5 papers · 1 filter
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…
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…
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…
A Predictive Approach for Selecting the Best Quantum Solver for an Optimization Problem
Deborah Volpe, Nils Quetschlich, Mariagrazia Graziano +2
Leveraging quantum computers for optimization problems holds promise across various application domains. Nevertheless, utilizing respective quantum computing solvers requires descr…
Towards an Automatic Framework for Solving Optimization Problems with Quantum Computers
Deborah Volpe, Nils Quetschlich, Mariagrazia Graziano +2
Optimizing objective functions stands to benefit significantly from leveraging quantum computers, promising enhanced solution quality across various application domains in the futu…