuel Yen-Chi Chen +2
Variational Quantum Circuits (VQC) are promising models for quantum machine learning, but standard monolithic architectures face an expressivity--trainability dilemma: small circui…
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…
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…
Federated Quantum Kernel Learning for Anomaly Detection in Multivariate IoT Time-Series
Kuan-Cheng Chen, Samuel Yen-Chi Chen, Chen-Yu Liu +1
The rapid growth of industrial Internet of Things (IIoT) systems has created new challenges for anomaly detection in high-dimensional, multivariate time-series, where privacy, scal…
You Only Measure Once: On Designing Single-Shot Quantum Machine Learning Models
Chen-Yu Liu, Leonardo Placidi, Kuan-Cheng Chen +2
Quantum machine learning (QML) models conventionally rely on repeated measurements (shots) of observables to obtain reliable predictions. This dependence on large shot budgets lead…