3 papers
cs.LG2025
Evaluating Angle and Amplitude Encoding Strategies for Variational Quantum Machine Learning: their impact on model's accuracy
Antonio Tudisco, Andrea Marchesin, Maurizio Zamboni +2
Recent advancements in Quantum Computing and Machine Learning have increased attention to Quantum Machine Learning (QML), which aims to develop machine learning models by exploitin…
quant-ph2025
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…
quant-ph2024
AMARETTO: Enabling Efficient Quantum Algorithm Emulation on Low-Tier FPGAs
Christian Conti, Deborah Volpe, Mariagrazia Graziano +2
Researchers and industries are increasingly drawn to quantum computing for its computational potential. However, validating new quantum algorithms is challenging due to the limitat…