7 papers
Physics-Inspired Probabilistic Computing for Extremely Large-Scale MIMO Detection in Future 6G Wireless Systems
Andrea Grimaldi, Christian Duffee, Eleonora Raimondo +8
Extremely large-scale multiple-input multiple-output (XL-MIMO) architectures are a key enabler of forthcoming 6G wireless communication networks by allowing high data rates through…
High-Parallel FPGA-Based Discrete Simulated Bifurcation for Large-Scale Optimization
Fabrizio Orlando, Deborah Volpe, Giacomo Orlandi +3
Combinatorial Optimization (CO) problems exhibit exponential complexity, making their resolution challenging. Simulated Adiabatic Bifurcation (aSB) is a quantum-inspired algorithm…
Graph Neural Network-Based Predictor for Optimal Quantum Hardware Selection
Antonio Tudisco, Deborah Volpe, Giacomo Orlandi +1
The growing variety of quantum hardware technologies, each with unique peculiarities such as connectivity and native gate sets, creates challenges when selecting the best platform…
Multi-VQC: A Novel QML Approach for Enhancing Healthcare Classification
Antonio Tudisco, Deborah Volpe, Giovanna Turvani
Accurate and reliable diagnosis of diseases is crucial in enabling timely medical treatment and enhancing patient survival rates. In recent years, Machine Learning has revolutioniz…
AEQUAM: Accelerating Quantum Algorithm Validation through FPGA-Based Emulation
Lorenzo Lagostina, Deborah Volpe, Maurizio Zamboni +1
This work presents AEQUAM (Area Efficient QUAntum eMulation), a toolchain that enables faster and more accessible quantum circuit verification. It consists of a compiler that trans…
Quantum Machine Learning in Healthcare: Evaluating QNN and QSVM Models
Antonio Tudisco, Deborah Volpe, Giovanna Turvani
Effective and accurate diagnosis of diseases such as cancer, diabetes, and heart failure is crucial for timely medical intervention and improving patient survival rates. Machine le…