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…
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…
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…
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 th…
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…