6 papers
PN-QNN: Harnessing Physical Noise as a Native Regularizer in Photonic Hybrid Quantum Neural Networks
Farah Elnakhal, Alberto Marchisio, Nouhaila Innan +2
Physical noise in near-term quantum hardware is usually treated as a nuisance to suppress. We ask whether it can instead act as a hardware-native regularizer for photonic hybrid qu…
Medical Imaging Classification with Cold-Atom Reservoir Computing using Auto-Encoders and Surrogate-Driven Training
Nuno Batista, Ana Morgado, Oscar Ferraz +3
We introduce a hybrid quantum-classical pipeline, based on neutral-atom reservoir computing, for medical image classification, focusing on the binary classification task of polyp d…
Enhancing Blood Cells Classification using Hybrid Quantum Neural Networks
Guilherme Cruz, Nouhaila Innan, Alberto Marchisio +2
Accurate classification of microscopic blood cells is still a critical task in medical image analysis, where subtle variations and limited data can challenge conventional deep lear…
Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices
Farah Elnakhal, Alberto Marchisio, Nouhaila Innan +2
Photonic quantum computing is a promising platform for scalable quantum machine learning, but designing effective hybrid architectures remains challenging under hardware and optimi…
GPU-Accelerated Syndrome Decoding for Quantum LDPC Codes below the 63 s Latency Threshold
Oscar Ferraz, Bruno Coutinho, Gabriel Falcao +3
This paper presents a GPU-accelerated decoder for quantum low-density parity-check (QLDPC) codes that achieves sub- s latency, below the surface code decoder's real-time thr…
An Experimental Exploration of In-Memory Computing for Multi-Layer Perceptrons
Pedro Carrinho, Hamid Moghadaspour, Oscar Ferraz +4
In modern computer architectures, the performance of many memory-bound workloads (e.g., machine learning, graph processing, databases) is limited by the data movement bottleneck th…