10 citations · 32 across the 11 of their papers we have counts for
11 papers
Fidelity-Aware Scheduling of Quantum Circuits on Multi-QPU Systems
Innocenzo Fulginiti, Antonio Tudisco, Salvatore Zammuto +7
High Performance Computing-Quantum Computing (HPCQC) platforms expose multiple Quantum Processing Units (QPUs) that may differ in size, topology, native gates, and noise characteri…
FIREQ: FPGA Instrumentation for Readout and Qubit control
Giuseppe La Capra, Fabio Calabrese, Giorgio D'Amico +8
We present FIREQ (FPGA Instrumentation for Readout and Qubit control), an open-source RFSoC-based framework for the control and readout of superconducting qubits. FIREQ combines a…
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…
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…
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…
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…